Transition Metal and N Doping on AlP Monolayers for Bifunctional Oxygen Electrocatalysts: Density Functional Theory Study Assisted by Machine Learning Description

Orbital hybridizations in single-atom catalysts for electrocatalysis

Single-atom catalysts (SACs) are rapidly standing at the forefront of catalytic development due to their unique structures with significantly different catalytic activity, selectivity, and stability from conventional nanocatalysts. The electronic properties and catalytic performances of SACs hinge on the results of orbital hybridization of isolated central atoms with ligand atoms as well as of central atoms with bonding atoms provided by intermediates. Therefore, we conduct multifaceted explorations around orbital hybridizations in single-atom catalysis to elucidate the structure-activity relationships. Firstly, we introduce the basic theoretical knowledge related to orbital hybridizations, and summarize the main descriptors of orbital hybridizations, focusing on the discussion of the types of orbital hybridizations in single-atom catalysis. Then, we briefly sum up the application of orbital hybridizations in single-atom electrocatalysis and put forward important strategies for regulating orbital hybridizations in SACs to improve the catalytic performances. Finally, we present a personal perspective on the future challenges and opportunities of orbital hybridizations in single-atom catalysis.

Intelligent design and synthesis of energy catalytic materials

Efficient energy conversion and storage are crucial for the sustainable development and growth of renewable energy sources. However, the limited varieties of traditional energy catalytic materials cannot match the fast-expansion requirement of raising various clean energy for industrial applications. Thus, accelerating the design and synthesis of high-performance catalysts is necessary for the application of energy equipment. Recently, with artificial intelligence (AI) technology being advanced by leaps and bounds, it is feasible to efficiently and precisely screen materials and optimize synthesis conditions in a huge unknown space. Here, we introduce and review AI techniques used in the development of catalytic materials in detail. We describe the workflow for designing and synthesizing new materials using machine learning (ML) and robotics. We summarize the sources of data collection, the intelligent algorithms commonly used to build ML models, and the laboratory modules for the intelligent synthesis of materials. We provide the illustrations of predicting the properties of catalytic materials with ML assistance in different material types. In addition, we present the potential strategies for finding material synthesis pathways, and advances in robotics to accelerate high-performance catalytic materials synthesis in the review. Finally, the summary, challenges, and potential directions in the development of AI-assisted catalytic materials are presented and discussed.

Computational Engineering of Non-van der Waals 2D Magnetene for Enhanced Oxygen Evolution and Reduction Reactions

Non-van der Waals two-dimensional materials containing exposed transition metal atoms are promising catalysts for green energy storage and conversion. For instance, hematene and ilmenene have been successfully applied as catalysts. Building on these reports, this work is the first investigation of recently synthesized magnetene towards the Oxygen Evolution Reaction (OER) and Oxygen Reduction Reaction (ORR). Using Density Functional Theory (DFT) calculations, we unveil the mechanism, performance and ideal conditions for OER and ORR on magnetene. With overpotentials of ηOER=0.50 V and ηORR=0.41 V, the material is not only a bifunctional catalyst, but also superior to state-of-the-art systems such as Pt and IrO2. Additionally, its catalytic properties can be further enhanced through engineering strategies such as point defects and in-plane compression. It reaches ηORR=0.28 V at a compressive strain of only 2 %, while the presence of Ni boosts it to ηOER=0.39 V and ηORR=0.31 V, comparable to many reported single-atom catalysts. Overall, this work demonstrates that magnetene is a promising bifunctional catalyst for applications such as regenerative fuel cells and metal-air batteries.

Edge-doped substituents as an emerging atomic-level strategy for enhancing M-N4-C single-atom catalysts in electrocatalysis of the ORR, OER, and HER

