Strategies for enhancing proton conductivity in perovskites: A review

Abstract

Proton-conductive perovskite materials are promising platforms for advanced electrochemical devices, including fuel cells, electrolyzers, and sensors, due to their mixed ionic–electronic transport properties. However, their practical application remains limited by inadequate proton conductivity and insufficient long-term stability. This review critically analyzes recent material optimization strategies to address these challenges. Defect engineering via aliovalent doping is identified as a key approach to increase oxygen vacancy concentration, thereby enhancing proton incorporation and transport. Surface modification is shown to improve interfacial properties while suppressing degradation mechanisms. Strategies for stability optimization are examined in terms of resistance to chemical, thermal, and mechanical stress. In addition, nanostructuring is demonstrated to shorten diffusion pathways and increase active surface area, facilitating proton transport. These approaches are evaluated in relation to both Grotthuss and vehicle proton conduction mechanisms. Overall, this review establishes a clear structure–property–performance relationship to guide the rational design of durable, high-performance proton-conductive perovskites for next-generation electrochemical systems.

Keywords

proton conductivity perovskite material doping strategies oxygen vacancy solid oxide fuel cells

Introduction

Recent advances in functional materials have played a critical role in addressing major challenges in energy conversion, environmental remediation, electronic devices, and photonic systems.¹ Material composition optimization, interface engineering, and structural design have been widely explored to enhance transport properties, stability, and overall performance across diverse applications. For instance, the controlled incorporation of trace elements has been shown to significantly influence electronic and catalytic behavior in complex systems.² Heterojunction engineering and surface modification strategies have been successfully applied to improve photocatalytic efficiency and charge separation in environmental and energy-related processes.³ Meanwhile, precise material structuring and advanced fabrication techniques have enabled high-performance electronic and optoelectronic devices with improved functionality and integration potential.^4,5 In photonics and solar-energy-related systems, optical and thermal management through material design has proven effective in enhancing device efficiency and operational stability.^6,7 Catalytic activity and durability have also been shown to strongly depend on material composition and deposition strategies, particularly in multi-component systems.⁸ In parallel, extensive efforts have been devoted to improving gas capture, separation, and transport processes through advanced material formulations and optimization approaches.^9,10 Moreover, surface engineering techniques such as micro-arc oxidation have emerged as versatile methods for tailoring functional properties of metal substrates,¹¹ while computational and optimization-based methods have supported the efficient design of complex engineering systems.^12,13

Material optimization strategies are fundamentally linked to the performance requirements of specific applications such as fuel cells, electrolyzers, and sensors.¹⁴ In fuel cells, optimization focuses on enhancing catalytic activity and durability through nanostructuring, alloying, and support design to improve reactions like oxygen reduction.¹⁵ For electrolyzers, materials are tailored for high efficiency and stability under harsh conditions, often using non-noble metals, heterostructures, and conductivity enhancement to accelerate hydrogen and oxygen evolution reactions.¹⁶ In sensors, optimization emphasizes sensitivity and selectivity by engineering surface functionality, porosity, and electronic properties. Overall, effective material design must directly address the key limitations of each application, ensuring a clear relationship between structure, properties, and performance.¹⁷

Material optimization strategies such as compositional tuning, defect engineering, and microstructure control directly influence the functional properties of perovskite-based materials, including proton conductivity, stability, and catalytic activity. These tailored properties determine the performance of specific electrochemical devices: in fuel cells, optimized proton conductivity enhances power output and efficiency; in electrolyzers, improved stability and ionic transport enable higher hydrogen production rates; and in sensors, precise control of defects and surface properties increases sensitivity and selectivity. Thus, systematic material optimization is essential for translating fundamental material improvements into high-performance, application-specific devices.^18–20

Doping is a widely employed strategy to improve the performance and proton conductivity of perovskite materials which significantly influence the chemistry defect of the perovskite structure, particularly by affecting the formation and distribution of vacancies and interstitial defects.^21,22 Also, chemical modification, including structural stability, nanostructuring, and functional efficiency, is considered essential for improving perovskite materials’ characteristics by changing out one or more components of the ABX₃ framework. For example, trivalent cations can be substituted at the B-site to create oxygen vacancies, which will facilitate the incorporation of protons into the lattice and increase the material’s proton conductivity.²³

In order to overcome these challenges, recent research has explored new strategies such as the creation of composite materials and the use of sophisticated characterization methods to investigate proton dynamics at the atomic level.²⁴ Several studies have explored proton conductivity in perovskite materials by focusing on the rational design and new strategies such as doping, chemical substitution, and nanostructuring that have been employed to optimize the crystal structure.^25,26 Therefore, these strategies are essential for improving the functionality of perovskite-based technologies, especially in solar cells, light-emitting diodes (LEDs), and sensors.^27,28 Thus, the main goal of this review is to explore the fundamental aspects of the optimization of proton-conductive perovskite materials through clarifying the basic processes that motivate proton conduction in perovskites; evaluating the impact of composition; studying the factors influencing their structure form, defects on proton transport characteristics; and identifying new approaches for further study to enhance proton conductivity and material stability.

Perovskite materials: a structural overview

Perovskite ceramics have emerged as one of the most interesting compounds in modern materials science with the general formula ABX₃, as defined by their characteristic crystal structure, where the arrangement is 1:1:3, in which X is an anion and A and B are cations. The ability to modify their electrical properties by compositional design leads to a rich variety of physical and chemical properties.^29,30 Their structural flexibility allows them to exist in different dimensional forms.

