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Abstract

Nickel has several industrial uses and is a valuable metal, making its selective separation and recycling a priority goal. A novel adsorbent, a Schiff base organically modified silica (ORMOSIL) aerogel, was prepared, for selective nickel removal from wastewater with other metal ions, by including a salen ionophore in the silica-based network. The newly developed adsorbent takes advantage of the salen’s selectivity and of the high porosity of silica aerogels. The aerogel-like adsorbent was prepared via sol-gel chemistry, using a coprecursor approach and ambient pressure drying. The inclusion of the Schiff base in the silica network was accomplished by reacting an amine-containing silica precursor with an aldehyde and confirmed by nuclear magnetic resonance (NMR) analysis. The adsorbent shrunk only 10% after evaporative drying, which resulted in a highly porous material (85% porosity, 4 cm³ g⁻¹ specific pore volume). The low surface area of 28 m² g^-1 was due to the predominantly macroporous structure of the material (mean pore diameter of 563 nm). Adsorption isotherms and kinetic curves with single and binary mixtures of cations at room temperature were used to assess the selectivity of the adsorbent. The adsorption follows a BET (Brunauer-Emmett-Teller) trend. Due to the proximity of the oxygen and nitrogen atoms in the salen and steric hindrance from their neighboring atoms, it is likely that only the smallest hydrated cations can act as a coordination center and interact with both donor atoms. Thus, nickel was fairly removed (50 mg g^-1), while other cations barely interacted with the adsorbent (cadmium adsorption maximum of 5 mg g^-1). The estimated selectivity coefficient for nickel ranges from 1.8, in relation to copper, to 9.4 relatively to cadmium, which can be relevant for the separation of nickel in several industrial contexts, for instance, from electroplating sludge.

1. Introduction

Heavy metals (HMs) are pollutants that accumulate in the environment, and due to high emissions from human activities, create severe levels of pollution in water courses, sediments, and soils [1, 2]. They are mobile hence leach and are absorbed by organisms, further spreading through ecosystems [3–7]. This issue can be overcome by stopping the pollutant emissions and/or deploying advanced waste treatment techniques. Moreover, many heavy metals are used as raw materials in different industries [8, 9] and have commercial value [9, 10]. Among them, we can cite copper, lead, cadmium, and nickel. They feature high toxicity and are prone to human-made emissions and accumulation in the environment, and concomitantly, they are relevant resources in today’s societies [8, 11, 12]. Copper is the third most important metal by weight [13]; its yearly production is estimated at 16 million tons [9, 14] and is used in electrical equipment (60% of its consumption), plumbing/construction, machinery, transport, coins, art, music instruments, kitchen utensils [11, 13], and to catalyze many reactions [15–17]. Copper is also a micronutrient in animals and plants. Lead and its related compounds are very toxic [18]. Most recent uses of lead [18] have been banned, such as gasoline additives, in solders, paint pigments, and the EU plans to ban lead ammunition and fishing gear [19]. It is still used for lead-acid batteries and as radiation shields [11]. No biological functions are known [18]. Cadmium is highly toxic. It can be applied as a stabilizer in plastics, pigment in dyes, coating agents, accessories/jewelry, Ni-Cd rechargeable batteries, and solar cells [20, 21], with the latter two contributing to impulse its use [21]. The EU has banned it from being used in plastics, paints, and jewelry [22]. In this paper, we focus our particular interest in nickel due to its increasing market value. Nickel is ferromagnetic at room temperature [11] and is known to catalyze reactions [23]. It is used for the production of metal alloys (stainless steel totals 75% of its consumption [24]), nickel cast iron (jewelry, coins), corrosion-resistant coatings by electroplating, and the production of batteries (nickel-metal hydride and Li-ion) [11, 25, 26]. Nickel has biological functions in plants and cyanobacteria [26]. Due to the aforementioned reasons, nickel is a valuable metal, so the minimization of its pollutant discharges, through separation and recovery, has economic impact on businesses. Furthermore, these also contribute to a more circular and sustainable economy, which many countries are promoting.

Several treatment techniques can be applied to remove heavy metals from wastewaters. These were fully described in a recent review of the authors [1]. However, only a few can be used for the simultaneous goal of recovering the cation being removed from water: ion exchange [27–29], adsorption [30–36], and electroplating [27, 28, 37] are the most effective ones. As such, operating these methods with high efficiency and low-cost at large scale is crucial to promote the recovery of metals as valuable resources. Both adsorption processes rely on the development of high performing materials (the ion exchanger and adsorbent, respectively) that are modified to be selective, while electrolysis can be employed for multiple species by assembling an electrolytic cell and adjusting electric potential on demand. However, a major drawback relies on the fact that electrochemical processes are expensive and only viable in cases where wastewater are not highly contaminated. On the other hand, adsorption processes are simple in operation and design, and their cost is mostly associated with the sorbent materials [27, 28, 37]. Natural materials as well as engineered ones have been used as adsorbents for heavy metals, and the number of published research on the topic has been increasing [1].

Schiff bases are the most common family of molecules used as nickel ionophores [38]. They are considered a subclass of imines and are obtained by a condensation reaction of a primary amine and a carbonyl precursor, e.g., an aldehyde [39]. These molecules can be multidentate and are generally based on nitrogen or oxygen donors but can also include phosphor and sulfur [39]. The formation of the ligand-nickel (II) complex was studied with different Schiff bases by several authors developing colorimetric nickel sensors (in which the response to the cation is measured by absorbance in the ultraviolet-visible region or by fluorescence), and it was found that the stability constant is very high (log $K > 5$ ) [40–44]. Ganjali et al. [43] confirmed the ligand’s selectivity by evaluating the stability constant towards copper (log $K = 5.9$ for Ni (II) vs. 4.2 for Cu (II)).

A particular case of Schiff base, salens (symmetrical tetradentate molecules with two nitrogen and two oxygen donor atoms [39]) were studied by Gupta and coauthors [44, 45]. They have successfully used salens as ionophores in ion sensing electrodes with poly(vinyl chloride) membranes [44, 45]. In one of the works, the authors have proposed two distinct molecules as nickel ionophores (Figure 1), both with very high affinity for nickel (log $K > 7$ for Ni (II) and <4.2 for the remaining cations) [44]. In the literature, the use of salens can also be found for the modification of MCM (Mobil Composition of Matter) and SBA (Santa Barbara Amorphous) particles [46–52], silica gel [53], or silica composites [54], in order to promote salen-metal cation complexes. However, only three works using silica-based materials, by Enache et al. [52], Kursunlu et al. [53], and Qiao et al. [54], are reporting adsorption studies. It should be mentioned that salens are also reported as copper ionophores [55, 56], responding selectively to this cation and exhibiting very high stability constants (log $K = 4.2$ [55] or 8.4 [56]). So, the selectivity of the Schiff base ligand must be influenced by the nonelectron donor groups in the molecule that affect, for instance, its overall size and accessibility of ions to the electron donor groups.

Figure 1

Representation of the ionophore molecules developed by Gupta et al. [44]. Proposed groups responsible for cation sorption are presented in blue.

In this work, we report the development of a selective adsorbent for nickel, obtained by modifying the silica matrix of a silica aerogel with hemi-salen functional groups. Thus, a highly porous and selective adsorbent is obtained. To the best of our knowledge, it is the first time a silica aerogel is modified using such a functional group. The modified aerogel-like monolith is tested in batch tests to assess its suitability and selectivity against common relevant cations.

2. Materials and Methods

2.1. Materials

As silica sources, methyltriethoxysilane (MTES, ≥99%), tetraethyl orthosilicate (TEOS, 98%), and (3-aminopropyl) trimethoxysilane (APTMS, ≥97%) were purchased from Sigma-Aldrich and used as received. Salicylaldehyde (p.a., Merck) was used to obtain the hemi-salen modifying groups on the silica matrix. Anhydrous oxalic acid (≥99%, Sigma-Aldrich) and ammonium hydroxide (25% NH₃ in H₂O, Sigma-Aldrich) were the sol-gel chemistry catalysts. Methanol (MeOH, 99.8%, VWR) and ethanol (EtOH, ≥99.8%, Fisher) were used as solvents. Deuterated methanol (CD₃OD, 99.8%, Eurisotop) and 3-(trimethylsilyl) propionic acid sodium salt (TMSP, 98%, Eurisotop) were used as solvent and internal reference for NMR spectroscopy. Heavy metal solutions were prepared using copper (II) nitrate hemipentahydrate (p.a., Chem-Lab), lead (II) nitrate (≥99.0%, Sigma-Aldrich), cadmium (II) nitrate tetrahydrate (≥99.0%, Sigma-Aldrich), and nickel (II) nitrate hexahydrate (crystals, Sigma-Aldrich). High purity water was used whenever needed. Nitric acid (65%, Fisher) was used to adjust the pH of solutions.

2.2. Modification of APTMS Co-precursor

The addition of a Schiff base functional group to the silica matrix was achieved by modifying the organic group in a silicon alkoxide precursor. The reaction between the primary amine of APTMS and salicylaldehyde was promoted [46, 47], resulting in a hemi-salen modified silica precursor (HSPTMS, (E)-2-(((3-(trimethoxysilyl)propyl)imino)methyl)phenol), as shown in Figure 2.

Figure 2

Schematic representation of the HSPTMS formation reaction. Proposed groups responsible for cation adsorption are presented in blue, and the groups that take part in the reaction are shown in green.

APTMS and salicylaldehyde were mixed in methanol with a 10 mol% excess of salicylaldehyde. This mixture, labelled as A, was stirred until homogenization and left to react in an oven for 24 hours at 27°C. The mixture turned yellow instantly, indicating the formation of the hemi-salen.

2.3. Synthesis of Schiff Base-Modified ORMOSIL Aerogel-Like Monolith

To prepare silica aerogels with the HSPTMS precursor, MTES was diluted in methanol and hydrolyzed (0.1 M oxalic acid). After one day, the hydrolyzed MTES, mixture B, was mixed with the so-called mixture A and stirred. After a couple of minutes, TEOS and then the basic catalyst (1 M ammonium hydroxide) were added. All sol-gel steps were carried out at 27°C. The Si: solvent: water molar ratios in the sol were kept at 1 : 12 : 8, and the silica co-precursors were mixed in an 50/35/15 molar percentage for MTES, TEOS, and HSPTMS, respectively. Gelation and aging occurred in an oven at 27°C for six days. Aged gels were demolded and washed by being immersed in hot ethanol for a total of six days, with ethanol being changed every day. Finally, the gel monoliths were dried in an oven for three days at 60°C.

2.4. Characterization

The formation of HSPTMS was investigated via NMR (Bruker Biospin GmbH, ¹H spectra collected at 400 MHz and ¹³C spectra collected at 100 MHz). ¹H and ¹³C spectra for both reactants and HSPTMS were obtained by dissolution in deuterated methanol. The analysis of the ¹³C spectrum did not contribute with additional information relatively to the ¹H spectrum analysis, and thus, it is not shown. HSPTMS was obtained directly from mixture A via evaporation of the solvent.