M-N4-C single-atom catalysts (MN4) have gained attention for their efficient use at the atomic level and adjustable properties in electrocatalytic reactions like the ORR, OER, and HER. Yet, understanding MN4's activity origin and enhancing its performance remains challenging. Edge-doped substituents profoundly affect MN4's activity, explored in this study by investigating their interaction with MN4 metal centers in ORR/OER/HER catalysis (Sub@MN4, Sub = B, N, O, S, CH3, NO2, NH2, OCH3, SO4; M = Fe, Co, Ni, Cu). The results show overpotential variations (0 V to 1.82 V) based on Sub and metal centers. S and SO4 groups optimize FeN4 for peak ORR activity (overpotential at 0.48 V) and reduce OER overpotentials for NiN4 (0.48 V and 0.44 V). N significantly reduces FeN4's HER overpotential (0.09 V). Correlation analysis highlights the metal center's key role, with ΔG*H and ΔG*OOH showing mutual predictability (R2 = 0.92). Eg proves a reliable predictor for Sub@CoN4 (ΔG*OOH/ΔG*H, R2 = 0.96 and 0.72). Machine learning with the KNN model aids catalyst performance prediction (R2 = 0.955 and 0.943 for ΔG*OOH/ΔG*H), emphasizing M-O/M-H and the d band center as crucial factors. This study elucidates edge-doped substituents' pivotal role in MN4 activity modulation, offering insights for electrocatalyst design and optimization.

Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry for the creation and optimization of electrocatalysts, which enhance key electrochemical reactions like the hydrogen evolution reaction (HER), the oxygen evolution reaction (OER), the hydrogen oxidation reaction (HOR), and the oxygen reduction reaction (ORR). This comprehensive review demonstrates how cutting-edge ML techniques are being leveraged in electrocatalyst design to overcome the time-consuming limitations of traditional approaches. ML methods, using experimental data from high-throughput experiments and computational data from simulations such as density functional theory (DFT), readily identify complex correlations between electrocatalyst performance and key material descriptors. Leveraging its unparalleled speed and accuracy, ML has facilitated the discovery of novel candidates and the improvement of known products through its pattern recognition capabilities. This review aims to provide a tailored breakdown of ML applications in a format that is readily accessible to materials scientists. Hence, we comprehensively organize ML-driven research by commonly studied material types for different electrochemical reactions to illustrate how ML adeptly navigates the complex landscape of descriptors for these scenarios. We further highlight ML's critical role in the future discovery and development of electrocatalysts for hydrogen energy transformation. Potential challenges and gaps to fill within this focused domain are also discussed. As a practical guide, we hope this work will bridge the gap between communities and encourage novel paradigms in electrocatalysis research, aiming for more effective and sustainable energy solutions.

Single-Atom Doped Fullerene (MN4-C54) as Bifunctional Catalysts for the Oxygen Reduction and Oxygen Evolution Reactions

Development of high-performance oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) catalysts is crucial to realizing the electrolytic water cycle. C60 is an ideal substrate material for single atom catalysts (SACs) due to its unique electron-withdrawing properties and spherical structure. In this work, we screened for a novel single-atom catalyst based on C60, which anchored transition metal atoms in the C60 molecule by coordination with N atoms. Through first-principles calculations, we evaluated the stability and activity of MN4-C54 (M = Fe, Co, Ni, Cu, Rh, Ru, Pd, Ag, Pt, Ir, Au). The results indicate that CuN4-C54, which is based only on earth-abundant elements, exhibited low overpotentials of 0.46 and 0.47 V for the OER and ORR, respectively, and was considered a promising bifunctional catalyst, showing better performance than the noble-metal ones. In addition, according to the linear relationship of intermediates, we established volcano plots to describe the activity trends of the OER and ORR on MN4-C54. Finally, d-band center and crystal orbital Hamiltonian populations methods were used to explain the catalytic origin. Suitable d-band centers lead to moderate adsorption strength, further leading to good catalytic performances.

Carbothermal Reduction-Assisted Synthesis of a Carbon-Supported Highly Dispersed PtSn Nanoalloy for the Oxygen Reduction Reaction

Exploring high-performance and low-platinum-based electrocatalysts to accelerate the oxygen reduction reaction (ORR) at the air cathode of zinc-air batteries remains crucial. Herein, by combining electroless deposition and carbothermal reduction, a nitrogen-doped carbon-supported highly dispersed PtSn alloy nanocatalyst (PtSn/NC) was prepared for a high-efficiency ORR process. Electrochemical measurements show that PtSn/NC exhibits excellent electrocatalytic ORR activity with a half-wave potential of 0.850 V versus reversible hydrogen electrode (RHE), which is higher than that of commercial Pt/C (0.815 V). The PtSn/NC-based (20 μgPt cm-2) rechargeable Zn-air battery exhibited astonishing performance with a maximum power density of up to 150.1 mW cm-2, as well as excellent rate performance and charge/discharge stability. Physical characterization reveals that carbothermal reduction could compel the transformation of Sn oxide into metallic Sn, which then alloys with the deposited Pt atoms to form the PtSn nanoalloy, in which electrons are transferred from Sn atoms to neighboring Pt atoms, thereby improving the ability of Pt-based active sites to catalyze the ORR process in PtSn/NC by optimizing the unoccupied d-band of Pt atoms. This work provides a reliable and innovative route for the rational design of highly dispersed Pt-based alloy ORR electrocatalysts.