Perovskites exist in different crystal frameworks such as (0D, 1D, 2D, 3D) depending on their basic building blocks and chemical compositions.³¹ These characteristics of perovskites include their dimensional tunability, which significantly influences their stability, charge transport, and light absorption properties. This makes perovskites particularly desirable for emerging technologies like solar cells, LEDs, lasers, and photocatalysts. These dimensionalities range from zero-dimensional (0D) isolated clusters to one-dimensional (1D) chains, two-dimensional (2D) layered structures, and three-dimensional (3D) extended frameworks.³² That makes them suitable for a wide range of application.^32,33

The perovskite crystal structure design is depicted in Figure 1, where X atoms (usually oxygen) are represented by red spheres, B atoms (smaller metal cations, like Ti⁴⁺) are represented by blue spheres, and A atoms (larger metal cations, like Ca²⁺) are represented by green spheres. A cations are larger than B cations in perovskites (Figure 1(a)), whereas an octahedron composed of six anions envelops the smaller cation Β (Figure 1(b)). This perovskite lattice is therefore made up of apex-connected octahedra with A cations positioned between them (Figure 1(c)). Cubes make up the structural structure, with the larger A cation in the middle, B cations in the eight corners, and X anions at the halfway points of the cube’s 12 sides.³⁴

Figure 1.

Perovskite ABX lattice: (a) large A and small В cations, with X anions; (b) octahedron by X anions; (c) octahedra lattice.³⁵

Although the cations at A and B sites display the same simple cubic topology within the perovskite structure, they usually show distinct patterns of chemical ordering referred to how different types of atoms (cations) are arranged or distributed within the crystal structure and obtained cubic lattice. In general, cations occupying the B-site exhibit a stronger tendency to undergo ordering compared to those on the A-site. Nonetheless, the bonding instabilities produced by layered ordering are usually offset either by oxygen vacancies or doping strategies.³⁶ Therefore, careful selection of materials and dopants led to optimizing the perovskite lattice which leads to increase in the conductivity. Calcium titanate (CaTiO₃) perovskite is a well-known example of a perfect arrangement that arises at high temperatures.

Proton conduction

Proton-conducting perovskites are materials that enable efficient proton transport at elevated temperatures, typically between 400 and 1000 °C.³⁷ The proton conduction mechanism in these materials involves both vehicular and Grotthuss mechanisms, influenced by composition, stoichiometry, and crystal structure.³⁸ Recent study has also explored layered perovskites, such as neodymium-doped BaLaInO₄, which demonstrate improved proton conductivity below 400 °C in wet air conditions.³⁹ In addition, barium-based perovskites, particularly Y- and Yb-doped Ba(Ce,Zr)O₃, have shown promise as electrolytes for solid oxide fuel and electrolysis cells due to their superior ionic conductivity.⁴⁰ These advancements in proton-conducting ceramics contribute to the development of sustainable hydrogen energy systems, depending on various factors. These factors influencing proton conductivity are grain size, sintering aids, doping, stability, and hydrogen solubility, all of which impact the material’s conductivity and performance (Figure 2).

Figure 2.

Key factors influencing ABO₃ proton conductivity.⁴¹

Grain size is crucial because smaller grains create more grain boundaries, which depends on their quality to support or restrict proton transport since some perovskite structures naturally promote easier proton migration. Sintering aids are frequently utilized in the fabrication process to increase conductivity, decrease porosity, and improve material densification.²⁰ Oxygen vacancies are introduced by doping, which involves replacing ions at the A or B site with ion of a different valence. These vacancies are necessary for proton incorporation and mobility. Another vital aspect is stability since long-term conductivity depends on materials maintaining their mechanical and chemical integrity under conditions of operation.^42,43

Perovskite-based proton-conducting oxides, particularly with compositions based on BaZrO₃ and BaCeO₃, have received much attention during the last two decades.⁴⁴–⁴⁶ These oxides exhibit strong protonic conductivity at high temperatures, making them promising candidates for high-temperature protonic ceramic fuel cells (PCFCs). The conventional technique for enhancing proton conductivity involves doping oxides. However, acceptor doping can result in proton trapping near dopants, which leads to limited proton conductivity and a high apparent activation energy at intermediate and low temperatures.⁴⁷ Proton migration across a material’s lattice is a vital process. In brief, a variety of structural, compositional, and environmental factors influence proton transport in perovskite-based materials.^41,48

Factors affecting proton conductivity in perovskites

Proton conductivity in perovskite materials is influenced by several factors and is gaining more insight into these factors to design superior materials. The perovskite structure allows tuning through A- and B-site ion substitution. High humidity and moderate temperatures (between 400 and 700 °C) maintain the hydration required for proton transport, resulting in optimal conductivity (Figure 3). Moreover, structural symmetry and minimized grain boundary resistance improve proton pathways. These factors collectively determine the efficiency of proton conduction in perovskites.⁴⁹

Figure 3.

Optimization of proton-conductive perovskite materials.

