Towards the computational design of solid catalysts

Exploring the Polymorphism of Dicalcium Silicates Using Transfer Learning Enhanced Machine Learning Atomic Potentials

Belitic cements are a greener alternative to Ordinary Portland Cement due to the lower CO2 associated with their production. However, their low reactivity with water is currently a drawback, resulting in longer setting times. In this study, we utilize a combination of evolutionary algorithms and machine learning atomic potentials (MLPs) to identify previously unreported belite polymorphs that may exhibit higher hydraulic reactivity than the known phases. To address the high computational demand of this methodology, we propose a novel transfer learning approach for generating MLPs. First, the models are pretrained on a large set of classical data (ReaxFF) and then retrained with density functional theory (DFT) data. We demonstrate that the transfer learning enhanced potentials exhibit higher accuracy, require less training data, and are more transferable than those trained exclusively on DFT data. The generated machine learning potential enables a fast, exhaustive, and reliable exploration of the dicalcium silicate polymorphs. This includes studying their stability through phonon analysis and calculating their structural and elastic properties. Overall, we identify ten new belite polymorphs within the energy range of the existing ones, including a layered phase with potentially high reactivity.

Breaking the Linear Scaling Relationship by Alloying Micro Sn to a Cu Surface toward CO2 Electrochemical Reduction

The electrochemical CO2 reduction reaction (CO2RR) to HCOOH provides an avenue for reducing global accelerated CO2 emissions and producing high-value-added chemicals. Nevertheless, the presence of an inherent linear scaling relationship (LSR) between *OCHO and *HCOOH leads to the electrosynthesis of HCOOH being achieved at high cathodic potentials. In this work, by adjusting the different Cu:Sn ratio of SnxCu(1-x) alloys, we comprehensively explored the electrocatalytic 2e- CO2RR performance toward the production of HCOOH. Combining density functional theory calculations with the constant-potential implicit solvent model, the Sn0.03Cu0.97 surface alloy was posited to be a promising electrocatalyst with superior HCOOH selectivity and an ultralow limiting potential of -0.20 V in an environment of pH = 7.2. The high performance was found to originate from the breaking of the LSR, which is a result of an extraordinary electronic property of the active Cu site. This work not only advances a global-searched strategy for the rational design of efficient catalysts toward HCOOH production but also provides in-depth insights into the underlying mechanism for the enhanced performance of microalloy electrocatalysts.

A compendium of all-in-one solar-driven water splitting using ZnIn2S4-based photocatalysts: guiding the path from the past to the limitless future

Photocatalytic water splitting represents a leading approach to harness the abundant solar energy, producing hydrogen as a clean and sustainable energy carrier. Zinc indium sulfide (ZIS) emerges as one of the most captivating candidates attributed to its unique physicochemical and photophysical properties, attracting much interest and holding significant promise in this domain. To develop a highly efficient ZIS-based photocatalytic system for green energy production, it is paramount to comprehensively understand the strengths and limitations of ZIS, particularly within the framework of solar-driven water splitting. This review elucidates the three sequential steps that govern the overall efficiency of ZIS with a sharp focus on the mechanisms and inherent drawbacks associated with each phase, including commonly overlooked aspects such as the jeopardising photocorrosion issue, the neglected oxidative counter surface reaction kinetics in overall water splitting, the sluggish photocarrier dynamics and the undesired side redox reactions. Multifarious material design strategies are discussed to specifically mitigate the formidable limitations and bottleneck issues. This review concludes with the current state of ZIS-based photocatalytic water splitting systems, followed by personal perspectives aimed at elevating the field to practical consideration for future endeavours towards sustainable hydrogen production through solar-driven water splitting.

Ichor: A Python library for computational chemistry data management and machine learning force field development

We present ichor, an open-source Python library that simplifies data management in computational chemistry and streamlines machine learning force field development. Ichor implements many easily extensible file management tools, in addition to a lazy file reading system, allowing efficient management of hundreds of thousands of computational chemistry files. Data from calculations can be readily stored into databases for easy sharing and post-processing. Raw data can be directly processed by ichor to create machine learning-ready datasets. In addition to powerful data-related capabilities, ichor provides interfaces to popular workload management software employed by High Performance Computing clusters, making for effortless submission of thousands of separate calculations with only a single line of Python code. Furthermore, a simple-to-use command line interface has been implemented through a series of menu systems to further increase accessibility and efficiency of common important ichor tasks. Finally, ichor implements general tools for visualization and analysis of datasets and tools for measuring machine-learning model quality both on test set data and in simulations. With the current functionalities, ichor can serve as an end-to-end data procurement, data management, and analysis solution for machine-learning force-field development.