Recent Advances in Iridium-based Electrocatalysts for Acidic Electrolyte Oxidation

Ongoing research to develop advanced electrocatalysts for the oxygen evolution reaction (OER) is needed to address demand for efficient energy conversion and carbon-free energy sources. In the OER process, acidic electrolytes have higher proton concentration and faster response than alkaline ones, but their harsh strongly acidic environment requires catalysts with greater corrosion and oxidation resistance. At present, iridium oxide (IrO2) with its strong stability and excellent catalytic performance is the catalyst of choice for the anode side of commercial PEM electrolysis cells. However, the scarcity and high cost of iridium (Ir) and the unsatisfactory activity of IrO2 hinder industrial scale application and the sustainable development of acidic OER catalytic technology. This highlights the importance of further research on acidic Ir-based OER catalysts. In this review, recent advances in Ir-based acidic OER electrocatalysts are summarized, including fundamental understanding of the acidic OER mechanism, recent insights into the stability of acidic OER catalysts, highly efficient Ir-based electrocatalysts, and common strategies for optimizing Ir-based catalysts. The future challenges and prospects of developing highly effective Ir-based catalysts are also discussed.

Carbon-Based Composites for Oxygen Evolution Reaction Electrocatalysts: Design, Fabrication, and Application

The four-electron oxidation process of the oxygen evolution reaction (OER) highly influences the performance of many green energy storage and conversion devices due to its sluggish kinetics. The fabrication of cost-effective OER electrocatalysts via a facile and green method is, hence, highly desirable. This review summarizes and discusses the recent progress in creating carbon-based materials for alkaline OER. The contents mainly focus on the design, fabrication, and application of carbon-based materials for alkaline OER, including metal-free carbon materials, carbon-based supported composites, and carbon-based material core-shell hybrids. The work presents references and suggestions for the rational design of highly efficient carbon-based OER materials.

Constructing highly efficient bifunctional catalysts for oxygen reduction and oxygen evolution by modifying MXene with transition metal

Exploring highly active electrocatalysts for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) has become a growing interest in recent years. Herein, an efficient pathway for designing MXene-based ORR/OER catalysts is proposed. It involves introducing non-noble metals into Vo (vacancy site), H1 and H2 (the hollow sites on top of C and the metal atom, respectively) sites on M2CO2 surfaces, named TM-VO/H1/H2-M2CO2 (TM = Fe, Co, Ni, M = V, Nb, Ta). Among these recombination catalysts, Co-H1-V2CO2 and Ni-H1-V2CO2 exhibit the most promising ORR catalytic activities, with low overpotential values of 0.35 and 0.37 V, respectively. Similarly, Fe-H1-V2CO2, Co-VO-Nb2CO2, and Ni-H2-Nb2CO2 possess low OER overpotential values of 0.29, 0.39, and 0.44 V, respectively, suggesting they have enormous potential as effective catalysts for OER. Notably, Co-H2-Ta2CO2 possesses the lowest potential gap value of 0.53 V, demonstrating it has an extraordinary bifunctional catalytic activity. The excellent catalytic performance of these recombination catalysts can be elucidated through an electronic structure analysis, which primarily relies on the electron-donating capacity and synergistic effects between transition metals and sub-metals. These results provide theoretical guidance for designing new ORR and OER catalysts using 2D MXene materials.

Unveiling the Role of Termination Groups in Stabilizing MXenes in Contact with Water

MXenes are versatile 2D materials demonstrating outstanding electrochemical and physical properties, but their practical use is limited, because of fast degradation in an aqueous environment. To prevent the degradation of MXenes, it is essential to understand the atomistic details of the reaction and to identify active sites. In this letter, we provided a computational analysis of the degradation processes at the interface between MXene basal planes and water using enhanced sampling ab initio molecular dynamics simulations and symbolic regression analysis. Our results indicate that the reactivity of Ti sites toward the water attack reaction depends on both local coordination and chemical composition of the MXene surfaces. Decreasing the work function of the Ti3C2Tx surfaces and avoiding Ti sites that are loosely anchored to the subsurface (e.g., O-coordinated) can improve surface stability. The developed computational framework can be further used to investigate other possible culprits of the degradation reaction, including the role of defects and edges.