Perovskite composition

The composition of perovskite materials significantly influences their proton conductivity, which is crucial for electrochemical applications. Proton conductivity in perovskites depends on A-site and B-site cation substitution, oxygen vacancy concentration, and lattice structure. Therefore, substituting A-site cations (e.g. La with Ba or Sr) impacts lattice distortion and prompts proton conduction pathways. As a result, larger cations (e.g. Ba²⁺) increase the lattice spacing, enabling proton mobility by reducing the activation energy for proton hopping.^50,51 While, the B-site substitutions often involve partially replacing the transition metal with another metal to enhance oxygen vacancy formation through dopants like Y³⁺ or Ga³⁺, crucial for water incorporation and proton conduction. For example, (BaZr_1−x Y_x O_3−δ) exhibits high proton conductivity due to its stable structure and abundant vacancies.^35,52 However, excessive vacancies can destabilize the structure or promote electronic conductivity.^53,54 Therefore, proton conductivity depends on optimizing lattice dynamics, oxygen vacancies, and structural stability.

Grotthuss via vehicle mechanism

Proton transport generally proceeds through two principal mechanisms: the Grotthuss mechanism and the vehicle mechanism. In the Grotthuss mechanism, protons are transferred by successive hopping between neighboring hydrolyzed ionic sites through a continuous hydrogen-bonded network.⁵⁵ In contrast, the vehicle mechanism involves the diffusion of protons from the anode to the cathode as hydrated proton species (e.g. H₃O⁺ and larger proton–water complexes). The comparative efficiency of one mechanism versus another is determined by a variety of factors, including the material’s composition, structure, hydration level, and operating conditions.⁵⁶

In particular situations, such as closely packed lattices or low hydration levels, the vehicle mechanism may be more significant impact when compared with the Grotthuss mechanism, which is more prevalent in environments with high hydration or plentiful hydrogen bonding.⁵⁷ However, Grotthuss mechanism is typically very fast and enables high conductivity, especially in proton-conducting materials, and the vehicle mechanism may be slower than proton hopping, especially in less conductive media. In perovskite materials, defect chemistry, especially oxygen vacancies, has the major impact on overall diffusion and proton transport rates.^58,59 However, some structural features may result in lower energy barriers for hydroxide ion migration between surface and deeper layers than for proton hopping.⁶⁰

Therefore, it is essential to understand these elements to create materials with the appropriate electrical characteristics for energy applications.^25,61 For example, in materials such as BaSnO₃ and SrTiO₃, BaCeO₃, BaZrO₃, the relatively open crystal structures and dynamic lattice distortions allow hydroxide ions to move more freely between surface and subsurface layers.^48,62 On the other hand, a strong hydrogen-bond network may be unfavorable for proton hopping.⁶⁰ As a result, by creating accessible migration paths, oxygen vacancies, in particular, reduce the energy barriers for hydroxide transport, resulting in faster and more effective ionic conduction as opposed to proton hopping.⁶³

Proton conduction in perovskites begins with the hydration reaction which occurs in the presence of water vapor. This process introduces protons (H⁺) into the perovskite structure, making it a proton conductor. However, the efficiency of hydration depends on temperature, oxygen vacancy concentration, and material composition. Once H^– are incorporated, they move through the perovskite lattice via the Grotthuss mechanism.⁵⁴ Then, protons (H⁺) hop between adjacent oxygen atoms via hydrogen bonds, allowing charge transfer without the physical migration of oxygen ions. This process is facilitated by the hydrogen-bond network, which enhances efficient conduction. In the vehicle mechanism, hydroxide ions (OH^–) physically migrate between oxygen vacancies (Vₒ), carrying charge, which depends on the mobility of ionic species and vacancy stability.

In specific conditions, such as densely packed lattices or systems with low hydration, the vehicle mechanism can play a more dominant role than the Grotthuss mechanism. Conversely, the Grotthuss mechanism is more prominent in highly hydrated environments or in systems with extensive hydrogen-bonding networks (Figure 4).^56,57

Figure 4.

Two H⁺ conducting mechanisms in a BaZrO₃-based perovskite oxide: (a) Grotthuss mechanism and (b) vehicle mechanism.⁶⁴

Doping effect on the Perovskite structure

Doping perovskite structures is an intentional approach to modify their physical and chemical properties that enhance the proton conductivity.⁶⁵ Proton mobility is greatly impacted by the special lattice structure of perovskites, which is characterized by their flexibility and the presence of many dopants (Figure 5). Dopants increase proton mobility by producing lattice strain or vacancy sites, which generates dynamically favorable proton hopping routes.⁶⁶ However, structural stiffness or the presence of particular materials might inhibit the process, showing the complex interaction between material composition, structural, and proton transfer efficacy.^56,67,68

Figure 5.

The proton trapping in perovskite structures.⁶⁹

Therefore, the addition of dopants has a significant impact on the perovskite lattices, specifically the formation and distribution of vacancies and substitution defects. For example, doping trivalent cations onto the B-site promotes the creation of oxygen vacancies, enhancing proton integration into the lattice structure which results in an increase in proton conductivity.³⁰

The effects of doping on a perovskite structure are depicted in Figure 3, with particular focus devoted to the interactions between protonic defects and oxygen vacancies.⁷⁰ It demonstrates how charge balancing caused by scandium (Sc) doping at the B-site results in oxygen vacancies (Vo). The incorporation of different cations modifies the structural stability, as well as the optical and electronic properties. Thus, the overall performance of the perovskite lattice improved. This modification is crucial for increasing the oxygen vacancy density, refining thermal expansion compatibility, and increasing the overall ionic and electronic conductivity (Figure 6).⁷¹

Figure 6.