A singular plasmonic-thermoelectric hollow nanostructure inducing apoptosis and cuproptosis for catalytic cancer therapy

Thermoelectric technology has recently emerged as a distinct therapeutic modality. However, its therapeutic effectiveness is significantly limited by the restricted temperature gradient within living organisms. In this study, we introduce a high-performance plasmonic-thermoelectric catalytic therapy utilizing urchin-like Cu2-xSe hollow nanospheres (HNSs) with a cascade of plasmonic photothermal and thermoelectric conversion processes. Under irradiation by a 1064 nm laser, the plasmonic absorption of Cu2-xSe HNSs, featuring rich copper vacancies (VCu), leads to a rapid localized temperature gradient due to their exceptionally high photothermal conversion efficiency (67.0%). This temperature gradient activates thermoelectric catalysis, generating toxic reactive oxygen species (ROS) targeted at cancer cells. Density functional theory calculations reveal that this vacancy-enhanced thermoelectric catalytic effect arises from a much more carrier concentration and higher electrical conductivity. Furthermore, the exceptional photothermal performance of Cu2-xSe HNSs enhances their peroxidase-like and catalase-like activities, resulting in increased ROS production and apoptosis induction in cancer cells. Here we show that the accumulation of copper ions within cancer cells triggers cuproptosis through toxic mitochondrial protein aggregation, creating a synergistic therapeutic effect. Tumor-bearing female BALB/c mice are used to evaluate the high anti-cancer efficiency. This innovative approach represents the promising instance of plasmonic-thermoelectric catalytic therapy, employing dual pathways (membrane potential reduction and thioctylated protein aggregation) of mitochondrial dysfunction, all achieved within a singular nanostructure. These findings hold significant promise for inspiring the development of energy-converting nanomedicines.

Engineered Two-Dimensional Transition Metal Dichalcogenides for Energy Conversion and Storage

Designing efficient and cost-effective materials is pivotal to solving the key scientific and technological challenges at the interface of energy, environment, and sustainability for achieving NetZero. Two-dimensional transition metal dichalcogenides (2D TMDs) represent a unique class of materials that have catered to a myriad of energy conversion and storage (ECS) applications. Their uniqueness arises from their ultra-thin nature, high fractions of atoms residing on surfaces, rich chemical compositions featuring diverse metals and chalcogens, and remarkable tunability across multiple length scales. Specifically, the rich electronic/electrical, optical, and thermal properties of 2D TMDs have been widely exploited for electrochemical energy conversion (e.g., electrocatalytic water splitting), and storage (e.g., anodes in alkali ion batteries and supercapacitors), photocatalysis, photovoltaic devices, and thermoelectric applications. Furthermore, their properties and performances can be greatly boosted by judicious structural and chemical tuning through phase, size, composition, defect, dopant, topological, and heterostructure engineering. The challenge, however, is to design and control such engineering levers, optimally and specifically, to maximize performance outcomes for targeted applications. In this review we discuss, highlight, and provide insights on the significant advancements and ongoing research directions in the design and engineering approaches of 2D TMDs for improving their performance and potential in ECS applications.

Unifying the ORR and OER with surface oxygen and extracting their intrinsic activities on platinum

Common half-cell measurements deliver oxygen reduction activities linked to the chosen scan rate, limiting their value for fundamental and comparative studies on platinum. Here we show a deconvolution of the intrinsic kinetics from the effect of surface oxygen on platinum. We find an electronic effect of the surface oxygen, substantiate a Tafel slope of ~120 mV/decade, obtain an exchange current density of 13 ± 4 µA/cm2, and an activity of 7 mA/cm2 at 900 mV. Eventually, we broaden the scope of this analysis to the effects of surface rearrangement, alloying, and supported Pt nanoparticles, the latter providing insight into discrepancies between half-cell and fuel cell measurements. We find through computational methods that binding energies of intermediates would be weakened by the presence of highly coordinated oxygen atoms. Finally, we obtain a phenomenological rate equation for the oxygen reduction and evolution reaction, suggesting that both reactions follow a shared mechanism.