Design Principles and Mechanistic Understandings of Non-Noble-Metal Bifunctional Electrocatalysts for Zinc-Air Batteries

Zinc-air batteries (ZABs) are promising energy storage systems because of high theoretical energy density, safety, low cost, and abundance of zinc. However, the slow multi-step reaction of oxygen and heavy reliance on noble-metal catalysts hinder the practical applications of ZABs. Therefore, feasible and advanced non-noble-metal electrocatalysts for air cathodes need to be identified to promote the oxygen catalytic reaction. In this review, we initially introduced the advancement of ZABs in the past two decades and provided an overview of key developments in this field. Then, we discussed the working mechanism and the design of bifunctional electrocatalysts from the perspective of morphology design, crystal structure tuning, interface strategy, and atomic engineering. We also included theoretical studies, machine learning, and advanced characterization technologies to provide a comprehensive understanding of the structure-performance relationship of electrocatalysts and the reaction pathways of the oxygen redox reactions. Finally, we discussed the challenges and prospects related to designing advanced non-noble-metal bifunctional electrocatalysts for ZABs.

Dipole Effect on Oxygen Evolution Reaction of 2D Janus Single-Atom Catalysts: A Case of Rh Anchored on the P6m2-NP Configurations

Catalytic performance of single-atom catalysts (SACs) relies fundamentally on the electronic nature and local coordination environment of the active site. Here, based on a machine-learning (ML)-aided density functional theory (DFT) method, we reveal that the intrinsic dipole in Janus materials has a significant impact on the catalytic activity of SACs, using 2D γ-phosphorus carbide (γ-PC) as a model system. Specifically, a local dipole around the active site is a key degree to tune the catalytic activity and can be used as an important descriptor with a high feature importance of 17.1% in predicting the difference of adsorption free energy (ΔGO* - ΔGOH*) to assess the activity of the oxygen evolution reaction. As a result, the catalytic performance of SACs can be tuned by an intrinsic dipole, in stark contrast to those external stimuli strategies previously used. These results suggest that dipole engineering and the revolutionary DFT-ML hybrid scheme are novel approaches for designing high-performance catalysts.

How to rationally design homogeneous catalysts for efficient CO2 electroreduction?

Electrified converting CO2 into valuable fuels and chemicals using a homogeneous electrochemical CO2 reduction (CO2ER) approach simplifies the operation, providing a potential option for decoupling energy harvesting and renewable chemical production. These merits benefit the scenarios where decentralization and intermittent power are key factors. This perspective aims to provide an overview of recent progress in homogeneous CO2ER. We introduce firstly the fundamentals chemistry of the homogeneous CO2ER, followed by a summary of the crucial factors and the important criteria broadly employed for evaluating the performance. We then highlight the recent advances in the most widely explored transition-metal coordinate complexes for the C1 and multicarbon (C2+) products from homogeneous CO2ER. Finally, we summarize the remaining challenges and opportunities for developing homogeneous electrocatalysts for efficient CO2ER. This perspective is expected to favor the rational design of efficient homogeneous electrocatalysts for selective CO2ER toward renewable fuels and feedstocks.

Theoretical Insights on the Charge State and Bifunctional OER/ORR Electrocatalyst Activity in 4d-Transition-Metal-Doped g-C3N4 Monolayers