The doping process occurring in the perovskite structures to achieve the enhanced performance of the perovskite material CsPbX₃.⁴⁵

A proton can be trapped near a substituted B-ion as electrostatic interaction makes hoping a way energetically unfavorable. On the other hand, the association of substituted B-ion with an oxygen vacancy has a positive charge and repeats the proton. These interactions influence the proton mobility.⁶⁹

In Table 1, ionic conductivities for different doped ceramic materials at 600 °C are compared, showing how differing dopant ions affect performance. Y³⁺ and Gd³⁺ doping in BaZrO₃ produces relatively high conductivities (~10^–³ and ~10^–2.5 S/cm, respectively), but Sc³⁺ and Ce⁴⁺ doping produces lower values (~10^–³ S/cm). Y³⁺ doping considerably increases conductivity (~10^–² S/cm) in SrCeO₃, while Ba²⁺ results in significantly poorer performance (~10^–³ S/cm). In addition, the Gd³⁺ exhibits higher conductivity (~10^–^2.5 S/cm) for CeO₂ in comparison with Y³⁺ and Ca²⁺. Sr²⁺ significantly increases conductivity (~10^–² S/cm) in LaGaO₃, but Ba²⁺ frequently produces lower values (~10^–⁴ S/cm). Overall, these results suggest that smaller trivalent dopants such as Y³⁺ and Gd³⁺ are more effective in promoting ion transport, emphasizing the critical role of dopant ionic size and charge in optimizing the conductivity of ceramic materials.

Table 1.

Doping effects on proton conductivity.

Material	Dopant element	Dopant concertation (mol%)	Ionic Radius (Å)	Conductivity (S/cm)	References
BaZrO₃	Y³⁺	20	0.90	~10⁻² at 600 °C	Arslanlar et al.,⁷² Gilardi et al.,⁷³ and Yılmaz et al.⁷⁴
	Sc³⁺	20	0.87	~10⁻³at 600 °C	Arslanlar et al.,⁷² Gilardi et al.,⁷³ and Yılmaz et al.⁷⁴
	Gd³⁺	20	0.94	~10^−2.5 at 600 °C
BaZrO₃	Ce⁴⁺	10	0.97	~10⁻³ at 600 °C	Arslanlar et al.,⁷² Gilardi et al.,⁷³ and Yılmaz et al.⁷⁴
SrCeO₃	Ba²⁺	10	1.35	~10⁻⁴ at 600 °C	Wei et al.⁷⁵ and Yadav et al.⁷⁶
SrCeO₃	Y³⁺	10	0.90	~10⁻² at 600 °C	Wei et al.⁷⁵ and Yılmaz et al.⁷⁶
	Nd³⁺	10	0.98	~10^−3.5 at 600 °C	Wei et al.⁷⁵ and Yılmaz et al.⁷⁶
	Sm³⁺	10	0.96	~10^−2.2 at 600 °C
CeO₂	Ca²⁺	5	1.00	~10⁻³ at 600 °C	Chen et al.,⁷⁷ Khakhal et al.⁷⁸ and Lucid et al.⁷⁹
CeO₂	Y³⁺	20	0.90	~10^−3.5 at 600 °C	Chen et al.,⁷⁷ Khakhal et al.⁷⁸ and Lucid et al.⁷⁹
	Gd³⁺	20	0.94	~10^−2.5 at 600 °C	Chen et al.,⁷⁷ Khakhal et al.⁷⁸ and Lucid et al.⁷⁹
LaGaO₃	Sr²⁺	10	1.18	~10⁻² at 600 °C	Chen and Fung⁸⁰ and Monti⁸¹
	Ca²⁺	10	1.00	~10^−2.5 at 600 °C
	Ba2+	10	1.35	~10⁻⁴ at 600 °C

The correlation between different doped perovskite materials depends strongly on the type and level of dopant-based conductivity (BaZrO₃, SrCeO₃, CeO₂, and LaGaO₃) at 600 °C. It shows that Y³⁺ always provides the highest conductivity in BaZrO₃ and SrCeO₃ that maximum conductivity is typically reached when the dopant’s ionic radius is close to 0.90Å–0.95Å. The conductivity drops as the ionic radius moves away from the optimum range, either getting smaller (Sc³⁺) or larger (Nd³⁺, Ba²⁺), most likely as a result of asymmetry in the lattice and defect clustering. The conductivity of LaGaO₃ doped with divalent ions (Ca²⁺, Sr²⁺, and Ba²⁺) sharply decreases as the ionic radius increases, highlighting the crucial role that dopant size plays in preserving high ionic conductivity in perovskite structures.⁸²

Generally, barium zirconate (BaZrO₃) and strontium cerate (SrCeO₃) are two frequent proton conductors found in perovskites: CeO₂-based (Ceria-based) materials have both protonic and electronic mixed conductivity: An electrolyte material that shows promise for high-temperature applications is LaGaO₃ (Lanthanum Gallate): Conductivity values listed are dependent on experimental conditions.