Growing highly ordered Pt and Mn bimetallic single atomic layers over graphdiyne

Controlling the precise growth of atoms is necessary to achieve manipulation of atomic composition and atomic position, regulation of electronic structure, and an understanding of reactions at the atomic level. Herein, we report a facile method for ordered anchoring of zero-valent platinum and manganese atoms with single-atom thickness on graphdiyne under mild conditions. Due to strong and incomplete charge transfer between graphdiyne and metal atoms, the formation of metal clusters and nanoparticles can be inhibited. The size, composition and structure of the bimetallic nanoplates are precisely controlled by the natural structure-limiting effect of graphdiyne. Experimental characterization clearly demonstrates such a fine control process. Electrochemical measurements show that the active site of platinum-manganese interface on graphdiyne guarantees the high catalytic activity and selectivity (~100%) for alkene-to-diol conversion. This work lays a solid foundation for obtaining high-performance nanomaterials by the atomic engineering of active site.

Universal Predictive Power: Introducing the Electronic Structure Decomposition Approach for CO Adsorption and Activation on Al2O3-Supported Ru Nanoparticles

Accurate prediction of catalyst performance is crucial for designing materials with specific catalytic functions. While the density functional theory (DFT) method is widely used for its accuracy, modeling heterogeneous systems, especially supported transition metals, poses significant computational challenges. To address these challenges, we introduce the Electronic Structure Decomposition Approach (ESDA), a novel method that identifies specific density of states (DOS) areas responsible for adsorbate interaction and activation on the catalyst. As a case study, we investigate the influence of α-Al2O3(0001) as a support material on CO adsorption energy and the stretching frequency of the C-O bond on Ru nanoparticles (NPs). Using multiple linear regression analysis, ESDA models were trained with data from isolated Ru NPs and adjusted using supported NP sample data. The ESDA models accurately predict the CO adsorption energies and C-O vibrational frequencies, demonstrating strong linear correlations between predicted and DFT-calculated values with low errors across various adsorption sites for both isolated and supported Ru NPs. Beyond pinpointing the DOS areas responsible for CO adsorption and C-O bond activation, this study provides insights into manipulating these DOS areas to control CO activation, hence facilitating CO dissociation. Additionally, ESDA significantly accelerates the characterization and prediction of CO adsorption and activation on both isolated and supported Ru NPs compared to DFT calculations, expediting the design of new catalytic materials and advancing catalysis research. Furthermore, ESDA's reliance on the electronic structure as a descriptor suggests its potential for predicting various properties beyond catalysis, broadening its applicability across diverse scientific domains.

Optimizing Cr(VI) reduction to Cr(III) using Pd-CNTs nanocatalyst: kinetic Monte Carlo simulation and experimental design insights

In this investigation, we explored the kinetics of Cr(VI) reduction to Cr(III) on carbon nanotube decorated with palladium (Pd-CNTs) nanocatalyst, using formic acid as the reducing agent. This study has been bone utilizing kinetic Monte Carlo simulation and experimental design methods. The mechanism and kinetic parameters of this reaction are provided. The effect various factors such as reaction time, pH level, dichromate (Cr2O72-) concentration, and formic acid concentration on Cr(VI) reduction was studied. Concentrations of HCOOH and Cr2O72- were identified as the crucial variables, while the HCOOH concentration has the most significant impact. Positive influences on Cr(VI) reduction were observed with increasing pH level and HCOOH concentration. Reaction time positively affects on Cr(VI) reduction efficiency. However, the concentration of Cr2O72- showed an increasing effect up to a threshold, negatively impacting the efficiency. The optimal conditions (Reaction time = 60 min, pH = 4.5, [Cr2O72-] = 5.05 × 10-3 M, and [HCOOH] = 0.95 M) for Cr(VI) reduction. At optimal conditions, the Cr(VI) reduction efficiency was obtained to be 100%.

Revisiting the photocharging effect on the BiVO4 (010) surface by identifying the charge reaction kinetics

The alteration of intermediates on the (010) facet of BiVO4 leads to variations in charge accumulation numbers before overcoming the rate-determining step, which accounts for the enhanced charge transfer for oxygen evolution. This discovery provides insights into the photocharging effect and the photoelectrochemical reaction mechanism.