The characterization routines of aerogels are described in previous works by the authors [57, 58]. Bulk and skeletal densities were used to obtain adsorbent porosity. Bulk density of the adsorbents was obtained by weighting the samples and measuring their dimensions on the three axes. Skeletal density was obtained with ground samples by He pycnometry (Accupyc 1330, Micrometrics). Linear shrinkage was calculated from the change in diameter of the dried sample comparatively to the gelation mold. The BET specific surface area was obtained through nitrogen adsorption (ASAP 2000, Micrometrics). Pore volume and average pore size were calculated in accordance with a previous work [59]. Microstructure observation was performed with field-emission scanning electron microscopy (FE-SEM) (Merlin Compact/VPCompact FESEM, Carl Zeiss Microscopy GmbH) [60, 61]. Fourier transform infrared spectroscopy (FTIR) (FT/IR 4200, Jasco) was performed, being the spectra obtained with KBr pellets in the wavenumber range of 4000 to 400 cm⁻¹, with 128 scans and a resolution of 4 cm⁻¹. C, H, and N content of powdered samples was determined by elemental analysis (EA 1108 CHNS-O, Fisons). Zeta potential measurements of an aqueous suspension of the sample nanoparticles (0.1%, $w / v$ ) at pH 4 were carried out by electrophoretic light scattering (Zetasizer NanoZS ZN 3500, Malvern Instruments); the suspension was dispersed in an ultrasound bath for 10 minutes, and the pH was adjusted by the addition of HCl just before measurements. The elemental composition of loaded adsorbent samples was estimated with energy-dispersive X-ray spectroscopy, EDS (X-Max^N Silicon Drift EDS Detector, Oxford Instruments).

Heavy metal concentration in solutions was determined by flame atomic absorption spectroscopy (AAS) with an acetylene-air flame (939 AAS, Unicam).

To provide insight on the interactions with the different ions, the geometry of hydrolyzed HSPTMS in water was computed. The system was composed of a box, with the precursor molecule surrounded by 632 water molecules, of dimensions $2.6520 nm \times 3.1410 nm \times 2.4120 nm$ , and with full periodic boundary conditions. The simulation was conducted in CP2K v7.1 [62] using the Geometry, Frequency, Noncovalent, eXtended Tight Binding (GFN-xTB) with the DFT-D3 dispersion correction [63, 64] as electronic model.

2.5. Adsorption Tests

Adsorption experiments followed the procedures used previously [57, 58, 65]. The aerogel-like monolith was prepared for adsorption by milling and selecting particles within a size range of 75 to 250 μm. Batch adsorption tests were conducted by mixing the powdered adsorbent and the cation solution in a test flask, shaken in a rotational stirrer at speed setting 16 rpm (REAX 20, Heidolph Instruments) with an adsorbent dose of 2 g L⁻¹ at pH 4 and 25°C. When the test ended, the solution was filtered, and the concentration of the filtrate was determined. For comparison, a silica aerogel without the Schiff base modification was tested in the same conditions.

Isotherm studies were performed by varying the adsorbate concentration from 20 to 500 mg L⁻¹ and conducted for 24 h. The selectivity of the Schiff base ORMOSIL aerogel-like monolith was studied in batch kinetic tests, with contact times ranging from 5 minutes to 24 h, with an adsorbate concentration of 100 mg L⁻¹ per cation. Binary mixtures containing copper and mixtures containing nickel plus copper and nickel ions isolated were tested.

The viability of recovering the adsorbed nickel was assessed by a desorption test performed with HCl and HNO₃ on nickel loaded particles (from the isotherm studies with a starting concentration of 100 mg L⁻¹). The loaded adsorbent was shaken with a 1 M solution of the desorption agent for three hours.

A minimum of two replicates were obtained for all reported data points.

2.6. Analysis of Adsorption Data

All physical quantities and adsorption model parameters here described are defined with mass units. While discussing binary mixtures, these are expressed in molar units when required. Adsorption capacity ( $q_{t}$ or $q_{e}$ if equilibrium is reached, mg g⁻¹) was calculated from the initial ( $C_{0}$ , mg L⁻¹) and final concentrations ( $C_{t}$ or $C_{e}$ , mg·L⁻¹, respectively), adsorbent mass ( $m$ , g), and solution volume ( $V$ , L) according to Equation (1). Time $t$ is expressed in hours. Selectivity was calculated with Equation (2) using the molar adsorption capacity after 24 hours. $\begin{matrix} (1) & q = \frac{V (C_{0} - C)}{m}, \\ (2) & α_{1, 2} = \frac{q_{1}}{q_{2}} . \end{matrix}$

Freundlich, BET, and Langmuir-Henry models were fitted to the equilibrium data to interpret the metal ion-adsorbent interactions. The pseudo-first order and pseudo-second order models, as well as a modified pseudo-second order model that considers an initial adsorption, were tested to describe the kinetic data. The fits were performed using nonlinear algorithms, and their quality was assessed using Akaike and Bayesian information criteria [66].

The Freundlich model [67], Equation (3), describes the adsorption on heterogeneous surfaces [68]. It has two parameters: the Freundlich constant, $K_{F}$ ((mg g⁻¹) (L mg⁻¹)^1/n _F), that gives the relative adsorption capacity of the adsorbent, and the heterogeneity factor 1/n _F. The BET model [69] describes multilayer adsorption and was conceptualized for the adsorption of gaseous species. It can be expressed for liquids with Equation (4) [70], in which $q_{m}$ represents the monolayer adsorption capacity (mg g⁻¹), $K_{L}$ is the equilibrium constant for the first adsorbate layer (L mg⁻¹), and $K_{S}$ is the equilibrium constant for the upper layers. $C_{BET}$ is equal to $K_{L}$ divided by $K_{S}$ . The Langmuir-Henry model, Equation (5), combines both the Langmuir and Henry isotherms [71], describing adsorption both at active surface sites and by the dissolution of the sorbate inside the porous matrix. $K_{L}$ is the Langmuir constant and has the same meaning as in the BET isotherm (L mg⁻¹), and $K_{H}$ is the Henry constant (L g⁻¹). $\begin{matrix} (3) & q_{e} = K_{F} {C_{e}}^{1 / n_{F}}, \\ (4) & q_{e} = \frac{q_{m} K_{L} C_{e}}{(1 - K_{S} C_{e}) (1 - K_{S} C_{e} + K_{L} C_{e})}, \\ (5) & q_{e} = \frac{q_{m} K_{L} C_{e}}{1 + K_{L} C_{e}} + K_{H} C_{e} . \end{matrix}$

In the kinetic models used, the equilibrium uptake or adsorption capacity, $q_{e}$ , is a model parameter. In the pseudo-first order model [72], Equation (6), $k_{1}$ is the first order rate constant (h^-1). This model reveals that the adsorption is controlled by diffusion. A modified pseudo-second order equation, considering an initial adsorption, reveals an adsorption process controlled by the surface reaction and is described in Equation (7). In this model, $q_{0}$ (mg g⁻¹) represents the initial uptake, and the pseudo-second order adsorption rate constant corresponds to $k_{2}$ (g mg⁻¹ h⁻¹). If the initial uptake is negligible, the equation is reduced to the pseudo-second order model [73]. It was verified that modified silica-based aerogels adsorb heavy metals very quickly [58]; hence, an initial uptake of sorbate can be considered in some cases. This can be attributed to the metal amount adsorbed during the preparation of the tests (which is sometimes observed by changes in the aerogel color), before the flasks are shaken, which is considered the effective start of the test. The modified pseudo-second order model can describe these situations. $\begin{matrix} (6) & q_{t} = q_{e} (1 - e^{- k_{1} t}), \\ (7) & q_{t} = q_{0} + \frac{q_{e}^{2} k_{2} t}{q_{e} k_{2} t + 1}, \end{matrix}$

The intraparticle diffusion and Boyd models were further applied to have a deeper analysis of the adsorption of nickel on the aerogels (a similar analysis was not possible for copper due to its fast adsorption). The intraparticle diffusion model (presented by Weber and Morris) is based on Fick’s 2nd law equation [74, 75] and can be described through Equation (8) $\begin{matrix} (8) & \frac{q_{t}}{q_{e}} = A_{0, i} + k_{P, i} t^{0.5}, \end{matrix}$ where $A_{0}$ is a constant related with the thickness of the boundary layer, $k_{P}$ (s^−0.5) is the rate constant and depends on the diffusion coefficient, and $i$ is related with the number of steps governing the adsorption process. On the other hand, the Boyd model (also based on Fick’s 2nd law equation) was also shown to predict the rate limiting step through the computation of the intercept of a linear equation described as $B_{t} = m t + y_{0}$ , where $B_{t}$ is defined by Equation (9) for short adsorption times. $\begin{matrix} (9) & B_{t} = 2 π - \frac{{F π}^{2}}{3} - {(1 - \frac{π F}{3})}^{1 / 2} (0 < F < 0.85), \\ (10) & F = \frac{q_{t}}{q_{e}} . \end{matrix}$

If $y_{0} = 0$ , the rate limiting step is intraparticle diffusion; otherwise, film diffusion model governs the process [76, 77].

3. Results and Discussion

3.1. Schiff Base Reaction

The formation of HSPTMS, via the reaction illustrated in Figure 2, was studied, and the NMR spectra are presented in Figure 3. The formation of HSPTMS can be observed, namely, by the disappearance of the carbonyl group from salicylaldehyde (peak a, δ ~10 ppm) and the amine group in APTMS (peak b, δ ~2.7 ppm) in the product, and the appearance of a new proton associated with the C=N bond (peak a, δ ~8.4 ppm). Protons associated with the methoxy groups and propyl chain did not suffer changes in their chemical environment, while the ones associated with the aromatic ring (peaks b-e in the salicylaldehyde and HSPTMS spectra) suffered some alterations, due to a new chemical environment.

Figure 3

¹H NMR spectra for salicylaldehyde, APTMS, and HSPTMS.

3.2. Modified Aerogel-Like Monolith Characterization

The obtained modified silica aerogel-like monolith and its porous morphology are depicted in Figure 4. The physical/structural properties of the adsorbent are summarized in Table 1.

Figure 4

Photograph (a) and micrograph at ×30 k magnification (b) of the Schiff base-modified aerogel.

(b)

Table 1

Physical/structural properties of the functional aerogel-like monolith adsorbent.