Table 1 provides a general overview, and the actual effect of doping can vary depending on the specific material, doping concentration, and operating conditions (e.g. temperature, humidity). Acidic doping is the most effective way to enhance proton conductivity, as it directly introduces protons or proton-donating groups into the material. While the aliovalent doping, creates defects (e.g. oxygen vacancies) that facilitate proton hopping in ceramics. Through proton consumption or conduction channel blockage, basic doping can reduce proton conductivity. However, in amphoteric doping, the material and doping concentration determine the effect since amphoteric dopants can act as either basic or acidic sites.

Also, the integration of doped perovskites with hybrid materials such as polymers or composites offers a promising strategy to synergistically enhance both ionic conductivity and the mechanical and chemical stability of the system. While doped perovskites provide fast ion-conduction pathways via oxygen vacancies and defect chemistry, the polymer matrix contributes flexibility, processability, and mechanical reinforcement. At the interface, interactions between the polymer and ceramic phases often lead to the formation of additional conduction pathways and reduced grain boundary resistance.

These hybrid structures also exhibit improved thermal and electrochemical stability, making them suitable for high-performance applications such as solid-state fuel cells and batteries. Recent studies, including those by Choi et al.⁸³ and Zhang et al.,⁸⁴ demonstrate that such composites can achieve higher conductivities and enhanced durability under operational conditions, thereby overcoming the limitations of single-phase electrolytes. These efforts collectively aim to advance doped perovskite materials for next-generation energy and electrochemical systems.^83,84

Moreover, the lattice structure of undoped perovskites, such as BaZrO₃, BaCeO₃, or LaGaO₃, remains stable, but they lack the oxygen vacancies and other defects required for significant proton conduction. Yet, when exposed to high temperatures and humid conditions, a few protons can move into the lattice by reacting with pre-existing oxygen vacancies or lattice flaws to produce hydroxyl groups. An associated proton transport is made possible to some extent by this process. However, undoped perovskites usually have considerably lower proton conductivity than their doped counterparts (Table 2). Doping is necessary to achieve practical levels of proton conductivity in applications like as fuel cells and hydrogen sensors because it introduces oxygen vacancies, which greatly improve proton uptake and mobility. This is achieved by doping with lower-valence cations, such as Y³⁺ instead of Zr⁴⁺.

Table 2.

Effects of doping on proton conductivity.

Doping charge	Effect on proton conductivity	Mechanism	Example materials	References
Acidic doping	Increases proton conductivity	Introduces protons (H⁺) or acidic groups (e.g. -SO₃H) that act as proton donors.	Nafion (sulfonated polymers), H₃PO₄-doped ceramics	Filatov et al.⁸⁵ and Tarasova et al.⁸⁶
Basic doping	May decrease proton conductivity	Basic dopants can consume protons (H⁺) or block proton pathways, reducing mobility.	BaZrO₃ doped with basic oxides (e.g., Y₂O₃)	Akbar et al.,⁸⁷, Kmentová et al.⁸⁸ and Shi and Morinaga⁸⁹
Aliovalent doping	Enhances proton conductivity	Creates oxygen vacancies or defects that facilitate proton hopping (Grotthuss mechanism).	Y-doped BaZrO₃, SrCeO₃ doped with rare earths	Di et al.⁹⁰
Isovalent doping	Minimal effect on proton conductivity	Does not significantly alter the charge carrier concentration or defect chemistry.	ZrO₂ doped with isovalent cations (e.g. Ti⁴⁺)	Akbr et al.⁸⁷ and Wang et al.⁹¹
Amphoteric doping	Variable effect (depends on dopant and host material)	Act as both proton donor and acceptor, depending on the environment and material structure.	Al₂O₃ or Ga₂O₃ in some proton conductors	Trejgis et al.⁹² and Tshikovhi et al.⁹³
Neutral doping	Little to no effect on proton conductivity	Does not introduce charge carriers or defects that influence proton transport.	Inert fillers or neutral polymers	Meng et al.⁹⁴ and Putilov and Tsidilkovski⁹⁵

Table 3.

Perovskite-based proton conductivity (doped and free of doped).