Catalytic mechanisms for As(III) oxidation by H2O2 over TiO2 surfaces, and effects of support, vacancy and photoirradiation

As(III) is much more toxic than As(V) while shows apparently lower affinity at minerals surfaces. Oxidation of As(III) to As(V) by H2O2 over anatase surface provides an attractive avenue for pollution control, and the chemocatalytic and photocatalytic mechanisms are unraveled by means of the DFT + D3 approach. Impacts of anatase as support, O2c/O3c vacancy, photoirradiation are addressed as well. As(III) oxidation under various reaction conditions leads to As(V) through dual electron transfers, while energy barriers differ substantially and decline as 1.80 (direct oxidation) > 1.35 (anatase as support) > 1.24 (O3c vacancy) > 0.50 (chemocatalysis) > 0.28 (photocatalysis) ≥ 0.26 (O2c vacancy) eV. Anatase as support promotes the reaction through bonding with H2O2/As(OH)3 and electron transfers, and its close participation during chemocatalysis produces the TiOOH active site that causes As(III) oxidation to proceed facilely under ambient circumstances. TiOOH exists in two forms (monodentate and bidentate mononuclear) and is critical for chemocatalysis, while its destruction for O3c vacancy exhibits strongly adverse effects to As(III) oxidation. Photoirradiation readily generates the OH• radicals, and corresponding mechanism is plausible while less preferred than the newly posed mechanism based on the Ti(H2O2) active site. Synergism among a number of surface atoms conduces to the superior activity for O2c vacancy and photocatalysis. Results provide a comprehensive understanding for As(III) oxidation to As(V) by H2O2, and facilitate catalysts design for As(III) oxidation that alleviates environmental pollution.

Toward an ab Initio Description of Adsorbate Surface Dynamics

The advent of machine learning potentials (MLPs) provides a unique opportunity to access simulation time scales and to directly compute physicochemical properties that are typically intractable using density functional theory (DFT). In this study, we use an active learning curriculum to train a generalizable MLP using the DeepMD-kit architecture. By using sufficiently long MLP-based molecular dynamics (MD) simulations, which provide DFT-level accuracy, we investigate the diffusion of key surface-bound adsorbates on a Ag(111) facet. Detailed analysis of the MLP/MD-calculated diffusivities sheds light on the potential shortcomings of using DFT-based nudged elastic band to estimate surface diffusion barriers. More generally, while this study is focused on a specific system, we anticipate that the underlying workflows and the resulting models can be extended to other adsorbates and other materials in the future.

Chemical Softness in Aromatic Adsorption: Benzene, Nitrobenzene and Anisole on Pt{111}

We describe a method for the calculation of chemical softness at metal surfaces, demonstrating its utility in understanding the adsorption of benzene, nitrobenzene and anisole at the Pt{111} surface. Based on this method, we show that directing effects due to either of the substituent groups are mostly swamped by substrate influences, while significant variations in softness within the groups themselves are readily apparent.

Recent Advances in Revealing the Electrocatalytic Mechanism for Hydrogen Energy Conversion System

In light of the intensifying global energy crisis and the mounting demand for environmental protection, it is of vital importance to develop advanced hydrogen energy conversion systems. Electrolysis cells for hydrogen production and fuel cell devices for hydrogen utilization are indispensable in hydrogen energy conversion. As one of the electrolysis cells, water splitting involves two electrochemical reactions, hydrogen evolution reaction and oxygen evolution reaction. And oxygen reduction reaction coupled with hydrogen oxidation reaction, represent the core electrocatalytic reactions in fuel cell devices. However, the inherent complexity and the lack of a clear understanding of the structure-performance relationship of these electrocatalytic reactions, have posed significant challenges to the advancement of research in this field. In this work, the recent development in revealing the mechanism of electrocatalytic reactions in hydrogen energy conversion systems is reviewed, including in situ characterization and theoretical calculation. First, the working principles and applications of operando measurements in unveiling the reaction mechanism are systematically introduced. Then the application of theoretical calculations in the design of catalysts and the investigation of the reaction mechanism are discussed. Furthermore, the challenges and opportunities are also summarized and discussed for paving the development of hydrogen energy conversion systems.

Modeling Scanning Electrochemical Cell Microscopy (SECCM) in Twisted Bilayer Graphene

Twisted 2D-flat band materials host exotic quantum phenomena and novel moiré patterns, showing immense promise for advanced spintronic and quantum applications. Here, we evaluate the nanostructure-activity relationship in twisted bilayer graphene by modeling it under the scanning electrochemical cell microscopy setup to resolve its spatial moiré domains. We solve the steady state ion transport inside a 3D nanopipette to isolate the current response at AA and AB domains. Interfacial reaction rates are obtained from a modified Marcus-Hush-Chidsey theory combining input from a tight binding model that describes the electronic structure of bilayer graphene. High rates of redox exchange are observed at the AA domains, an effect that reduces with diminished flat bands or a larger cross-sectional area of the nanopipette. Using voltammograms, we identify an optimal voltage that maximizes the current difference between the domains. Our study lays down the framework to electrochemically capture prominent features of the band structure that arise from spatial domains and deformations in 2D flat-band materials.