Exploring efficient and stable electrocatalysts for the bifunctional oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) is vital to developing renewable energy technologies. However, due to the substantial and intricate design space associated with these bifunctional OER/ORR electrocatalysts, their development presents a formidable challenge, resulting in their cost-prohibitive nature in both experimental and computational studies. Herein, using the defect physics method, we systematically investigate the formation energies and bifunctional overpotential (ηBi) of 4d-transition-metal (4d-TM, 4d-TM = Zr, Nb, Mo, Ru, Rh, Pd, and Ag)-doped monolayer supercell g-C3N4 (4d-TM@C54N72) based on the density functional theory (DFT) calculations. Under N-rich and C-rich conditions, we find that the formation energies of RhN@C54N71 (Rh occupation N) and PdN@C54N71 (Pd occupation N) are smaller than that of other 4d-TMN@C54N71 (4d-TM occupation N site); for the 4d-TMint@C54N72 (4d-TM interstitial site occupation), the lowest-formation energy defects are Pdint@C54N72. These results indicate that they have better stabilities. Interestingly, for these formation energy lower systems, Pd0int@C54N72 (ηBi = 1.00 V) and Rh1+N@C54N71 (ηBi = 0.73 V) have ultralow overpotential and can be great candidates for bifunctional OER/ORR electrocatalysts. We find the reason is that adjusting the charge states of 4d-TM@C54N72 can tune the interaction strength between the oxygenated intermediates and the 4d-TM@C54N72, which plays a crucial role in the activity of reactions. Additionally, the data obtained through machine learning (ML) application suggest that the electronegativity (Nm) and bond length of 4d-TM and coordination atoms (dTM-OOH) are primary descriptors characterizing the OER and ORR activities, respectively. The charged defect tuning of the bifunctional OER/ORR activity for 4d-TM@C54N72 would enable electrocatalytic performance optimization and the development of potential electrocatalysts for renewable energy applications.

Bifunctional diatomic site catalysts supported by β12-borophene for efficient oxygen evolution and reduction reactions

Efficient bifunctional catalysts for oxygen evolution and reduction reactions (OERs/ORRs) are of great importance for sustainable and renewable clean energy, especially for metal-air batteries. Herein, we investigated β12-borophene with double-hole sites capped with 3d transition metal atoms to explore its catalyst performance for hydrogen evolution reactions (HERs), OERs and ORRs. It was found that the borophene is a good platform for diatomic site catalysts (DASCs) due to their advantage of stability over the corresponding single-atom catalysts (SACs) or clusters. The HER performance of DASCs on β12-BM was further improved compared to the SAC case. Furthermore, the supported FeNi DASC exhibited good catalytic performance for both OERs and ORRs, the overpotentials for which were 0.43 and 0.55 V, respectively, better than those of the corresponding supported Ni or Fe SAC due to synergistic effects. We herein propose a novel descriptor involving the Bader charges of coordinated atoms explicitly, behaving much better than the d-band center and integrated crystal orbital Hamilton population (-ICOHP) for DASCs. The synergistic effect of Fe-Ni pairs balanced the too strong binding of OH and further activated OH to achieve better catalytic performance. The results of this study can provide theoretical guidance for the design of efficient bifunctional electrocatalysts.

A novel tetragonal T-C2N supported transition metal atoms as superior bifunctional catalysts for OER/ORR: From coordination environment to rational design

Single-atom catalysts with particular electronic structures and precisely regulated coordination environments delivering excellent activity for oxygen-evolution reaction (OER) and oxygen-reduction reaction (ORR) are highly desirable for renewable energy applications. In this work, a novel tetragonal carbon nitride T-C2N monolayer with remarkable stability was predicted by using the RG2 method. Inspired by the well-defined atomic structures and just right N4 aperture of T-C2N substrate, the electrocatalytic performance of a series of transition metal single-atoms anchored on porous T-C2N matrix (TM@C2N) have been systematically investigated. In addition, machine learning (ML) method was employed with the gradient boosting regression GBR model to deeply explore the complex controlling factors and offer direct guidance for rational discovery of desirable catalysts. On this basis, the coordination environment of the central TM active sites has been tailored by incorporating heteroatoms. Impressively, the Co@C2N/B-C, Rh@C2N/SC and Rh@C2N/SN exhibit significantly enhanced OER/ORR activity with notably low ηOER/ηORR of 0.39/0.32, 0.26/0.35 and 0.37/0.27 V, respectively. Our work provides insights into the rational design, data-driven, performance regulation, mechanism analysis and practical application of TMNC catalysts. Such a systematic theoretical framework can also be expanded to many other kinds of catalysts for energy storage and conversion.

The Isoelectronic Dopant in the Z-Scheme SnS2/β-As Heterostructure Enhancing Photocatalytic Overall Water Splitting

The catalytic field aims to decrease reaction barriers, accelerate reaction processes, and enhance the selectivity toward a target product. This study uses first-principles calculations to design a modified direct Z-scheme SnS2/β-As heterostructure as a potential photocatalyst for overall water splitting. Our previous investigations have demonstrated that the SnS2/β-As heterostructure can realize a hydrogen evolution reaction (HER) under light, while the oxygen evolution reaction (OER) follows a pathway involving the intermediate HOOH*. Interestingly, by substituting an S atom of SnS2 with a Se or Te atom, the rate-determining step of the OER is significantly reduced from 3.76 eV to 2.56 or 2.22 eV. Moreover, the OER can occur directly without the transition via HOOH*. Isoelectronic doping effectively trades off the adsorption strength of OER intermediates and promotes the OER process. This work highlights the dual benefits of isoelectronic doping, namely lowering the reaction barrier of the rate-determining step and promoting the selectivity of end products. These findings provide insights into the rational design of high-efficiency photocatalysts for water splitting.