Bulk density (g cm⁻³)	Skeletal density (g cm⁻³)	Porosity (%)	Linear shrinkage (%)	$S_{BET}$ (m² g⁻¹)	$V_{pore}$ (cm³ g⁻¹)	$D_{pore}$ (nm)
$0.22 \pm 0.04$	$1.396 \pm 0.004$	$85 \pm 3$	$10 \pm 3$	$27.7 \pm 0.3$	$3.9 \pm 0.8$	$563 \pm 122$

The ORMOSIL aerogel-like monolith samples feature a distinctive bright yellow color, due to the presence of the hemi-salen. Despite being dried by evaporation of the solvent, the gel remained a monolith and exhibits a small radial shrinkage, resulting in a bulk density and porosity similar to that of amine modified silica aerogels and contrasting to their xerogel counterparts [58]. The skeletal density of this adsorbent is lower than that of silica, as it is observed with ORMOSIL aerogels. As expected, the modification of the silica matrix with the Lewis base group impacted the structural properties of the adsorbent, as this sample is less porous (and hence, denser) than other ORMOSIL aerogels (without Lewis base groups) or native silica aerogels [58, 59, 78, 79]. For the Schiff base-modified aerogel-like monolith, hydrogen bonding with solvent molecules does not counter the effect of nonhydrolysable apolar groups in the network, resulting in low capillary stresses during solvent evaporation and low shrinkages in the final material. This result can be due to: the presence of the azomethine group (imine) instead of a primary or secondary amine in amine modified gels; and/or the high pore radius. Thiol modified silica xerogels also retained monolithity after evaporative drying, and their properties are similar to the aerogel counterparts [57, 80]. The specific surface area of this adsorbent is small, even when compared to other ORMOSIL aerogels, and is due to the predominant macroporous nature of the material, as indicated by the average pore size in Table 1. Previous works show that, in some situations, the specific surface area does not make a significant impact in adsorption performance [58, 80].

The FE-SEM image depicted in Figure 4(b) confirms the high porosity of the sample, revealing numerous voids with a wide distribution of pore sizes. In fact, many pores smaller than the average pore size estimated (563 nm, Table 1) are observable in this image. The pearl necklace type of microstructure expected from silica aerogels is visible. Additionally, the secondary silica particles are very small and seem to be poorly individualized, surely due to the extended aging period. This microstructure is similar to that of amine modified aerogels recently reported by the authors [58]. The evaluated structural properties allow to conclude that the prepared sample can be considered an aerogel, according to the different proposals for this definition [79, 81–83].

The FTIR spectra and the C, H, and N compositions of the aerogel-like monolith are presented in Figure 5 and Table 2, respectively. The interpretation of the experimental results obtained by elemental analysis relies on theoretical assumptions regarding the condensation of hydrolyzed precursor molecules in the sol, previously detailed by the authors [65].

Figure 5

Infrared spectrum of the adsorbent.

Table 2

C, H, and N contents of the Schiff base-modified aerogel-like monolith.

Sample/hypothesis	wt% C	wt% H	wt% N
Complete condensation	27.0	3.7	2.4
Incomplete condensation 1OH	25.1	4.5	2.2
Incomplete condensation 2OH	22.9	5.1	2.0
Experimental values	$24.4 \pm 2.0$	$3.6 \pm 0.1$	$2.5 \pm 0.1$

The FTIR spectrum of the adsorbent reveals the formation of the silica matrix and the incorporation of the Schiff base in its structure. Bands associated with siloxane bonds are visible at 577, 1099, and 1162sh cm⁻¹; bands associated with the ortho substituted benzene ring are visible at 1464 and 3100 cm⁻¹, and the bonded hydroxyl groups generate a broad band at 3431 cm⁻¹. Some bands are resultant from the overlap of different functional groups that vibrate at similar frequencies. The bands at 465 and 791 cm⁻¹ are the result of overlapping vibrations from siloxane bonds and the benzene ring, while the band at ~1632 cm⁻¹ results from the overlapping of multiple bond stretching of the benzene group, the azomethine bond, and the hydroxyl groups. These bonds limit the conclusions gained from this analysis. The remaining bands are due to the methyl and methylene groups in the MTMS and HSPTMS precursors.

Analyzing the carbon content of the sample, the elemental analysis reveals that hydrolysis is not complete, suggesting an incomplete condensation of one hydroxyl group per Si. This result can be justified by the fact that HSPTMS co-precursor may undergo incomplete hydrolysis, in comparison to the remaining co-precursors, due to its slower reactivity and to it being added just before the base. Furthermore, the large organic group in this co-precursor is likely to hinder the formation of siloxane bridges. The nitrogen content in the sample is superior to the predicted, which can be related with the presence of ammonia residues even after the washing stage, as found before in samples without nitrogen-containing precursors [58]. The experimental value obtained indicates that there are 1.8 mmol of hemi-salen groups per gram of adsorbent or $3.9 \times 10^{19}$ active sites per square meter. It was verified experimentally by EDS that the distribution of the coprecursors in the aerogel-like monolith matrix is not homogenous, as expected. Nitrogen was not detected with statistical significance in some portions of sample, and in others reached 4 wt%. The hydrogen content is inferior to the predicted, but this element is also more affected by the randomness of the network ramification. The excess of salicylaldehyde seems to be completely removed by the washing stage, as the carbon content would exceed the predictions if otherwise.

The addiction of the hemi-salen groups caused the silica surface to feature a positive charge ( $24 \pm 1$ mV), at the conditions for cation adsorption, instead of a negative charge found in nonmodified silica aerogels. Positive zeta potentials were also reported for amine-modified silicas [84–86]. In fact, it is known that inner-sphere complexation, mechanism in which the cation is adsorbed by losing its hydration shell and forming chemical bonds with the adsorbent, is insensitive to the surface charge of the adsorbent [87]. By contrast, if the adsorption of cations is due to electrostatic forces or hydrogen bonding, it is only verified on a negatively charged adsorbent surface [87].

3.3. Adsorption Isotherms and Mechanisms

The experimental data and the best isotherm fit are presented in Figure 6. The fit parameters for the studied models are reported in Table 3.

Figure 6

Adsorption isotherms in single-metal solutions.

Table 3

Fit parameters for the isotherm models and maximum uptake by Schiff base-modified aerogel-like monolith.

	Ni	Cd	Cu	Pb
$q_{e, \max}$ exp (mg g^-1)	49.9	5.1	14.4	23.4
	BET model
$q_{m}$ (mg g⁻¹)	$19 \pm 2$	$4 \pm 2$	$7.6 \pm 0.4$	$14 \pm 1$
$K_{L} \times 10^3$ (L mg⁻¹)	$7 \pm 2$	$4 \pm 3$	$87 \pm 24$	$524 \pm 268$
$K_{S} \times 10^3$ (L mg⁻¹)	$1.6 \pm 0.0$	$1.2 \pm 0.3$	$0.99 \pm 0.08$	$0.8 \pm 0.2$
AIC	18	22	5	30
BIC	−3	−19	−8	10
	Freundlich model
$1 / n_{F}$	$1.3 \pm 0.1$	$1.1 \pm 0.1$	$0.33 \pm 0.04$	$0.16 \pm 0.04$
$K_{L}$ (L mg⁻¹)	$(2 \pm 1) \times 10^{- 2}$	$(9 \pm 4) \times 10^{- 3}$	$1.7 \pm 0.4$	$8 \pm 2$
AIC	21	−6	7	230
BIC	13	−18	1	15
	Langmuir-Henry model
$q_{m}$ (mg g⁻¹)	^(a)	^(a)	$6.6 \pm 0.9$	$14 \pm 2$
$K_{F}$ (mg g⁻¹ (L mg^-1)^1/n _F)	^(a)	^(a)	$0.12 \pm 0.07$	$0.5 \pm 0.3$
$K_{H} \times 10^3$ (L g⁻¹)	^(a)	^(a)	$15 \pm 3$	$17 \pm 6$
AIC	^(a)	^(a)	11	32
BIC	^(a)	^(a)	−2	12

^(a)The model did not fit to the data.

Nickel removal, cation for which some salens were shown to be ionophores, was the highest observed out of the four cations studied. This was expected, given the high formation constants of nickel-Schiff base complexes. From the statistically point of view, the BET model represented the data the best for the adsorption of nickel, copper, and lead, as the data points seem to follow a type II isotherm (gas isotherm classification) [88] or an L3 isotherm (solid-liquid isotherm classification) [89], which is less defined in nickel adsorption. Thus, the adsorption by the Schiff base-modified ORMOSIL aerogel-like monolith is suggested to occur in multilayers of adsorbate deposited on the surface of the adsorbent. However, understanding how metal ions can form multilayers by adsorption onto an ionophore-containing surface is not straightforward. In fact, the adsorption of metal ions from aqueous media is generally controlled by adsorbent surface chemistry and surface area [90] and occurs in the form of coordination bonds [91–98]. In fact, in other materials modified with Lewis bases, the multiple neighboring functional groups participate in the complexation of one cation, and the complexing amine groups can even replace water molecules from the primary hydration shell (which is known as inner-sphere complexation) [91, 95, 96, 99, 100]. The interaction of Lewis base-modified adsorbents with the heavy metal cations may be explained by the Pearson acid-base concept. Thus, the results reported in this work follow a different trend compared to amine modified silica aerogels [58] or similar materials for which the Langmuir model fitted to the data the best in most situations [52–54]. However, by the way the data is presented in the literature, we cannot conclude if testing higher cation concentrations would produce an isotherm shaped like a BET curve. Even so, it should be highlighted that a multilayer-like adsorption for metal ions has been previously reported [101–104]. Furthermore, in a previous work, the existence of multiple types of surface groups available for adsorption generated a L4 isotherm for copper [58]. Different hypotheses for this observation can be raised and are discussed as follows.

The adsorption isotherms can be due to a combination of different factors: the macroporous nature of the adsorbent [88] and the affinity between adsorbate layers, as relevant as cation-adsorbent interactions [89], assuming that multilayers are present. The latter means that adsorption is not an exclusive result of the interaction with active surface sites. Multilayer adsorption is commonplace in the adsorption of organic pollutants due to van der Waals or π-π interactions; however, cations would repel each other. Some anions may interact with the adsorbed cation layer [105]; based on that, Jorgetto et al. [106] proposed that the BET isotherm reflects multiple adsorbate layers due to the electrostatic interactions between alternating layers of cations and counter-ions in solution. However, this situation does not seem so likely with the nitrate anions used in this work [105]. To evaluate the possibility of multilayer of adsorbed cations at the surface of the adsorbent, energy dispersive X-ray analysis (EDS) was conducted with the loaded adsorbent particles. The presence of cations at the surface was not detected (data not shown), with one exception for copper. In a previous work, SEM and EDS analyses showed that the loaded adsorbent particles were coated by metal salts, possibly due to nucleation induced by adsorbed species or to chemical precipitation at the surface of the adsorbent [80]. Such behavior was not observed in this work, and the microstructure of the loaded adsorbent simply seemed more closed (data not shown). This was expected as the loaded particles were dried by evaporating water, which increases capillary pressure in the pores by forming hydrogen bonds with the solid. Only when analyzing a large sample area could the presence of some copper (as high as $2.5 \pm 0.2$ wt%) be detected. The implication of this observation is further discussed later.