Emerging Atomistic Modeling Methods for Heterogeneous Electrocatalysis

Heterogeneous electrocatalysis lies at the center of various technologies that could help enable a sustainable future. However, its complexity makes it challenging to accurately and efficiently model at an atomic level. Here, we review emerging atomistic methods to simulate the electrocatalytic interface with special attention devoted to the components/effects that have been challenging to model, such as solvation, electrolyte ions, electrode potential, reaction kinetics, and pH. Additionally, we review relevant computational spectroscopy methods. Then, we showcase several examples of applying these methods to understand and design catalysts relevant to green hydrogen. We also offer experimental views on how to bridge the gap between theory and experiments. Finally, we provide some perspectives on opportunities to advance the field.

Capturing Catalyst Strain Dynamics during Operando CO Oxidation

Understanding the strain dynamic behavior of catalysts is crucial for the development of cost-effective, efficient, stable, and long-lasting catalysts. Using time-resolved Bragg coherent diffraction imaging at the fourth generation Extremely Brilliant Source of the European Synchrotron (ESRF-EBS), we achieved subsecond time resolution during operando chemical reactions. Upon investigation of Pt nanoparticles during CO oxidation, the three-dimensional strain profile highlights significant changes in the surface and subsurface regions, where localized strain is probed along the [111] direction. Notably, a rapid increase in tensile strain was observed at the top and bottom Pt {111} facets during CO adsorption. Moreover, we detected oscillatory strain changes (6.4 s period) linked to CO adsorption during oxidation, where a time resolution of 0.25 s was achieved. This approach allows for the study of adsorption dynamics of catalytic nanomaterials at the single-particle level under operando conditions, which provides insight into nanoscale catalytic mechanisms.

Applicability of the d-Band Model to Predict the Influence of Elastic Strains on the Adsorption Energy of Different Adsorbates onto Pt and PtO2 Surfaces

The influence of elastic strains on the adsorption processes of seven adsorbates (H, C, N, O, CO, NO, and H) onto the surface of Pt(111) and PtO2 (110) has been investigated using density functional theory (DFT) simulations. The total adsorption energy was decomposed into mechanical and electronic contributions. Our results indicate that elastic strain in metals affects the adsorption energy by modifying the electronic structure of the surface rather than changing the physical space where the atoms reside after adsorption. In fact, the mechanical contribution to the adsorption energy in Pt was negligible compared to the electronic interaction and independent of the deformation. The mechanical contribution in the case of PtO2 was also independent of the applied strain, but its magnitude was slightly higher due to the ionic bonding between Pt and O atoms in the slab. The variation of the electronic contribution to the adsorption energy in Pt and PtO2 followed the predictions of the d-band model for all adsorbates, expanding its applicability to different adsorbates onto the same surface and to oxides.

Adsorbed Carbon Monoxide-Enabled Self-Terminated Au-Grafting on Pt6 Nanoclusters for Enhanced Methanol Electrooxidation

The study presents the first example of an adsorbed carbon monoxide (CO) enabled self-terminated Au-grafting on triphenylphosphine (PPh3) stabilized Pt6 nanoclusters (NCs) (Pt6 (PPh3)4Cl5 NCs or Pt6 NCs). Adsorbed PPh3 ligands weaken the Pt-CO bond enabling the self-terminated Au-grafting on Pt6 NCs. The Au-grafted Pt6 NCs exhibit enhanced methanol electrooxidation (MOR) in acidic solutions. The surface is composed of a PtAu ensemble exhibiting enhanced MOR and CO tolerance due to the synergistic interaction of Pt with Au and PPh3. The hydrogen underpotential deposition (H-UPD) signal from a CO-covered surface reveals the existence of free-Pt sites on the PtAu ensemble causing higher MOR reactivity. The Au and PPh3 ensure electrocatalytic activity of the NCs, depriving of them at anodic potentials results in "a death-valley" trend.