Materials	Dopant	Method	Power density/temp.	References
La_0.5Sr_0.5Mn_0.9Ni_0.1O_3-δ (LSMNi)	Ni	Sol–gel	1100 mWcm⁻² at 700 °C	Yao et al.⁹⁶
Sr_1.75K_0.25Fe_1.5Mo_0.5O_6-δ (SKFM)BaZr_0.4Ce_0.4Y_0.2O_3-δ (BZCY4)	Mixed: BZCY4/SKFM	Sol–gel	1000.8 mWcm⁻² at 700 °C	Zhang et al.⁴⁶
Ba_0.9Co_0.7Fe_0.2Nb_0.1O_3-δ (BCFN)BaCe_0.7Zr_0.1Y_0.1Yb_0.1O_3-δ (BCZYYb)	Mixed: BCFN-BCZYYb	Solid-state, sol–gel	859 mWcm⁻² at 700 °C	Chen et al.⁹⁷
BaCo_0.4Fe_0.4Nb_0.1Sc_0.1O_3-δ (BCFNS)	Nb⁵⁺ and Sc³⁺	Solid-state	840 mWcm⁻² at 650 °C	Lu et al.⁴⁴
Ba_0.95La_0.05Fe_0.8Ni_0.2O_3−δ	Ni	Sol–gel	631mWcm^–2 at 700 °C	Jing et al.⁹⁸
PrBa_0.9K_0.1Fe_1.9Zn_0.1O_5+δ (PBKFZ) Pr_0.8Nd_0.2BaFe_1.9Zn_0.1O_5+δ (PNBFZ)	Nd, K	Nitrate-gel combustion	650 mWcm⁻² at 700 °C	Teketel et al.⁹⁹
BaCo_0.4Fe_0.4Zr_0.1Y_0.1O_2.9-δF_0.1 (BCFZYF)	F-	Sol–gel	921 mWcm⁻² at 650 °C	Ren et al.¹⁰⁰
Ba_0.95La_0.05Fe_0.8Zn_0.2O_3−δ (BLFZ) BaZr_0.1Ce_0.7Y_0.1Yb_0.1O_3−δ (BZCYYb)	BLFZ-BZCYYb	Sol–gel	329 mWcm⁻² at 750 °C	Wang et al.¹⁰¹
Nd(Ba_0.75Ca_0.25) Co_1.5Fe_0.4Ni_0.1O_5+δ (NBCCFN)BaZr_0.1Ce_0.7Y_0.1Yb_0.1O_3-δ (BZCYYb)	Ca BZCYYb and NBCCFN-GDC)	Sol–gel	882.2 mWcm⁻² at 750 °C	Xie et al.¹⁰²
BaCe_0.9–xMo_xY_0.1O_3–δ	Mo	Solid-state	418.7 mWcm⁻² at 600 °C	Hanif et al.¹⁰³
Pr_0.7Ba_0.3Co_0.8-xFe_0.2Ni_xO_3-δ	Ni	Nitric-citric combustion, solid-state	1.600 mWcm⁻² at 700 °C	Zhu et al.⁶²
Sr₂Fe_1.4Zn_0.1Mo_0.5O_6-δ (SFZM)	Zn	Sol-gel, solid-phase	630 mWcm⁻² at 600 °C	Cheng et al.¹⁰⁴
(La_0.6Sr_0.4)_0.95Fe_0.8Ni_0.1Mo_0.1O_3-δ	Mo	Combustion	204 mWcm⁻² in H₂ 172 mWcm⁻² in C₂H₆ at 750 °C	Fan et al.¹⁰⁵
La_0.5Sr_0.5Fe_0.9Mo_0.1O_3-δ (LSFMo) BaZr_0.1Ce_0.7Y_0.2O_3-δ (BZCY)	Mo	Combustion	582 mWcm⁻² (1)1174 mWcm⁻² (2)at 700 °C	Xu et al.³⁵
BaHf_0.8Ln_0.2O_3-δ (Ln = Y, Y, Dy, Gd)	Y	Solid-state	10.21 mWcm⁻² at 700 °C	Yang et al.⁵²
Ba(Co_0.4Fe_0.4Zr_0.1Y_0.1)_0.95Mg_0.05O_3-δ	Mg	EDTA-CA complexing	850 mWcm⁻² at 600 °C	Liang et al.¹⁰⁶
PrBa_0.9Ca_0.1Co_2-xZn_xO_5+δ (PBCCZx)	Zn	Sol–gel	876 mWcm⁻² at 750^oC	Wang et al.⁴²
La_0.6Sr_0.4Fe_1-xNb_xO_3-δ	Nb	Solid-state	503 mWcm⁻² at 700 °C	Yu et al.¹⁰⁷
Nd(Ba_0.4Sr_0.4Ca_0.2)Co_1.6 Fe_0.4O_5+δ	Ca	Sol–gel	926 mWcm⁻² at 750 °C	Chen et al.⁵⁶
BaZr_0.1Ce_0.7Y_0.2O_3-δ (BZCY7)NiO-BZCY7	Ni	Pechini	520 mWcm⁻² at 700 °C	Ding and Xue⁶⁷
LnBa_0.5Sr_0.5Co_1.5Fe_0.5O_5+δ (LnBSCF, Ln=Pr, Nd, and Gd)		Pechini	670 mWcm⁻² at 500 °C	Choi⁵⁰
La(Mg_2/3Nb_1/3)O₃ (LMN)		Solid-state	742 mWcm⁻² at 550 °C	Gao et al.¹⁰⁸
PrBa_0.5Sr_0.5Co_1.5Fe_0.5O_5.84-δF_0.16 (16F-PBSCF)		Traditional citric acid–EDTA process	510 mWcm⁻² at 600 °C	Xu et al.⁵¹
(PrBa)_0.95(Fe_0.9Mo_0.)₂O_5+δ (PBFM)		Pechini	532 mWcm⁻² at 700 °C	Li et al.¹⁰⁹
BaCe_0.5Fe_0.3Bi_0.2O_3-δ (BCFB)		Citric acid–nitrate gel combustion	736 mWcm⁻² at 700 °C	Shan et al.¹¹⁰
NdBaFe_1.9Nb_0.1O_5+δ (NBFNb10)		Solid-state	392 mWcm⁻² at 700 °C	Mao et al.¹¹¹
La_0.6Sr_0.4Fe_0.9Cr_0.1O_3-α (LSFC10),		Citric acid–nitrate gel combustion	412 mWcm⁻² at 700 °C	Ding et al.¹¹²
GdBaFeNiO_5+δ (GBFN) cobalt-free		Citric acid–nitrate gel combustion	456 mWcm⁻² at 700 °C	Yang et al.¹¹³
BaCo_0.4Fe_0.4Zr_0.1Y_0.1O_3-δ (BCFZY)		(EDTA) citric acid monohydrate (CA) complexing method	677 mWcm⁻² at 550 °C	Sun et al.¹¹⁴
PrBa_0.5Sr_0.5Co_1.5Fe_0.5O_5+δ (PBSCF)		Inkjet printing	728 mWcm⁻² at 600 °C	Chang et al.⁷¹
SrSc_0.175Nb_0.025Co_0.8O_3-δ (SSNC)		Sol–gel	498 mWcm⁻² at 700 °C	Zhu et al.¹¹⁵
BaCe_0.4Fe_0.4Co_0.2O_3-δ (BCFC)		Pechini	335 mWcm⁻² at 700^oC	Zhoa et al.¹¹⁶
GdBa_0.5Sr_0.5Co₂O_{5+ δ} (GBSC)		Pechini	430 mWcm⁻² at 700^oC	Ding and Xue¹¹⁷
SmBa_0.5Sr_0.5Co₂O_{5+ σ} (SBSC)		Pechini	533 mWcm⁻² at 700^oC	Ding et al.¹¹⁸
Ba_0.95La_0.05FeO_3-δ (BLF)		Pechini, sol–gel	325 mWcm⁻² at 700 °C	Yan et al.¹¹⁹
SmBaCuCoO_5+δ (SBCC) SmBaCuFeO_5+δ (SBCF)		Auto ignition process	449 mW cm² 333 mW cm² at 700 °C	Nian et al.¹²⁰