To obtain further insight on this matter, the hybrid Langmuir-Henry model (Equation (5)) was analyzed (Table 3). This considers the possibility of the structure of water molecules inside the adsorbent’s pores to be different than in the liquid water (bulk) allowing the dissolution of different amount of electrolyte, in addition to adsorption at active surface sites. If that is occurring, the hybrid Langmuir-Henry model would fit better to experimental data, which is not the case. Lead is the only cation for which the plateau corresponding to the monolayer adsorption capacity is well-defined, resembling a Langmuir curve, suggesting that the cation-adsorbent interactions are strong in this case, and AIC and BIC do not agree on the preferred model; however, we can observe that the data resembles the BET curve.

Based on the previous observations, we must conclude that in spite of the BET model represented the data the best for nickel, copper, and lead, the adsorption of these cations does not occur in multilayers. As such, the increase in adsorption capacity after a plateau (saturation of active sites) may simply reflect changes in the adsorbent’s surface/active site availability (e.g., by rearranging of adsorbed species) or the occurrence of metal nucleation induced by the salen-metal initial interaction [107–109]. EDS spectra support this conclusion, since some copper was quantified using a large area of sample.

A different but related question that shall be addressed is the interaction mechanism between metal ions and the Schiff base. At the highest equilibrium concentration, the Schiff base: Ni ratio is 2 : 1. It could be said that not all potential adsorption sites are occupied; however, as mentioned before, it was proposed that neighboring Lewis base groups are involved in the complexation of one cation. Hence, it is possible that all Schiff base groups in the aerogel are involved in the adsorption process. This hypothesis is explored again below. Nonspecific interactions, like electrostatic interactions, cannot occur with the positively charged surface of the modified silica aerogel-like monolith. The adsorption must occur due to strong interactions with the adsorbent’s surface. Furthermore, it was observed (data not shown) that loaded adsorbent particles exhibit a different color than pristine particles, which was shown to be associated with metal complexation [91]. Thus, we must conclude that the adsorption is due to complexation of cations by the Schiff base, which most likely occurs with partial loss of hydration water (chemisorption) [87].

We propose that the hemi-salen groups interact differently with the cations, due to the latter’s hydrated radius (or its size relative to the distance between the electron donor atoms in the Schiff base) and the proximity of adjacent Schiff base groups. The imine and the hydroxyl group in the Schiff base are relatively close (distance estimated at 2.4 Å, Figure 7), compared to the cation’s hydrated radius (3.9 Å in the equatorial direction of the Jahn-Teller distorted octahedron for copper, 4.1 Å for nickel, 4.6 Å for cadmium, and 5.1 Å for lead [110]). So, considering a single hemi-salen group, it is possible that the bigger cations are not complexed by both atoms, as they would retain a large radius even after partial loss of the hydration shell, and could be repelled by atoms neighboring the imine and hydroxyl groups. The Schiff base could then act as two different active sites, for cadmium and lead, resulting in a weaker interaction between the phases. This justifies the cadmium isotherm and the reduced removal of cadmium and lead. The Freundlich model fitted to the cadmium adsorption data the best, as a linear trend is observed. This shows that cadmium adsorption is due mainly to pore diffusion rather than interactions between solid and liquid phases. A different hypothesis, already mentioned, considers two adjacent hemi-salen groups complexing the metal together, in what would be a tetradentate salen ligand [46, 47, 49]. It is easily understandable that the distance between these groups will determine the cation size that acts as the coordination center. In this situation, potentially all the cations tested can be adsorbed, but because the distribution of the active sites in the adsorbent is not uniform, the distance between surface groups cannot be determined.

Figure 7

Representation of the optimized structure of the hydrolyzed HSPTMS coprecursor.

The removal observed is very reduced when compared to previous amine-modified aerogels [58] or mercapto-amine aerogels [80] but is higher than unmodified aerogels [58, 65]. The cumulative effect of the ionophore ligand, for which cation radius is important, and the impossibility of electrostatic interactions help to justify this observation. A silica aerogel not modified with Lewis bases is not a good heavy metal sorbent and only interacts with lead (the most labile) under the same conditions (uptake for copper of 2.5 mg g^-1, 15.7 mg g^-1 for lead, 1.6 mg g^-1 for cadmium, and 1.4 mg g^-1 for nickel). The here presented Schiff base ORMOSIL aerogel-like monolith is much more efficient in nickel removal than the salen modified silica gel (uptake capacity of 4 mg g^-1) reported by Kursunlu et al. [53]. When modifying mesoporous silica with salen, Enache and coauthors found that the adsorption of lead increased a little (20% for MCM and up to 5% for HMS) up to 99 mg g^-1 [52]. The adsorption of lead increased 49% with the incorporation of the salen reported in this work. The nickel uptake reported in this work is also superior to that of some amine-modified silicas (28 mg g^-1) [111] but is inferior to that of EDTA-modified silica (74 mg g^-1) [112] or poly (sodium 4-styrenesulfonate)-modified zeolitic imidazolate framework-8 (330 mg g^-1) [113]. The Schiff base silica aerogel-like monolith is a better nickel sorbent than natural minerals, zeolites, sawdust and biochar adsorbents [1, 114, 115], and other materials [116, 117].

3.4. Adsorption Kinetics and Selectivity

The HM adsorption by the prepared adsorbent was studied in binary mixtures, as a kinetic test. The total molar uptake results are presented in Table 4 and Figure 8. The kinetic curves for copper and nickel adsorption isolated and in binary mixtures are reported in Table 5 and Figure 9.

Table 4

Fitting parameters of the kinetic models for the total adsorption in binary mixtures.

	Modified pseudo-second order model					Pseudo-first order model
	$q_{0} \times 10^{2}$ (mmol g⁻¹)	$q_{e} \times 10$ (mmol g⁻¹)	$k_{2}$ (g mmol⁻¹ h⁻¹)	AIC	BIC	$q_{e} \times 10$ (mmol g⁻¹)	$k_{1}$ (h⁻¹)	AIC	BIC
Ni + Cd	$9 \pm 1$	$2.3 \pm 0.2$	$0.8 \pm 0.3$	−10	−51	$2.5 \pm 0.3$	$0.9 \pm 0.4$	−32	−40
Ni + Cu	^(a)	$3.7 \pm 0.3$	$142 \pm 68$	−59	−63	$3.6 \pm 0.1$	$23 \pm 7$	−55	−59
Ni + Pb	$7 \pm 2$	$2.8 \pm 0.3$	$0.4 \pm 0.2$	−9	−50	$2.6 \pm 0.2$	$0.3 \pm 0.1$	−38	−46
Cu + Cd	^(a)	$1.7 \pm 0.4$	$32 \pm 29$	−27	−39	$1.6 \pm 0.2$	$8 \pm 6$	−24	−37
Cu + Pb	^(a)	$1.3 \pm 0.2$	$51 \pm 32$	−47	−55	$1.3 \pm 0.1$	$4 \pm 1$	−46	−54

^(a)Negligible value.

Figure 8

Adsorption kinetics for the total uptake in binary mixtures of (a) nickel and (b) copper.

(b)

Table 5

Fitting parameters of the kinetic models for the adsorption of nickel and copper isolated and in the presence of interfering ions.

	Modified pseudo-second order model					Pseudo-first order model
	$q_{0}$ (mg g⁻¹)	$q_{e}$ (mg g⁻¹)	$k_{2}$ (g mg⁻¹ h⁻¹)	AIC	BIC	$q_{e}$ (mg g⁻¹)	$k_{1}$ (h⁻¹)	AIC	BIC
Ni	$4.7 \pm 0.8$	$17 \pm 3$	$(5 \pm 3) \times 10^{- 3}$	24	4	$16 \pm 2$	$0.3 \pm 0.1$	25	19
Ni (w/Cd)	$3.7 \pm 0.6$	$15 \pm 2$	$(8 \pm 3) \times 10^{- 3}$	18	−2	$14 \pm 1$	$0.3 \pm 0.1$	20	14
Ni (w/Cu)	^(a)	$15 \pm 2$	$(5 \pm 3) \times 10^{- 2}$	21	8	$13 \pm 1$	$0.5 \pm 0.2$	24	12
Ni (w/Pb)	^(a)	$14 \pm 1$	$(2.3 \pm 0.7) \times 10^{- 2}$	9	1	$13 \pm 1$	$0.3 \pm 0.1$	14	6
Cu	^(a)	$5.5 \pm 0.4$	$1.0 \pm 0.3$	2	−11	$5.4 \pm 0.2$	$2.8 \pm 0.6$	5	−8
Cu (w/Ni)	^(b)	^(b)	^(b)	^(b)	^(b)	^(b)	^(b)	^(b)	^(b)
Cu (w/Cd)	^(a)	$10 \pm 1$	$0.13 \pm 0.07$	17	5	$9 \pm 1$	$0.8 \pm 0.3$	21	9
Cu (w/Pb)	^(a)	$8.0 \pm 0.8$	$0.7 \pm 0.3$	5	−4	$7.5 \pm 0.4$	$4 \pm 1$	10	1

^(a)Negligible value. ^(b)System is always at equilibrium—Figure 8(b).

Figure 9

Adsorption kinetics for (a) nickel and (b) copper, isolated and in binary mixtures.

(b)

The plots from Figures 8 and 9 illustrate that a significant amount of adsorbates is adsorbed in a short period of time. From there on, the adsorption process continues slowly, which is more pronounced when nickel is present. On the majority of datasets, the modified pseudo-second order kinetic model is reduced to pseudo-second order model, as there is no relevant initial adsorption. The fit quality criteria, AIC and BIC, agree that this model is clearly better than the pseudo-first order model, which indicates that the adsorption of the different sorbates is controlled by the surface reaction, i.e., the interaction with active surface sites. When an initial uptake is significant, AIC penalizes the modified pseudo-second order model for having more parameters (Tables 4 and 5) while BIC considers this model more adequate than the pseudo-first order one. Figures 8 and 9 clearly show that the kinetic data follows the pseudo-second order trend, and so this model was chosen as the most adequate. Figure 6 elucidates that, on the concentrations tested for the kinetic tests, we are near the BET curve knee, and thus, the insight provided by the kinetic tests does not allow to disprove the existence of multilayers since the BET theory assumes that the first layer is Langmuir-like, and so it is reduced to the Langmuir equation when there is only one adsorbed layer [70, 118].

Regarding the adsorption of nickel by the Schiff base-modified aerogel-like adsorbent, the analysis of Boyd model, considered for short adsorption times, shows that intraparticle diffusion is not the rate limiting step (Table 6). This was expected as the pseudo-second order fitted to the data, indicating that chemisorption is the limiting step. It should be noted that the pseudo-first order model, which was shown to be mathematically equivalent to the Boyd model derived for long adsorption times [119], did not fit well to the data. It can also be seen that, apart from nickel adsorption kinetics in the presence of lead, the adsorption process shows two linear regions, as described by Equation (9). The first stage involves a diffusion effect of the boundary layer, followed by a faster process which might be related with the interaction with the ionophore. For the case of Ni(II), in the presence of Pb(II), only one step is detected. Taking into account the magnitude of $k_{P}$ , we may hypothesize that the boundary layer has no significant effect on the adsorption process.