Building up a view and understanding of the multifunctional activity of black phosphorous nanosheet modified with the metal atom

Constructing metal-semiconductor interfaces by loading metal atoms onto two-dimensional material to build atomically dispersed single-atom catalysts (SACs) has emerged as a new frontier for improving atom utilization and designing multifunctional electrocatalysts. Nowadays, studies on black phosphorus nanosheets in electrocatalysis have received much attention and the successful preparation of metal nanoparticle/black phosphorus (BP) hybrid electrocatalysts indicates BP nanosheets can serve as a potential support platform for SACs. Herein, by using large-scale ab initio calculations, we explored a large composition space of SACs with transition metal atoms supported on BP monolayer (M-BP) and built a comprehensive picture of activity trend, stability, and electronic origin towards oxygen reduction and evolution reaction (ORR and OER) and hydrogen evolution reaction (HER). The results show that the catalytic activity can be widely tuned by reasonable regulation of metal atoms. Ni-, Pd-, and Pt-BP could effectively balance the binding strength of the target intermediates, thus achieving efficient bifunctional activity for OER and ORR. Favorable bifunctional catalytic performance for OER and HER can be realized on Rh-BP. Especially, Pt-BP exhibits promising trifunctional activity towards OER, ORR, and HER. Multiple-level corrections among overpotential, Gibbs free energy, orbital population, and d-band center reveal that the trend and origin of catalytic activity are intrinsically determined by the d-band center of metal sites. The thermodynamic and dynamic stability simulations demonstrate that the active metal centers are firmly anchored on BP substrate with intact M-P bonds. These findings provide a theoretical basis for the rational design of BP-based SACs toward promising multifunctional activity.

Spontaneous Internal Electric Field in Heterojunction Boosts Bifunctional Oxygen Electrocatalysts for Zinc-Air Batteries: Theory, Experiment, and Application

Heterojunctions are a promising class of materials for high-efficiency bifunctional oxygen electrocatalysts in both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). However, the conventional theories fail to explain why many catalysts behave differently in ORR and OER, despite a reversible path (* O2 ⇋* OOH⇋* O⇋* OH). This study proposes the electron-/hole-rich catalytic center theory (e/h-CCT) to supplement the existing theories, it suggests that the Fermi level of catalysts determines the direction of electron transfer, which affects the direction of the oxidation/reduction reaction, and the density of states (DOS) near the Fermi level determines the accessibility for injecting electrons and holes. Additionally, heterojunctions with different Fermi levels form electron-/hole-rich catalytic centers near the Fermi levels to promote ORR/OER, respectively. To verify the universality of the e/h-CCT theory, this study reveals the randomly synthesized heterostructural Fe3 N-FeN0.0324 (Fex N@PC with DFT calculations and electrochemical tests. The results show that the heterostructural F3 N-FeN0.0324 facilitates the catalytic activities for ORR and OER simultaneously by forming an internal electron-/hole-rich interface. The rechargeable ZABs with Fex N@PC cathode display a high open circuit potential of 1.504 V, high power density of 223.67 mW cm-2 , high specific capacity of 766.20 mAh g-1 at 5 mA cm-2 , and excellent stability for over 300 h.

The rational design of high-performance graphene-based single-atom electrocatalysts for the ORR using machine learning

In this work, high-performance two-dimensional (2D) graphene-based single-atom electrocatalysts (ZZ/ZA-MN_xC_y) for the oxygen reduction reaction (ORR) were screened out using machine learning (ML). A model was built for the fast prediction of electrocatalysts and two descriptors valence electron correction (VEc) and degree of construction differences (DC) were proposed to improve the accuracy of the model prediction. Two evaluation criteria, high-performance catalyst retention rate r_R and high-performance catalyst occupancy rate r_O, were proposed to evaluate the accuracy of ML models in high-performance catalyst screening. The addition of VEc and DC in the model could change the mean absolute error (MAE_test) of the test set, the coefficient of determination (R²_test) of the test set, r_O, and r_R from 0.334 V, 0.683, 0.222, and 0.360 to 0.271 V, 0.774, 0.421, and 0.671, respectively. The partially screened potential high-performance ORR electrocatalysts such as ZZ-CoN₄ and ZZ-CoN₃C₁ were also further investigated using a Density Functional Theory (DFT) method, which confirmed the accuracy of the ML model (MAE = 0.157 V, R² = 0.821).