Table 3 summarizes various doped materials, preparation methods, and their power densities at operating temperatures for SOFC applications. Materials like LSMNi, SKFM/BZCY₄, and BCFN/BCZYYb exhibit high performance, with power densities up to 1.61 W/cm² at 700 °C. Preparation techniques include sol–gel, solid-state, and combustion, showcasing diverse fabrication approaches (Table 3).

Dopants such as Ni, Mo, Ca, and Zn were enhanced conductivity and efficiency. Also, mixed and composite materials, like NBCCFN/BZCYYb and LSFMo/BZCY, show a power density above 800 mW/cm². The performance ranges were between [10.21 and 1610 mW/cm²], with optimal temperatures among (600–750) °C. Materials such as LnBa_0.5Sr_0.5Co_1.5Fe_0.5O₅^+δ (LnBSCF, Ln = Pr, Nd, Gd), prepared via the Pechini method, achieve 0.67 W/cm² at 500 °C, showing high performance at low temperatures. At 550 °C, La(Mg_2/3Nb_1/3)O₃ (LMN) has one of the highest peak power densities of any material synthesized using solid-state techniques, with a peak power density of 742 mW/cm².

In addition, composite cathodes like 16F-PBSCF and PBFM, produced using citric acid–EDTA processes and Pechini methods, achieved moderate power densities of 0.51 W/cm² at 600 °C and 532 mW/cm² at 700 °C. In comparison, advanced cathode–electrolyte combinations, such as BCFB cathode with NiO-BZCY7 anode, achieved 736 mW/cm² at 700 °C using gel combustion methods. Similarly, BZCYYb/BCFZY demonstrated 677 mW/cm² at 550 °C with EDTA complex.

The inkjet-printed PBSCF nanopowder achieved 728 mW/cm² at 600 °C, showing improvements. In comparison, sol–gel or gel combustion techniques and other compositions, such as GBFN and SSNC cathodes balanced with BZCY electrolytes, obtained 456 and 498 mW/cm², respectively. Furthermore, with power densities of 335 and 325 mW/cm² at 700 °C, complex anode systems such as BCZYYb + NiO + starch or BLF + BZCY7 composites also demonstrated remarkable performance.

Moreover, cobalt-free cathodes like GBFN (GdBaFeNiO_5+δ) and doped compositions like SmBaCuCoO_5+δ (SBCC) and SmBaCuFeO_5+δ (SBCF) combined with new electrolytes such as BaCe_0.8Sm_0.2O_5+δ (BCS) are explored for sustainability and efficiency, achieving 449 and 333 mW/cm² at 700 °C, respectively. The balance between fabrication methods, material choices, and operating conditions for optimizing SOFC performance across varied temperature ranges is illustrated in Table 3. In contrast, high-performance materials like LMN, PBSCF, and LnBSCF have demonstrated great potential; at 550 °C, LMN achieved a peak power density of 742 mW/cm². PBSCF, GBFN, and BLF cathodes are frequently employed in conjunction with NiO anodes and electrolytes based on BZCY. Inkjet printing and auto-ignition synthesis are two examples of innovative methods of production that are constantly advancing material design and increasing overall efficiency.