A systematic first-principles investigation of the structural, electronic, mechanical, optical, and thermodynamic properties of Half-Heusler ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn) for spintronics and optoelectronics applications

This paper is the first to look at the structural, electronic, mechanical, optical, and thermodynamic properties of the ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn) half-Heusler (HH) using DFT based first principles method. The lattice parameters that we have calculated are very similar to those obtained in prior investigations with theoretical and experimental data. The positive phonon dispersion curve confirm the dynamical stability of ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn). The electronic band structure and DOS confirmed that the studied materials ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn) are direct band gap semiconductors. The investigation also determined significant constants, including dielectric function, absorption, conductivity, reflectivity, refractive index, and loss function. These optical observations unveiled our compounds potential utilization in various electronic and optoelectronic device applications. The elastic constants were used to fulfill the Born criteria, confirming the mechanical stability and ductility of the solids ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn). The calculated elastic modulus revealed that our studied compounds are elastically anisotropic. Moreover, ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn) has a very low minimum thermal conductivity (Kmin), and a low Debye temperature (θD), which indicating their appropriateness for utilization in thermal barrier coating (TBC) applications. The Helmholtz free energy (F), internal energy (E), entropy (S), and specific heat capacity (Cv) are determined by calculations derived from the phonon density of states.

Microkinetic Molecular Volcano Plots for Enhanced Catalyst Selectivity and Activity Predictions

Molecular volcano plots, which facilitate the rapid prediction of the activity and selectivity of prospective catalysts, have emerged as powerful tools for computational catalysis. Here, we integrate microkinetic modeling into the volcano plot framework to develop "microkinetic molecular volcano plots". The resulting unified computational framework allows the influence of important reaction parameters, including temperature, reaction time, and concentration, to be quickly incorporated and more complex situations, such as off-cycle resting states and coupled catalytic cycles, to be tackled. Compared to previous generations of molecular volcanoes, these microkinetic counterparts offer a more comprehensive understanding of catalytic behavior, in which selectivity and product ratios can be explicitly determined by tracking the evolution of each product concentration over time. This is demonstrated by examining two case studies, rhodium-catalyzed hydroformylation and metal-catalyzed hydrosilylation, in which the unique insights provided by microkinetic modeling, as well as the ability to simultaneously screen catalysts and reaction conditions, are highlighted. To facilitate the construction of these plots/maps, we introduce mikimo, a Python program that seamlessly integrates with our previously developed automated volcano builder, volcanic.

The Importance of Reaction Energy in Predicting Chemical Reaction Barriers with Machine Learning Models

Improving our fundamental understanding of complex heterocatalytic processes increasingly relies on electronic structure simulations and microkinetic models based on calculated energy differences. In particular, calculation of activation barriers, usually achieved through compute-intensive saddle point search routines, remains a serious bottleneck in understanding trends in catalytic activity for highly branched reaction networks. Although the well-known Brønsted-Evans-Polyani (BEP) scaling - a one-feature linear regression model - has been widely applied in such microkinetic models, they still rely on calculated reaction energies and may not generalize beyond a single facet on a single class of materials, e. g., a terrace sites on transition metals. For highly branched and energetically shallow reaction networks, such as electrochemical CO2 reduction or wastewater remediation, calculating even reaction energies on many surfaces can become computationally intractable due to the combinatorial explosion of states that must be considered. Here, we investigate the feasibility of activation barrier prediction without knowledge of the reaction energy using linear and nonlinear machine learning (ML) models trained on a new database of over 500 dehydrogenation activation barriers. We also find that inclusion of the reaction energy significantly improves both classes of ML models, but complex nonlinear models can achieve performance similar to the simplest BEP scaling when predicting activation barriers on new systems. Additionally, inclusion of the reaction energy significantly improves generalizability to new systems beyond the training set. Our results suggest that the reaction energy is a critical feature to consider when building models to predict activation barriers, indicating that efforts to reliably predict reaction energies through, e. g., the Open Catalyst Project and others, will be an important route to effective model development for more complex systems.

Regulation of electron density redistribution for efficient alkaline hydrogen evolution reaction and overall water splitting

The rational design of morphology and heterogeneous interfaces for non-precious metal electrocatalysts is crucial in electrochemical water decomposition. In this paper, a bifunctional electrocatalyst (Ni/NiFe LDH), which coupling nickel with nickel-iron layer double hydroxide (NiFe LDH), is synthesized on carbon cloth. At current density of 10 mA cm-2, the Ni/NiFe LDH exhibits a low hydrogen evolution reaction (HER) overpotential of only 36 mV due to the accelerated electrolyte penetration, which is caused by superhydrophilic interface. Moreover, an alkaline electrolyzer is formed and provide a current density of 10 mA cm-2 with a voltage of only 1.49 V. It is confirmed by the density functional theory (DFT) that electron from the Ni layer is transferred to NiFe LDH layer, redistributing the local electron density around the heterogeneous phase interface. Thus, the Gibbs free energy for hydrogen adsorption is optimized. This work provides a promising strategy for the rational regulation of electrons at heterogeneous interfaces and the synthesis of flexible electrocatalysts.