Table 6

Kinetic parameters obtained for intraparticle diffusion and Boyd models for adsorption of Ni(II) in the absence and presence of other metal ions.

		Ni	Ni + Cd	Ni + Cu	Ni + Pb
Intraparticle diffusion	$k_{P, 1}$ 10³ (s^−0.5)	$1.8 \pm 0.2$	$2.3 \pm 0.2$	$1.1 \pm 0.2$	$3.7 \pm 0.1$
	$A_{0, 1}$	$0.28 \pm 0.01$	$0.22 \pm 0.01$	$0.47 \pm 0.03$	$0.15 \pm 0.02$
	$R^{2}$	0.9754	0.9860	0.9057	0.9961
	$k_{P, 2}$ 10³ (s^−0.5)	$4.03 \pm 0.07$	$3.9 \pm 0.5$	$2.5 \pm 0.1$	—
	$A_{0, 2}$	$0.07 \pm 0.01$	$0.10 \pm 0.08$	$0.26 \pm 0.02$	—
	$R^{2}$	0.9994	0.9701	0.9968	—
Boyd	$m$ 10⁵ (s⁻¹)	$1.43 \pm 0.02$	$1.7 \pm 0.1$	$1.0 \pm 0.3$	$3.5 \pm 0.1$
	$y_{0}$	$0.106 \pm 0.001$	$0.083 \pm 0.007$	$0.34 \pm 0.04$	$0.01 \pm 0.01$
	$R^{2}$	0.9991	0.9843	0.8625	0.9961

When copper and nickel are mixed, the adsorption of copper (Figure 9(b)) is almost instantaneous and remains somewhat constant, while nickel adsorption increases over time and seems that it has not reached equilibrium after 24 hours (Figure 9(a)). Figure 8 shows that the mixtures of cadmium and lead with nickel have a higher uptake than those with copper. Figure 9 clarifies this observation by revealing that nickel adsorption is not affected by the presence of these interfering cations (considering the equilibrium uptakes and their experimental error in Table 5); hence, the equilibrium found has no statistically significant change for all situations presented, and its uptake is higher than that of copper. With copper (Figure 9(b)), interfering cations have a synergistic effect on the former’s adsorption, enhancing it, and its equilibrium uptake is affected by the interferents.

The observation that nickel adsorption is unaffected by the presence of interferents is a clear indication of selectivity of the material towards this cation. Furthermore, this selectivity could not be achieved by mere nonspecific interactions between phases, meaning that the hemi-salen ligands in the aerogel-like monolith are strongly binding this cation, corroborating the idea of strong interactions for some cations. This is most likely the reason for the different shape of the nickel isotherm.

The recovery of nickel, achieved with the desorption tests with both desorption agents (HCl and HNO₃), was of 7%, meaning that the recovery of the adsorbed cation is not likely to be achieved without the degradation of the adsorbent as a consequence of strong adsorbent-adsorbate interactions. Thus, this is also an indication of the strong adsorption interaction between the cation and the adsorbent, in agreement with the chemisorption hypothesis drawn in the previous discussion.

The selectivity coefficients in the binary mixtures are reported in Table 7. The selectivity coefficients confirm that nickel is adsorbed preferentially, in the presence of the other tested cations, as expected. In the absence of nickel, a selectivity towards copper is verified as expected from salen ligands.

Table 7

Selectivity coefficients of the Schiff base-modified aerogel-like monolith.

Cation	$α_{Cu, i}$	$α_{Ni, i}$
Cd	3.7	9.4
Cu	1.0	1.8
Pb	7.5	5.4
Ni	0.6	1.0

4. Conclusion

The preparation of a selective adsorbent for nickel was achieved by incorporating a salen ionophore in a silica network, resulting in a bright yellow adsorbent. The ORMOSIL aerogel-like monolith was dried via ambient pressure drying but remained a highly porous (85%) monolith, with a reduced linear shrinkage (10%). The small specific surface area obtained (28 m² g^-1) is typical for some modified silica aerogels and is a result of the macroporous structure of the material. The isotherm studies revealed that the BET curve models the adsorption of the majority of the tested cations, although different interactions with surface sites at higher sorbate concentrations seem more likely than the formation of multilayers. Nickel was the most adsorbed cation (experimental maximum of 50 mg g^-1), an improvement towards different reported materials. Kinetic studies evidenced a very fast initial uptake, which is sometimes reflected by what can be considered as an initial boost to the adsorption process that slows down as active sites become occupied. The adsorption of binary mixtures, not common in newly reported adsorbents, revealed a high affinity for both copper and nickel by the Schiff base-modified aerogel-like monolith. However, it is clear that copper is only the preferred sorbate in the absence of nickel, as copper uptake decreases slightly (in the presence of nickel) as time increases, and nickel uptake is not affected by the presence of other species in solution. The selectivity coefficients calculated indicate that the prepared adsorbent removes nickel ~9 times more than cadmium, ~5 times more than lead, and~ 2 times more than copper, confirming the fitness of this material for the separation of nickel from solutions with other metals. Further interfering ions should be tested in the future to assess the viability of the material here presented in separating nickel from complex mixtures/mixtures containing other common ions. The desorption of nickel was not very extensive, so further tests must be conducted in different conditions for the improvement of nickel release. Because of the high stability of Schiff base-nickel complex that was formed, desorption might only be significant if ligands are used as desorption agents, and several ligands should be tested for this purpose. The economic value of nickel may trigger the interest in the new sorbent here developed, in particular due to its high selectivity, which can contribute to follow the circular economy concept. Additionally, these results pave the way for using silica-based aerogels as potential materials for acting as sensors of metal ions.

Footnotes

Data Availability

Data and material may be available upon request to the corresponding authors.

Conflicts of Interest

The authors declare that there is no conflict of interest regarding the publication of this article.

Acknowledgments

The authors acknowledge Pedro Maximiano for his cooperation with the computational calculus. J.P. Vareda acknowledges the PhD grant SFRH/BD/131280/2017 by Fundação para a Ciência e a Tecnologia, I.P. (FCT, Portugal) funded by national funds from MCTES (Ministério da Ciência, Tecnologia e Ensino Superior) and, when appropriate, cofunded by the European Commission through the European Social Fund. Consumables for the syntheses and characterizations performed at CIEPQPF and CQC research units were funded by national funds through the FCT and when appropriate cofunded by FEDER under the PT2020 Partnership Agreement under the projects POCI-01-0145-FEDER-006910 and POCI-01-0145-FEDER-007630 (FCT Refs. UIDB/EQU/00102/2020 and UIDB/QUI/00313/2020, respectively). Moreover, tests were also performed under the scope of the project “BIOSHELL” (Ref. “BLUEBIO/0003/2019–Recycling Crustaceans Shell Wastes for Developing Biodegradable Wastewater Cleaning Composites”), financed by FCT within program ERA-NET cofund on Blue Bioeconomy (BlueBio)—Unlocking the Potential of Aquatic Bioresources.

References

Vareda

J. P.

Valente

A. J. M.

Durães

Assessment of heavy metal pollution from anthropogenic activities and remediation strategies: a review

Journal of Environmental Management 2019 246

8237403

101 118

10.1016/j.jenvman.2019.05.126

2-s2.0-85066503559

31176176

Adriano

D. C.

Trace elements in terrestrial environments: biogeochemistry, bioavailability, and risks of metals 2001 2nd

Springer

Park

J. H.

Choppala

G. K.

Bolan

N. S.

Chung

J. W.

Chuasavathi

Biochar reduces the bioavailability and phytotoxicity of heavy metals

Plant and Soil 2011 348

8237403

1-2 439 451

10.1007/s11104-011-0948-y

2-s2.0-80053576012

Bolan

Kunhikrishnan

Thangarajan

Kumpiene

Park

Makino

Kirkham

M. B.

Scheckel

Remediation of heavy metal(loid)s contaminated soils - To mobilize or to immobilize?

Journal of Hazardous Materials 2014 266

8237403

141 166

10.1016/j.jhazmat.2013.12.018

2-s2.0-84891604486

Kabata-Pendias

Trace Elements in Soils and Plants 2011 4th

USA

CRC Press

10.1201/b10158

2-s2.0-84939446853

Adriano

D. C.

Wenzel

W. W.

Vangronsveld

Bolan

N. S.

Role of assisted natural remediation in environmental cleanup

Geoderma 2004 122

8237403

2-4 121 142

10.1016/j.geoderma.2004.01.003

2-s2.0-4444318891

Amundsen

P.-A.

Staldvik

F. J.

Lukin

A. A.

Kashulin

N. A.

Popova

O. A.

Reshetnikov

Y. S.

Heavy metal contamination in freshwater fish from the border region between Norway and Russia

Science of the Total Environment 1997 201

8237403

3 211 224

10.1016/S0048-9697(97)84058-2

2-s2.0-0030738953

9241871

Guerreiro

Ortiz

A. G.

de Leeuw

Viana

Horálek

Air Quality in Europe — 2016 Report 2016

Denmark

European Environment Agency

The International Council on Mining and Metals

Trends in the Mining and Metals Industry in Mining’s Contribution to Sustainable Development: the series 2012

10.

World Bank Group

Commodity Markets Outlook January 2017

Washington

11.

Cutler

C. P.

Chen

J. K.

Thyssen

J. P.

Use of metals in our society

Metal Allergy: From Dermatitis to Implant and Device Failure 2018

Cham

Springer International Publishing

3 16

10.1007/978-3-319-58503-1_1

2-s2.0-85053942241

12.

European Environment Agency

Indicator assessment: heavy metal emissions

EEA Indicators 2019

Denmark

13.

Oorts

Alloway

J. B.

Copper

Heavy Metals in Soils: Trace Metals and Metalloids in Soils and their Bioavailability 2013

Dordrecht

Springer

367 394

10.1007/978-94-007-4470-7_13

14.

Alloway

B. J.

Alloway

B. J.

Introduction

Heavy Metals in Soils: Trace Metals and Metalloids in Soils and their Bioavailability 2013

Netherlands: Dordrecht

Springer

3 9

10.1007/978-94-007-4470-7_1

15.

Clavadetscher

Hoffmann

Lilienkampf

Mackay

Yusop

R. M.

Rider

S. A.

Mullins

J. J.

Bradley

Copper catalysis in living systems and in situ drug synthesis

Angewandte Chemie International Edition 2016 55

8237403

50 15662 15666

10.1002/anie.201609837

2-s2.0-85027943668

27860120

16.