As stated previously, doping plays a critical role in enhancing the proton conductivity of perovskite-based materials by influencing both the doping level and the concentration of oxygen vacancies. A-site doping (e.g. Sr²⁺, K⁺, Ca²⁺) introduces charge imbalance, generating oxygen vacancies that facilitate proton transport, while B-site doping (e.g. Ni²⁺, Mo⁶⁺, Nb⁵⁺, Zn²⁺, Sc³⁺) directly modifies the electronic structure and defect chemistry, enhancing conductivity. Higher-valent dopants such as Mo⁶⁺ and Nb⁵⁺ increase vacancy concentration, improving performance up to an optimal level beyond which phase stability may suffer. Notably, mixed systems combining proton- and electron-conducting phases (e.g. BCFN–BCZYYb, SKFM–BZCY4) exhibit high power densities due to synergistic effects at the interfaces and better vacancy distribution. Ni-doped and Mo-doped perovskites, in particular, show excellent performance, reaching power densities of up to 1600 mW/cm² at 700 °C. Overall, the most efficient systems maintain a delicate balance between doping concentration, vacancy formation, and structural stability, optimizing proton conduction and electrochemical performance at intermediate operating temperatures.

Future perspectives

Proton-conducting perovskites face challenges such as poor chemical stability and moisture-rich environments, high grain boundary resistance, and trade-offs between doping levels and conductivity. One of the main limitations of proton-conducting perovskites is their chemical instability, which leads to degradation of the material and performance loss in devices like fuel cells. This process causes the breakdown of the perovskite framework and precipitation of secondary phases such as CeO₂ or ZrO₂, resulting in loss of mechanical integrity and significant reduction in proton conductivity. The degradation is largely irreversible and severely limits the material’s stability and performance in applications exposed to CO₂ and humid atmospheres.

Performance is further limited by thermal expansion gaps, reduced hydration at high temperatures, and challenges in creating dense microstructures as a result of high sintering temperatures. However, the significant impact of microstructural features, particularly grain size, porosity, grain boundary resistance, and phase connectivity, on the proton conductivity of doped perovskite materials. Fine grain structures, typically achieved through sol–gel, Pechini, or combustion methods, enhance proton transport by increasing the number of grain boundaries, which can act as fast diffusion paths for protons if well-sintered and defect-engineered.¹²¹

For example, high-performance materials like PrBaCoNi (1600 mW/cm²) and LSFMo/BZCY (1174 mW/cm²) benefit from such synthesis techniques that promote uniform, nanostructured grains with high surface area and improved proton accessibility. On the other hand, solid-state synthesized materials often exhibit larger grain sizes and lower porosity, which may limit proton conduction due to higher grain boundary resistance and reduced surface reactivity, as seen in some Nb and Mo-doped systems with moderate performance (~400–600 mW/cm²). In addition, composites or mixed phases (e.g. BCFN–BCZYYb, SKFM–BZCY4) often display interconnected grain structures that facilitate continuous ion pathways and reduce internal resistance, contributing to their superior electrochemical output. Therefore, careful control of the microstructure minimizing porosity, optimizing grain size, and ensuring good grain boundary contact is as critical as doping in achieving high-performance proton-conducting perovskite electrolytes and electrodes (Figure 7).

Figure 7.

Doping, mechanisms, and performance of perovskite-based materials.

This review addresses these issues requires balanced doping strategies, improved stability, and cost-effective synthesis techniques to overcome these problems due to their multipurpose applications in energy conversion and storage, environmental sensing, and their potential to contribute to more sustainable and efficient technological solutions. Moreover, it is important to consider external factors that might affect proton mobility inside a material such as humidity and temperature. Thus, understanding the impact of these factors on proton migration and conductivity is crucial for the development of efficient perovskite-based devices. As a result, the future study purpose must focus on the synthesis of new perovskite-based fabrication with ratio of some elements through changing the concentrations and using different doping techniques including solid-state reaction, sol–gel, hydrothermal/solvothermal, and combustion methods to improve the conduction properties.

Conclusion

Proton-conducting perovskites (ABO₃) derive their performance from a delicate coupling between cation chemistry, defect formation, and crystal structure. Across reported systems, B-site substitution with trivalent rare-earth dopants (e.g. Y, Yb, Sc, and Gd) consistently enhances proton transport by increasing oxygen vacancy concentration and enabling Grotthuss-type migration. However, a persistent materials trade-off emerges: BaCeO₃-based compositions favor high proton conductivity, whereas BaZrO₃-based systems offer superior chemical robustness, limiting simultaneous optimization of transport and stability. Progress in synthesis and processing, including sol–gel, solid-state, and combustion routes, demonstrates that microstructural control and dopant distribution are as critical as composition in governing defect chemistry, activation energy, and long-term operational stability. These findings collectively indicate that proton conduction is not an intrinsic material constant but a tunable emergent property governed by coupled structural and defect-level design.

Future advances will depend on moving beyond empirical doping toward predictive compositional engineering, expanded rare-earth and multi-dopant chemistries (e.g. Pr-, Nd-, and Gd-based systems), and nanoscale architectural control. Resolving the conductivity–stability trade-off will require integrated strategies that simultaneously optimize defect thermodynamics and transport pathways. Ultimately, establishing quantitative structure–property relationships will be essential for the rational design of durable, high-performance proton-conducting perovskites for fuel cells, electrolyzers, and hydrogen separation technologies.

Footnotes

ORCID iD

Dham O. Alshamary

Ethical consideration

Not applicable.

Consent to participate

The authors declare that all authors were involved in the research and contributed to the manuscript.

Consent for publication

The authors confirm that we give our full consent for publishing this manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The author(s) received financial support for the research, from the Industrial Grant No. PV071-2024 and the University Matching Grant No. MG035-2024.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

The data that support this study are accompanied as a supplementary material.

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