Cu2MoS4 Nanocatalyst-Based Electrochemical Sensor for Ofloxacin Electro-Oxidation: Delineating the Combined Roles of Crystallinity and Morphology on the Analytical Performance

In this study, we demonstrate the influence of crystallinity and morphology on the analytical performance of various Cu2MoS4 (CMS) nanocatalysts-based electrochemical sensors for the high-efficiency detection of Ofloxacin (OFX) antibiotic. The electrochemical kinetics parameters including peak current response (ΔIp), peak-to-peak separation (ΔEp), electrochemically active surface area (ECSA), electron-transfer resistance (Rct), were obtained through the electrochemical analyses, which indicate the single-crystalline nature of CMS nanomaterials (NMs) is beneficial for enhanced electron-transfer kinetics. The morphological features and the electrochemical results for OFX detection substantiate that by tuning the tube-like to plate-like structures of the CMS NMs, it might noticeably enhance multiple adsorption sites and more intrinsic active catalytic sites due to the diffusion of analytes into the interstitial spaces between CMS nanoplates. As results, highly single-crystalline and plate-shaped morphology structures of CMS NMs would significantly enhance the electrocatalytic OFX oxidation in terms of onset potential (Eonset), Tafel slope, catalytic rate constant (kcat), and adsorption capacity (Γ). The CMS NMs-based electrochemical sensing platform showed excellent analytical performance toward the OFX detection with two ultra-wide linear detection concentration ranges from 0.25-100 and 100-1000 μM, a low detection limit of 0.058 μM, and an excellent electrochemical sensitivity (0.743 μA μM-1 cm-2).

Reducing the Runtime of Fault-Tolerant Quantum Simulations in Chemistry through Symmetry-Compressed Double Factorization

Quantum phase estimation based on qubitization is the state-of-the-art fault-tolerant quantum algorithm for computing ground-state energies in chemical applications. In this context, the 1-norm of the Hamiltonian plays a fundamental role in determining the total number of required iterations and also the overall computational cost. In this work, we introduce the symmetry-compressed double factorization (SCDF) approach, which combines a CDF of the Hamiltonian with the symmetry shift technique, significantly reducing the 1-norm value. The effectiveness of this approach is demonstrated numerically by considering various benchmark systems, including the FeMoco molecule, cytochrome P450, and hydrogen chains of different sizes. To compare the efficiency of SCDF to other methods in absolute terms, we estimate Toffoli gate requirements, which dominate the execution time on fault-tolerant quantum computers. For the systems considered here, SCDF leads to a sizable reduction of the Toffoli gate count in comparison to other variants of DF or even tensor hypercontraction, which is usually regarded as the most efficient approach for qubitization.

Toward Designing Reactive Metal Clusters for Dinitrogen Activation: A Guideline Based on N2 Initial Adsorption

Gas-phase metal clusters are ideal models to explore transition-metal-mediated N2 activation mechanism. However, the effective design and search of reactive clusters in N2 activation are currently hindered by the lack of clear guidelines. Inspired by the Sabatier principle, we discovered in this work that N2 initial adsorption energy (ΔEads) is an important parameter to control the N2 activation reactivity of metal clusters in the gas phase. This mechanistic insight obtained from high-level calculations rationalizes the N2 activation reactivity of many previously reported metal clusters when combined with the known factor determining the N≡N cleavage process. Furthermore, based on this guideline of ΔEads, we successfully designed several new reactive clusters for cleaving N≡N triple bond under mild conditions, including FeV2S2-, TaV2C2-, and TaV2C3-, the high N2 activation reactivity of which has been fully corroborated in our gas phase experiments employing mass spectrometry with collision-induced dissociation. The importance of ΔEads revealed in this work not only reshapes our understanding of N2 activation reactions in the gas phase but also could have implication for other N2 activation processes in the condensed phase. The more general establishment of this new perspective on N2 activation reactivity warrants future experimental and computational studies.