Recent advances in developing multiscale descriptor approach for the design of oxygen redox electrocatalysts

Oxygen redox electrocatalysis is the crucial electrode reaction among new-era energy sources. The prerequisite to rationally design an ideal electrocatalyst is accurately identifying the structure-activity relationship based on the so-called descriptors which link the catalytic performance with structural properties. However, the quick discovery of those descriptors remains challenging. In recent, the high-throughput computing and machine learning methods were identified to present great prospects for accelerating the screening of descriptors. That new research paradigm improves cognition in the way of oxygen evolution reaction/oxygen reduction reaction activity descriptor and reinforces the understanding of intrinsic physical and chemical features in the electrocatalytic process from a multiscale perspective. This review summarizes those new research paradigms for screening multiscale descriptors, especially from atomic scale to cluster mesoscale and bulk macroscale. The development of descriptors from traditional intermediate to eigen feature parameters has been addressed which provides guidance for the intelligent design of new energy materials.

Rational Design of Atomically Dispersed Metal Site Electrocatalysts for Oxygen Reduction Reaction

Future renewable energy supply and a cleaner Earth greatly depend on various crucial catalytic reactions for the society. Atomically dispersed metal site electrocatalysts (ADMSEs) have attracted tremendous research interest and are considered as the next-generation promising oxygen reduction reaction (ORR) electrocatalysts due to the maximum atom utilization efficiency, tailorable catalytic sites, and tunable electronic structures. Despite great efforts have been devoted to the development of ADMSEs, the systematic summary for design principles of high-efficiency ADMSEs is not sufficiently highlighted for ORR. In this review, the authors first summarize the fundamental ORR mechanisms for ADMSEs, and further discuss the intrinsic catalytic mechanism from the perspective of theoretical calculation. Then, the advanced characterization techniques to identify the active sites and effective synthesis methods to prepare catalysts for ADMSEs are also showcased. Subsequently, a special emphasis is placed on effective strategies for the rational design of the advanced ADMSEs. Finally, the present challenges to be addressed in practical application and future research directions are also proposed to overcome the relevant obstacles for developing high-efficiency ORR electrocatalysts. This review aims to provide a deeper understanding for catalytic mechanisms and valuable design principles to obtain the advanced ADMSEs for sustainable energy conversion and storage techniques.

How machine learning can accelerate electrocatalysis discovery and optimization

Advances in machine learning (ML) provide the means to bypass bottlenecks in the discovery of new electrocatalysts using traditional approaches. In this review, we highlight the currently achieved work in ML-accelerated discovery and optimization of electrocatalysts via a tight collaboration between computational models and experiments. First, the applicability of available methods for constructing machine-learned potentials (MLPs), which provide accurate energies and forces for atomistic simulations, are discussed. Meanwhile, the current challenges for MLPs in the context of electrocatalysis are highlighted. Then, we review the recent progress in predicting catalytic activities using surrogate models, including microkinetic simulations and more global proxies thereof. Several typical applications of using ML to rationalize thermodynamic proxies and predict the adsorption and activation energies are also discussed. Next, recent developments of ML-assisted experiments for catalyst characterization, synthesis optimization and reaction condition optimization are illustrated. In particular, the applications in ML-enhanced spectra analysis and the use of ML to interpret experimental kinetic data are highlighted. Additionally, we also show how robotics are applied to high-throughput synthesis, characterization and testing of electrocatalysts to accelerate the materials exploration process and how this equipment can be assembled into self-driven laboratories.