Dong

Liu

Sun

Qiu

Zhou

Yin

S.-F.

Copper catalysis for selective heterocoupling of terminal alkynes

Journal of the American Chemical Society 2016 138

8237403

38 12348 12351

10.1021/jacs.6b07984

2-s2.0-84989249058

17.

Lang

Zewge

Houpis

I. N.

Volante

R. P.

Amination of aryl halides using copper catalysis

Tetrahedron Letters 2001 42

8237403

19 3251 3254

10.1016/S0040-4039(01)00458-0

2-s2.0-0035821252

18.

Steinnes

Alloway

J. B.

Lead

Heavy Metals in Soils: Trace Metals and Metalloids in Soils and their Bioavailability 2013

Dordrecht

Springer

395 409

10.1007/978-94-007-4470-7_14

19.

European Chemicals Agency

Lead in shot, bullets and fishing weights 2019

April 2021, https://echa.europa.eu/hot-topics/lead-in-shot-bullets-and-fishing-weights

20.

Das

3 - Review of restricted substances in apparel

Product Safety and Restricted Substances in Apparel 2013

India

Woodhead Publishing

14 28

21.

Occupational Safety & Health Administration

Cadmium

April 2021, https://www.osha.gov/cadmium

22.

European Chemicals Agency

Substances restricted under REACH 2021

April 2021, https://echa.europa.eu/substances-restricted-under-reach

23.

Tasker

S. Z.

Standley

E. A.

Jamison

T. F.

Recent advances in homogeneous nickel catalysis

Nature 2014 509

8237403

7500 299 309

10.1038/nature13274

2-s2.0-84900544451

24828188

24.

World Bank Group

Commodity Markets Outlook April 2020

Washington

25.

Duda-Chodak

Blaszczyk

The impact of nickel on human health

Journal of Elementology 2008 13

8237403

4 685 696

26.

Gonnelli

Renella

Alloway

J. B.

Chromium and Nickel

Heavy Metals in Soils: Trace Metals and Metalloids in Soils and their Bioavailability 2013

Dordrecht

Springer

313 333

10.1007/978-94-007-4470-7_11

27.

Wang

Removal of heavy metal ions from wastewaters: a review

Journal of Environmental Management 2011 92

8237403

3 407 418

10.1016/j.jenvman.2010.11.011

2-s2.0-78650520448

28.

Kurniawan

T. A.

Chan

G. Y. S.

W.-H.

Babel

Physico-chemical treatment techniques for wastewater laden with heavy metals

Chemical Engineering Journal 2006 118

8237403

1-2 83 98

10.1016/j.cej.2006.01.015

2-s2.0-33646492475

29.

Da̧browski

Hubicki

Podkościelny

Robens

Selective removal of the heavy metal ions from waters and industrial wastewaters by ion-exchange method

Chemosphere 2004 56

8237403

2 91 106

10.1016/j.chemosphere.2004.03.006

2-s2.0-2142775431

30.

Heidari

Younesi

Mehraban

Heikkinen

Selective adsorption of Pb(II), Cd(II), and Ni(II) ions from aqueous solution using chitosan-MAA nanoparticles

International Journal of Biological Macromolecules 2013 61

8237403

251 263

10.1016/j.ijbiomac.2013.06.032

2-s2.0-84881240525

23817093

31.

Shaheen

S. M.

Derbalah

A. S.

Moghanm

F. S.

Removal of heavy metals from aqueous solution by zeolite in competitive sorption system

International Journal of Environmental Science and Development 2012 3

8237403

4 362 367

10.7763/IJESD.2012.V3.248

32.

Verweij

P. D.

Dugué

Driessen

W. L.

Reedijk

Rowatt

Sherrington

D. C.

Metal uptake by N,

N^{'}

-bis(2-benzimidazolylmethyl) amine immobilized on poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate)

Reactive Polymers 1991 14

8237403

3 213 227

10.1016/0923-1137(91)90038-P

2-s2.0-0026203949

33.

Dam

H. A.

Kim

Selective copper(II) sorption behavior of surface-imprinted core−shell-type polymethacrylate microspheres

Industrial & Engineering Chemistry Research 2009 48

8237403

12 5679 5685

10.1021/ie801321d

2-s2.0-67650096968

34.

Dudler

Lindoy

L. F.

Sallin

Schlaepfer

C. W.

An oxygen-nitrogen donor macrocycle immobilized on silica gel. A reagent showing high selectivity for copper(II) in the presence of cobalt (II), nickel (II), zinc (II) or cadmium (II)

Australian Journal of Chemistry 1987 40

8237403

9 1557 1563

10.1071/CH9871557

2-s2.0-84970610794

35.

Nosrati

Larsson

Lindén

J. B.

Zihao

Addai-Mensah

Nydén

Polyethyleneimine functionalized mesoporous diatomite particles for selective copper recovery from aqueous media

International Journal of Mineral Processing 2017 166

8237403

29 36

10.1016/j.minpro.2017.07.001

2-s2.0-85022047731

36.

El Hanandeh

Mahdi

Imtiaz

M. S.

Modelling of the adsorption of Pb, Cu and Ni ions from single and multi-component aqueous solutions by date seed derived biochar: comparison of six machine learning approaches

Environmental Research 2021 192, article 110338

8237403

10.1016/j.envres.2020.110338

33075354

37.

Al-Saydeh

S. A.

El-Naas

M. H.

Zaidi

S. J.

Copper removal from industrial wastewater: a comprehensive review

Journal of Industrial and Engineering Chemistry 2017 56

8237403

35 44

10.1016/j.jiec.2017.07.026

2-s2.0-85027248956

38.

Vareda

J. P.

Valente

A. J. M.

Durães

Ligands as copper and nickel ionophores: applications and implications on wastewater treatment

Advances in Colloid and Interface Science 2021 289, article 102364

8237403

10.1016/j.cis.2021.102364

33540287

39.

Hernández-Molina

Mederos

McCleverty

J. A.

Meyer

T. J.

1.19 - Acyclic and Macrocyclic Schiff Base Ligands

Comprehensive Coordination Chemistry II 2003

Oxford

Pergamon

411 446

40.

Peralta-Domínguez

Rodríguez

Ramos-Ortíz

Maldonado

J. L.

Meneses-Nava

M. A.

Barbosa-García

Santillan

Farfán

A Schiff base derivative from cinnamaldehyde for colorimetric detection of Ni²⁺ in water

Sensors and Actuators B: Chemical 2015 207

8237403

511 517

10.1016/j.snb.2014.09.100

2-s2.0-84941281767

41.

Goswami

Chakraborty

Paul

Halder

Maity

A. C.

A simple quinoxaline-based highly sensitive colorimetric and ratiometric sensor, selective for nickel and effective in very high dilution

Tetrahedron Letters 2013 54

8237403

37 5075 5077

10.1016/j.tetlet.2013.07.051

2-s2.0-84881140127

42.

Kang

J. H.

Lee

S. Y.

Ahn

H. M.

Kim

A novel colorimetric chemosensor for the sequential detection of Ni²⁺ and CN⁻ in aqueous solution

Sensors and Actuators B: Chemical 2017 242

8237403

25 34

10.1016/j.snb.2016.11.026

2-s2.0-84994740510

43.

Ganjali

M. R.

Hosseini

Motalebi

Sedaghat

Mizani

Faridbod

Norouzi

Selective recognition of Ni²⁺ ion based on fluorescence enhancement chemosensor

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2015 140

8237403

283 287

10.1016/j.saa.2014.12.042

2-s2.0-84921534449

25615675

44.

Gupta

V. K.

Singh

A. K.

Pal

M. K.

Ni(II) selective sensors based on Schiff bases membranes in poly(vinyl chloride)

Analytica Chimica Acta 2008 624

8237403

2 223 231

10.1016/j.aca.2008.06.054

2-s2.0-48949096983

18706328

45.

Gupta

V. K.

Jain

A. K.

Ishtaiwi

Lang

Maheshwari

Ni²⁺ selective sensors based on meso-tetrakis-{4-[tris-(4-allyl dimethylsilyl-phenyl)-silyl]-phenyl}porphyrin and (sal)₂trien in poly(vinyl chloride) matrix

Talanta 2007 73

8237403

5 803 811

10.1016/j.talanta.2007.04.049

2-s2.0-35348914715

46.

Antony

Marimuthu

Vishnoi

Murugavel

Ethoxysilane appended M(II) complexes and their SiO₂/MCM-41 supported forms as catalysts for efficient oxidation of secondary alcohols

Inorganica Chimica Acta 2018 469

8237403

173 182

10.1016/j.ica.2017.09.024

2-s2.0-85029507129

47.

Bhunia

Koner

Tethering of nickel(II) Schiff-base complex onto mesoporous silica: an efficient heterogeneous catalyst for epoxidation of olefins

Polyhedron 2011 30

8237403

11 1857 1864

10.1016/j.poly.2011.04.040

2-s2.0-79957960486

48.

Parida

K. M.

Singha

Sahoo

P. C.

A facile method for promoting activities of vanadium–Schiffbase complex anchored on organically modified MCM-41 in epoxidation reaction

Journal of Molecular Catalysis A: Chemical 2010 325

8237403

1-2 40 47

10.1016/j.molcata.2010.03.028

2-s2.0-77954175844

49.

Nikoorazm

Ghorbani-Choghamarani

Mahdavi

Esmaeili

S. M.

Efficient oxidative coupling of thiols and oxidation of sulfides using UHP in the presence of Ni or Cd salen complexes immobilized on MCM-41 mesoporous as novel and recoverable nanocatalysts

Microporous and Mesoporous Materials 2015 211

8237403

174 181

10.1016/j.micromeso.2015.03.011

2-s2.0-84925780735

50.

Yang

Zhang

Hao

Guan

Ding

Shang

Qiu

Kan

Heterogenization of functionalized cu(II) and VO(IV) Schiff base complexes by direct immobilization onto amino-modified SBA-15: styrene oxidation catalysts with enhanced reactivity

Applied Catalysis A: General 2010 381

8237403

1-2 274 281

10.1016/j.apcata.2010.04.018

2-s2.0-77953698839

51.

Yang

Zhang

Hao

Kan

Tethering of Cu(II), Co(II) and Fe(III) tetrahydro-salen and salen complexes onto amino-functionalized SBA-15: effects of salen ligand hydrogenation on catalytic performances for aerobic epoxidation of styrene

Chemical Engineering Journal 2011 171

8237403

3 1356 1366

10.1016/j.cej.2011.05.047

2-s2.0-79960021167

52.

Enache

D. F.

Vasile

Simonescu

C. M.

Culita

Vasile

Oprea

Pandele

A. M.

Razvan

Dumitru

Nechifor

Schiff base-functionalized mesoporous silicas (MCM-41, HMS) as Pb(ii) adsorbents

RSC Advances 2018 8

8237403

1 176 189

10.1039/C7RA12310H

2-s2.0-85040248283

53.

Kursunlu

A. N.

Guler

Dumrul

Kocyigit

Gubbuk

I. H.

Chemical modification of silica gel with synthesized new Schiff base derivatives and sorption studies of cobalt (II) and nickel (II)

Applied Surface Science 2009 255

8237403

21 8798 8803

10.1016/j.apsusc.2009.06.055

2-s2.0-67651155747

54.

Qiao

Zhang

Sun

Niu

Adsorption performance and mechanism of Schiff base functionalized polyamidoamine dendrimer/silica for aqueous Mn(II) and Co(II)

Chinese Chemical Letters 2020 31

8237403

10 2742 2746

10.1016/j.cclet.2020.04.036

55.

Mondal

Lohar

Pal

Maji

Chattopadhyay

A new chemosensor selective for Cu²⁺ ions through fluorescence quenching approach applicable to real samples

Journal of the Indian Chemical Society 2015 92

8237403

1 8

56.

Gholivand

M. B.

Niroomandi

Yari

Joshagani

Characterization of an optical copper sensor based on N,

N^{'}

-bis(salycilidene)-1,2-phenylenediamine

Analytica Chimica Acta 2005 538

8237403

1-2 225 231

10.1016/j.aca.2005.01.059

2-s2.0-17844404253

57.

Vareda

J. P.

Durães

Functionalized silica xerogels for adsorption of heavy metals from groundwater and soils

Journal of Sol-Gel Science and Technology 2017 84

8237403

3 400 408

10.1007/s10971-017-4326-y

2-s2.0-85013212415

58.

Vareda

J. P.

Valente

A. J. M.

Durães

Silica aerogels/xerogels modified with nitrogen-containing groups for heavy metal adsorption

Molecules 2020 25

8237403

12 2788

10.3390/molecules25122788

32560338

59.

Vareda

J. P.

Matias

Durães

Facile preparation of ambient pressure dried aerogel-like monoliths with reduced shrinkage based on vinyl-modified silica networks

Ceramics International 2018 44

8237403

14 17453 17458

10.1016/j.ceramint.2018.06.213

2-s2.0-85049299070

60.

Howard

A. G.

Khdary

N. H.

Spectrofluorimetric determination of surface-bound thiol groups and its application to the analysis of thiol-modified silicas

Analyst 2004 129

8237403

9 860 863

10.1039/b407566h

2-s2.0-4944236784

15343404

61.

Jung

H.-S.

Moon

D.-S.

Lee

J.-K.

Quantitative analysis and efficient surface modification of silica nanoparticles

Journal of Nanomaterials 2012 2012

8237403

593471

10.1155/2012/593471

2-s2.0-84862289211

62.

Kühne

T. D.

Iannuzzi

Del Ben

Rybkin

V. V.

Seewald

Stein

Laino

Khaliullin

R. Z.

Schütt

Schiffmann

Golze

Wilhelm

Chulkov

Bani-Hashemian

M. H.

Weber

Borštnik

Taillefumier

Jakobovits

A. S.

Lazzaro

Pabst

Müller

Schade

Guidon

Andermatt

Holmberg

Schenter

G. K.

Hehn

Bussy

Belleflamme

Tabacchi

Glöß

Lass

Bethune

Mundy

C. J.

Plessl

Watkins

VandeVondele

Krack

Hutter

CP2K: an electronic structure and molecular dynamics software package - quickstep: efficient and accurate electronic structure calculations

The Journal of Chemical Physics 2020 152

8237403

19, article 194103

10.1063/5.0007045

33687235

63.

Grimme

Bannwarth

Shushkov

A robust and accurate tight-binding quantum chemical method for structures, vibrational frequencies, and noncovalent interactions of large molecular systems parametrized for all spd-block elements (Z = 1–86)

Journal of Chemical Theory and Computation 2017 13

8237403

5 1989 2009

10.1021/acs.jctc.7b00118

2-s2.0-85019082002

28418654

64.

Grimme

Antony

Ehrlich

Krieg

A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu

The Journal of Chemical Physics 2010 132

8237403

15, article 154104

10.1063/1.3382344

2-s2.0-77951680464

20423165

65.

Lamy-Mendes

Torres

R. B.

Vareda

J. P.

Lopes

Ferreira

Valente

Girão

A. V.

Valente

A. J. M.

Durães

Amine modification of silica aerogels/xerogels for removal of relevant environmental pollutants

Molecules 2019 24

8237403

20 3701

10.3390/molecules24203701

2-s2.0-85073462619

31618901

66.

Posada

Buckley

T. R.

Model selection and model averaging in phylogenetics: advantages of Akaike information criterion and Bayesian approaches over likelihood ratio tests

Systematic Biology 2004 53

8237403

5 793 808

10.1080/10635150490522304

2-s2.0-9644301241

15545256

67.

Freundlich

H. M. F.

Over the adsorption in solution

The Journal of Physical Chemistry 1906 57

8237403

385 471

68.

Foo

K. Y.

Hameed

B. H.

Insights into the modeling of adsorption isotherm systems

Chemical Engineering Journal 2010 156

8237403

1 2 10

10.1016/j.cej.2009.09.013

2-s2.0-72049131056

69.

Brunauer

Emmett

P. H.

Teller

Adsorption of gases in multimolecular layers

Journal of the American Chemical Society 1938 60

8237403

2 309 319

10.1021/ja01269a023

2-s2.0-12444272525

70.

Ebadi

Soltan Mohammadzadeh

J. S.

Khudiev

What is the correct form of BET isotherm for modeling liquid phase adsorption?

Adsorption 2009 15

8237403

1 65 73

10.1007/s10450-009-9151-3

2-s2.0-72449188290

71.

Naylor

T. D.

Bevington

J. C.

20 - Permeation Properties A2 - Allen, Geoffrey

Comprehensive Polymer Science and Supplements 1989

Amsterdam

Pergamon

643 668

72.

Lagergreen

Zur theorie der sogenannten adsorption gelöster stoffe

Zeitschrift für Chemie und Industrie der Kolloide 1907 2

8237403

1 15 15

10.1007/BF01501332

2-s2.0-34347109632

73.

Y. S.

McKay

Sorption of dye from aqueous solution by peat

Chemical Engineering Journal 1998 70

8237403

2 115 124

10.1016/S0923-0467(98)00076-1

74.

F.-C.

Tseng

R.-L.

Juang

R.-S.

Initial behavior of intraparticle diffusion model used in the description of adsorption kinetics

Chemical Engineering Journal 2009 153

8237403

1–3 1 8

10.1016/j.cej.2009.04.042

2-s2.0-67749085881

75.

Qiu

Pan

B. C.

Zhang

Q. J.

Zhang

W. M.

Zhang

Q. X.

Critical review in adsorption kinetic models

Journal of Zhejiang University Science A 2009 10

8237403

5 716 724

10.1631/jzus.A0820524

2-s2.0-67349286796

76.

Fan

H.-T.

Sun

Jiang

Wang

Q.-J.

D.-W.

Huang

C.-C.

Wang

K.-J.

Zhang

Z.-G.

W.-X.

Adsorption of antimony(III) from aqueous solution by mercapto-functionalized silica-supported organic-inorganic hybrid sorbent: mechanism insights

Chemical Engineering Journal 2016 286

8237403

128 138

10.1016/j.cej.2015.10.048

2-s2.0-84946430789

77.

Kumar

K. V.

Porkodi

Mass transfer, kinetics and equilibrium studies for the biosorption of methylene blue using Paspalum notatum

Journal of Hazardous Materials 2007 146

8237403

1-2 214 226

10.1016/j.jhazmat.2006.12.010

2-s2.0-34250361142

17222969

78.

Vareda

J. P.

Maximiano

Cunha

L. P.

Ferreira

A. F.

Simões

P. N.

Durães

Effect of different types of surfactants on the microstructure of methyltrimethoxysilane-derived silica aerogels: a combined experimental and computational approach

Journal of Colloid and Interface Science 2018 512

8237403

64 76

10.1016/j.jcis.2017.10.035

2-s2.0-85031791624

29054008

79.

Vareda

J. P.

Lamy-Mendes

Durães

A reconsideration on the definition of the term aerogel based on current drying trends

Microporous and Mesoporous Materials 2018 258

8237403

Supplement C 211 216

10.1016/j.micromeso.2017.09.016

2-s2.0-85029716813

80.

Vareda

J. P.

Durães

Efficient adsorption of multiple heavy metals with tailored silica aerogel-like materials

Environmental Technology 2019 40

8237403

4 529 541

10.1080/09593330.2017.1397766

2-s2.0-85033675757

81.

Leventis

Sadekar

Chandrasekaran

Sotiriou-Leventis

Click synthesis of monolithic silicon carbide aerogels from polyacrylonitrile-coated 3D silica networks

Chemistry of Materials 2010 22

8237403

9 2790 2803

10.1021/cm903662a

2-s2.0-77951952512

82.

Kistler

S. S.

Coherent expanded aerogels and jellies

Nature 1931 127

8237403

3211 741

10.1038/127741a0

2-s2.0-0000903815

83.

Hüsing

Schubert

Ley

Aerogels

Ullmann’s Encyclopedia of Industrial Chemistry 2000

Wiley-VCH Verlag GmbH & Co. KGaA

10.1002/14356007.c01_c01

84.

Soto-Cantu

Cueto

Koch

Russo

P. S.

Synthesis and rapid characterization of amine-functionalized silica

Langmuir 2012 28

8237403

13 5562 5569

10.1021/la204981b

2-s2.0-84859456518

22428537

85.

Sheng

Wei

Zuo

Chen

Pan

Dong

Amine-functionalized magnetic mesoporous silica nanoparticles for DNA separation

Applied Surface Science 2016 387

8237403

1116 1124

10.1016/j.apsusc.2016.07.061

2-s2.0-84978540808

86.

Hsiao

I. L.

Fritsch-Decker

Leidner

Al-Rawi

Hug

Diabaté

Grage

S. L.

Meffert

Stoeger

Gerthsen

Ulrich

A. S.

Niemeyer

C. M.

Weiss

Biocompatibility of amine-functionalized silica nanoparticles: the role of surface coverage

Small 2019 15

8237403

10 1805400

10.1002/smll.201805400

2-s2.0-85061041387

87.

Bradl

Kim

Kramar

StÜben

Bradl

H. B.

Chapter 2 Interactions of Heavy Metals

Interaction and Remediation 2005 6

8237403

28 164

10.1016/S1573-4285(05)80021-3

2-s2.0-77956764590

88.

Thommes

Kaneko

Neimark

A. V.

Olivier

J. P.

Rodriguez-Reinoso

Rouquerol

Sing

K. S. W.

Physisorption of gases, with special reference to the evaluation of surface area and pore size distribution (IUPAC Technical Report)

Pure and Applied Chemistry 2015 87

8237403

9-10 1051 1069

10.1515/pac-2014-1117

2-s2.0-84944241280

89.