Heterogeneous catalysis mediated by light, electricity and enzyme via machine learning: Paradigms, applications and prospects

Energy crisis and environmental pollution have become the bottleneck of human sustainable development. Therefore, there is an urgent need to develop new catalysts for energy production and environmental remediation. Due to the high cost caused by blind screening and limited valuable computing resources, the traditional experimental methods and theoretical calculations are difficult to meet with the requirements. In the past decades, computer science has made great progress, especially in the field of machine learning (ML). As a new research paradigm, ML greatly accelerates the theoretical calculation methods represented by first principal calculation and molecular dynamics, and establish the physical picture of heterogeneous catalytic processes for energy and environment. This review firstly summarized the general research paradigms of ML in the discovery of catalysts. Then, the latest progresses of ML in light-, electricity- and enzyme-mediated heterogeneous catalysis were reviewed from the perspective of catalytic performance, operating conditions and reaction mechanism. The general guidelines of ML for heterogeneous catalysis were proposed. Finally, the existing problems and future development trend of ML in heterogeneous catalysis mediated by light, electricity and enzyme were summarized. We highly expect that this review will facilitate the interaction between ML and heterogeneous catalysis, and illuminate the development prospect of heterogeneous catalysis.

Strain-mediated oxygen evolution reaction on magnetic two-dimensional monolayers

By screening 56 magnetic 2D monolayers through first-principles calculations, it was found that 8 magnetic 2D monolayers (CoO₂, FeO₂, FeSe, FeTe, VS₂, VSe₂, VTe₂ and CrSe₂) can bind O*, OH* and OOH* intermediates of the oxygen evolution reaction (OER), in which the overpotentials of CoO₂, FeO₂, VSe₂, and VTe₂ monolayers are 0.684, 1.107, 0.863 and 0.837 V, respectively. After applying suitable biaxial tensile strains, the overpotentials of CoO₂, FeO₂ and VTe₂ monolayers are reduced over 40%. In particular, the overpotentials of CoO₂ and VTe₂ monolayers decrease to 0.372 V and 0.491 V under the biaxial tensile strains of 4.0% and 3.0%, respectively, which are comparable to the reported overpotentials of noble metal and low-dimensional materials. Tensile strains modify the potential determining step for the OER and enhance the catalytic activity of metal atoms of magnetic 2D monolayers. Magnetic 2D monolayers could be activated by strain engineering as catalysts for the OER.

Strain Effects on the Electronic and Optical Properties of Blue Phosphorene

Monolayer blue phosphorene (BlueP) systems were investigated under biaxial strain range from −10% to +10%. All these systems exhibit excellent stability, accompanying changes in the electronic and optical properties. BlueP becomes metallic at −10% strain and transforms into a direct semiconductor at 10% strain while maintaining indirect semiconductor behaviors at −8% to +8% strain. The bandgap of BlueP decreases linearly with strain, and tensile strain exhibits a more moderate bandgap modulation than compressive strain. The real part of the dielectric function of BlueP is enhanced under compressive strain, while the optical absorption in the visible and the infrared light regions increases significantly under tensile strain. The maximum absorption coefficient of 0.52 ×105/cm occurs at 530 nm with the 10% strain. Our analysis indicates that the semiconductor–metal transition and the indirect–direct bandgap transition are the competition results of the energy states near the Fermi level under a massive strain. The potent compressive strain leads the py orbitals of the conduction band to move downward and pass through the Fermi level at the K point. The robust tensile strain guides the energy states at the Γ point to approach the Fermi level and become the band edges. Our results suggest that the energy storage capacity of BlueP can be significantly improved by compressive strain, while the visible light photocatalytic performance is enhanced by tensile strains of less than 8%. Our works provide a reference for the practical applications of BlueP in photocatalyst, photovoltaic cells, and electronic devices.

Strain engineering in single-atom catalysts: GaPS4 for bifunctional oxygen reduction and evolution

We report here a theoretical study on 34 transition metal doped two-dimensional GaPS4 catalysts denoted as transition metal transition metal@VS-GaPS4.

Exploring high-efficiency electrocatalysts of metal-doped two-dimensional C4N for oxygen reduction, oxygen evolution, and hydrogen evolution reactions by first-principles screening

The HER/ORR/OER on 3d, 4d, and 5d transition metal doped C4N are studied using DFT methods.

The surface reconstruction induced enhancement of the oxygen evolution reaction on α-SnWO4 (010) based on a density functional theory study

It is possible to stabilize the O–W, O–Sn, R–OOSn and ST3 terminations of the α-SnWO4(010) surface. The O–Sn termination exhibits a low overpotential value of 0.51 V, showing remarkable oxygen evolution reaction (OER) performance.