Piccin

J. S.

Cadaval

T. R. S. A.

de Pinto

L. A. A.

Dotto

G. L.

Bonilla-Petriciolet

Mendoza-Castillo

D. I.

Reynel-Ávila

H. E.

Adsorption Isotherms in Liquid Phase: Experimental, Modeling, and Interpretations

Adsorption Processes for Water Treatment and Purification 2017

Cham

Springer International Publishing

19 51

10.1007/978-3-319-58136-1_2

2-s2.0-85055016004

90.

Cao

Gao

Harris

Dairy-manure derived biochar effectively sorbs lead and atrazine

Environmental Science & Technology 2009 43

8237403

9 3285 3291

10.1021/es803092k

2-s2.0-66449119650

19534148

91.

Benhamou

Baudu

Derriche

Basly

J. P.

Aqueous heavy metals removal on amine-functionalized Si-MCM-41 and Si-MCM-48

Journal of Hazardous Materials 2009 171

8237403

1-3 1001 1008

10.1016/j.jhazmat.2009.06.106

2-s2.0-70349326004

19615819

92.

Bois

Bonhommé

Ribes

Pais

Raffin

Tessier

Functionalized silica for heavy metal ions adsorption

Colloids and Surfaces A: Physicochemical and Engineering Aspects 2003 221

8237403

1-3 221 230

10.1016/S0927-7757(03)00138-9

2-s2.0-0038690309

93.

Cheng

Huang

Khan

Liu

Liao

Y. S.

Adsorption of Cd by peanut husks and peanut husk biochar from aqueous solutions

Ecological Engineering 2016 87

8237403

Supplement C 240 245

10.1016/j.ecoleng.2015.11.045

2-s2.0-84949666800

94.

Deng

Liu

Zeng

Tan

Huang

Tang

Wang

Hua

Yan

Competitive adsorption of Pb(II), Cd(II) and Cu(II) onto chitosan-pyromellitic dianhydride modified biochar

Journal of Colloid and Interface Science 2017 506

8237403

Supplement C 355 364

10.1016/j.jcis.2017.07.069

2-s2.0-85025166696

28750237

95.

Guimarães

A. M. F.

Ciminelli

V. S. T.

Vasconcelos

W. L.

Smectite organofunctionalized with thiol groups for adsorption of heavy metal ions

Applied Clay Science 2009 42

8237403

3-4 410 414

10.1016/j.clay.2008.04.006

2-s2.0-56749176229

96.

Liang

Sun

Wang

Sun

Qin

Preparation, characterization of thiol-functionalized silica and application for sorption of Pb²⁺ and Cd²⁺

Colloids and Surfaces A: Physicochemical and Engineering Aspects 2009 349

8237403

1-3 61 68

10.1016/j.colsurfa.2009.07.052

2-s2.0-70349162829

97.

Wei

Synthesis of thiol-functionalized MCM-41 mesoporous silicas and its application in Cu(II), Pb(II), Ag(I), and Cr(III) removal

Journal of Nanoparticle Research 2010 12

8237403

6 2111 2124

10.1007/s11051-009-9770-3

2-s2.0-77955013944

98.

Wang

Pan

Cai

Guo

Xiao

Single and binary adsorption of heavy metal ions from aqueous solutions using sugarcane cellulose-based adsorbent

Bioresource Technology 2017 241

8237403

Supplement C 482 490

10.1016/j.biortech.2017.05.162

2-s2.0-85020286453

99.

Prakash

Kumar

Tripathi

B. P.

Shahi

V. K.

Sol–gel derived poly(vinyl alcohol)-3-(2-aminoethylamino) propyl trimethoxysilane: cross-linked organic–inorganic hybrid beads for the removal of Pb(II) from aqueous solution

Chemical Engineering Journal 2010 162

8237403

1 28 36

10.1016/j.cej.2010.04.048

2-s2.0-77954563362

100.

Kłonkowski

A. M.

Grobelna

Widernik

Jankowska-Frydel

Mozgawa

The coordination state of copper(II) complexes anchored and grafted onto the surface of organically modified silicates

Langmuir 1999 15

8237403

18 5814 5819

10.1021/la981256+

2-s2.0-0033171406

101.

Sćiban

Radetić

Kevresan

Klasnja

Adsorption of heavy metals from electroplating wastewater by wood sawdust

Bioresource Technology 2007 98

8237403

2 402 409

10.1016/j.biortech.2005.12.014

2-s2.0-33748462682

16469494

102.

Teow

Y. H.

Kam

L. M.

Mohammad

A. W.

Synthesis of cellulose hydrogel for copper (II) ions adsorption

Journal of Environmental Chemical Engineering 2018 6

8237403

4 4588 4597

10.1016/j.jece.2018.07.010

2-s2.0-85049879400

103.

Danesh

Ghorbani

Marjani

Separation of copper ions by nanocomposites using adsorption process

Scientific Reports 2021 11

8237403

1 1676

10.1038/s41598-020-80914-w

33462314

104.

Batool

Idrees

Hussain

Kong

Adsorption of copper (II) by using derived-farmyard and poultry manure biochars: efficiency and mechanism

Chemical Physics Letters 2017 689

8237403

190 198

10.1016/j.cplett.2017.10.016

2-s2.0-85032854414

105.

Lam

K. F.

Chen

McKay

Yeung

K. L.

Anion effect on Cu²⁺ adsorption on NH₂-MCM-41

Industrial & Engineering Chemistry Research 2008 47

8237403

23 9376 9383

10.1021/ie701748b

2-s2.0-57949107838

106.

Jorgetto

A. d. O.

da Silva

A. C. P.

Wondracek

M. H. P.

Silva

R. I. V.

Velini

E. D.

Saeki

M. J.

Pedrosa

V. A.

Castro

G. R.

Multilayer adsorption of Cu(II) and Cd(II) over Brazilian Orchid Tree (Pata- de-vaca) and its adsorptive properties

Applied Surface Science 2015 345

8237403

81 89

10.1016/j.apsusc.2015.03.142

2-s2.0-84933556409

107.

Bhadbhade

M. M.

Srinivas

Effects on molecular association, chelate conformation, and reactivity toward substitution in copper Cu(5-X-salen) complexes, salen2- = N,N'-ethylenebis(salicylidenaminato), X = H, CH3O, and Cl: synthesis, x-ray structures, and EPR investigations

Inorganic Chemistry 1993 32

8237403

24 5458 5466

10.1021/ic00076a010

2-s2.0-0000305949

108.

Mohammadikish

Bagheri

Synthesis and characterization of [Cu(salen)]2 coordination nano-assembly by a green and simple method

Zeitschrift für Kristallographie - Crystalline Materials 2017 232

8237403

6 407 414

10.1515/zkri-2016-2003

2-s2.0-85020726296

109.

Dong

Tao

Milway

Zhang

Meng

Self-assembly of copper and cobalt complexes with hierarchical size and catalytic properties for hydroxylation of phenol

Nanoscale Research Letters 2011 6

8237403

1 484

10.1186/1556-276X-6-484

2-s2.0-84862927981

21824407

110.

Persson

Hydrated metal ions in aqueous solution: how regular are their structures?

Pure and Applied Chemistry 2010 82

8237403

10 1901 1917

10.1351/PAC-CON-09-10-22

2-s2.0-77957280516

111.

Faghihian

Nourmoradi

Shokouhi

Removal of copper (II) and nickel (II) from aqueous media using silica aerogel modified with amino propyl triethoxysilane as an adsorbent: equilibrium, kinetic, and isotherms study

Desalination and Water Treatment 2013 52

8237403

1-3 305 313

10.1080/19443994.2013.785367

2-s2.0-84893084331

112.

Kumar

Barakat

M. A.

Daza

Y. A.

Woodcock

H. L.

Kuhn

J. N.

EDTA functionalized silica for removal of Cu(II), Zn(II) and Ni(II) from aqueous solution

Journal of Colloid and Interface Science 2013 408

8237403

200 205

10.1016/j.jcis.2013.07.019

2-s2.0-84885177258

23948457

113.

Zhang

Jia

Zhang

Pan

Sorption enhancement of nickel(II) from wastewater by ZIF-8 modified with poly (sodium 4-styrenesulfonate): mechanism and kinetic study

Chemical Engineering Journal 2021 414, article 128812

8237403

10.1016/j.cej.2021.128812

114.

Yang

Xue

Peng

Zhang

Highly efficient nickel (II) removal by sewage sludge biochar supported α-Fe₂O₃ and α-FeOOH: sorption characteristics and mechanisms

PLoS One 2019 14

8237403

6, article e0218114

10.1371/journal.pone.0218114

2-s2.0-85067193952

31188870

115.

Šuránek

Melichová

Kureková

Kljajević

Nenadović

Removal of nickel from aqueous solutions by natural bentonites from Slovakia

Materials 2021 14

8237403

2 282

10.3390/ma14020282

33430482

116.

Siddiqui

M. N.

Ali

Asim

Chanbasha

Quick removal of nickel metal ions in water using asphalt-based porous carbon

Journal of Molecular Liquids 2020 308, article 113078

8237403

10.1016/j.molliq.2020.113078

117.

Veneu

D. M.

Yokoyama

Cunha

O. G. C.

Schneider

C. L.

Monte

M. B. . M.

Nickel sorption using bioclastic granules as a sorbent material: equilibrium, kinetic and characterization studies

Journal of Materials Research and Technology 2019 8

8237403

1 840 852

10.1016/j.jmrt.2018.05.020

2-s2.0-85050464441

118.

Hammond

K. D.

Conner

W. C.

Gates

B. C.

Jentoft

F. C.

Chapter One - Analysis of Catalyst Surface Structure by Physical Sorption

Advances in Catalysis 2013

Academic Press

1 101

10.1016/B978-0-12-420173-6.00001-2

2-s2.0-84888421908

119.

Plazinski

Rudzinski

Kinetics of adsorption at solid/solution interfaces controlled by intraparticle diffusion: a theoretical analysis

The Journal of Physical Chemistry C 2009 113

8237403

28 12495 12501

10.1021/jp902914z

2-s2.0-68149141507

A New Schiff Base Organically Modified Silica Aerogel-Like Material for Metal Ion Adsorption with Ni Selectivity

Abstract

1. Introduction

2. Materials and Methods

2.1. Materials

2.2. Modification of APTMS Co-precursor

2.3. Synthesis of Schiff Base-Modified ORMOSIL Aerogel-Like Monolith

2.4. Characterization

2.5. Adsorption Tests

2.6. Analysis of Adsorption Data

3. Results and Discussion

3.1. Schiff Base Reaction

3.2. Modified Aerogel-Like Monolith Characterization

3.3. Adsorption Isotherms and Mechanisms

3.4. Adsorption Kinetics and Selectivity

4. Conclusion

Footnotes

Data Availability

Conflicts of Interest

Acknowledgments

References