High-Rate and Selective C2H6-to-C2H4 Photodehydrogenation Enabled by Partially Oxidized Pdδ+ Species Anchored on ZnO Nanosheets under Mild Conditions

Photocatalytic C2H6-to-C2H4 conversion is very promising, yet it remains a long-lasting challenge due to the high C-H bond dissociation energy of 420 kJ mol-1. Herein, partially oxidized Pdδ+ species anchored on ZnO nanosheets are designed to weaken the C-H bond by the electron interaction between Pdδ+ species and H atoms, with efforts to achieve high-rate and selective C2H6-to-C2H4 conversion. X-ray photoelectron spectra, Bader charge calculations, and electronic localization function demonstrate the presence of partially oxidized Pdδ+ sites, while quasi-in situ X-ray photoelectron spectra disclose the Pdδ+ sites initially adopt and then donate the photoexcited electrons for C2H6 dehydrogenation. In situ electron paramagnetic resonance spectra, in situ Fourier transform infrared spectra, and trapping agent experiments verify C2H6 initially converts to CH3CH2OH via ·OH radicals, then dehydroxylates to CH3CH2· and finally to C2H4, accompanied by H2 production. Density-functional theory calculations elucidate that loading Pd site can lengthen the C-H bond of C2H6 from 1.10 to 1.12 Å, which favors the C-H bond breakage, affirmed by a lowered energy barrier of 0.04 eV. As a result, the optimized 5.87% Pd-ZnO nanosheets achieve a high C2H4 yield of 16.32 mmol g-1 with a 94.83% selectivity as well as a H2 yield of 14.49 mmol g-1 from C2H6 dehydrogenation in 4 h, outperforming all the previously reported photocatalysts under similar conditions.

Integration of a Bismuth-Based Tris-Mononuclear Complex with 2D Functional Materials for Highly Efficient and Durable Aqueous Electrocatalytic Hydrogen Evolution

The eminence of transitioning from traditional fossil fuel-based energy resources to renewable and sustainable energy sources is most evidently crucial. The potential of hydrogen as an alternative energy source has specifically focuses the electrocatalytic water splitting (EWS) as a promising technique for generating hydrogen. Development of efficient electrocatalysts to facilitate the EWS process while rationalizing the limitations of noble metal catalysts like platinum has become one of the daunting tasks. Consequently, porous functional materials such as metal complexes (MCs) and graphene oxide (GO) can act as potential catalysts for EWS. Therefore, a composite of GO and a mononuclear bismuth metal complex is synthesized through in situ facile synthesis, which is further utilized as an efficient electrocatalyst for the hydrogen evolution reaction (HER). Several potential electrocatalytic MC@GO composite (BMGO-3,5,7) materials were prepared with compositional variation of GO (3, 5, and 7 wt %). The experimental results demonstrate that the BMGO5 composite exhibits excellent HER activity with a low overpotential value of 105 mV at 10 mA cm-2 and a low Tafel slope of 44 mV dec-1 in 1 M KOH solution. Furthermore, a comprehensive investigation on the potentiality of the BMC-GO composite for hydrogen evolution from river water splitting was performed in order to address the issue of freshwater depletion. Inclusion of a mononuclear MC for facile synthesis of functional GO-based efficient electrocatalyst material is very scanty in the literature. This unique approach could assist future research endeavors toward designing efficient electrocatalysts for sustainable renewable energy generation. This is one of the first of its kind, where mononuclear MCs were utilized to develop GO-based functional composite materials for efficient electrocatalysis toward sustainable renewable energy generation.

Dynamic (Sub)surface-Oxygen Enables Highly Efficient Carbonyl-Coupling for Electrochemical Carbon Dioxide Reduction

Nowadays, high-valent Cu species (i.e., Cuδ +) are clarified to enhance multi-carbon production in electrochemical CO2 reduction reaction (CO2RR). Nonetheless, the inconsistent average Cu valence states are reported to significantly govern the product profile of CO2RR, which may lead to misunderstanding of the enhanced mechanism for multi-carbon production and results in ambiguous roles of high-valent Cu species. Dynamic Cuδ + during CO2RR leads to erratic valence states and challenges of high-valent species determination. Herein, an alternative descriptor of (sub)surface oxygen, the (sub)surface-oxygenated degree (κ), is proposed to quantify the active high-valent Cu species on the (sub)surface, which regulates the multi-carbon production of CO2RR. The κ validates a strong correlation to the carbonyl (*CO) coupling efficiency and is the critical factor for the multi-carbon enhancement, in which an optimized Cu2O@Pd2.31 achieves the multi-carbon partial current density of ≈330 mA cm-2 with a faradaic efficiency of 83.5%. This work shows a promising way to unveil the role of high-valent species and further achieve carbon neutralization.

Dynamic Active Sites In Situ Formed in Metal Nanoparticle Reshaping under Reaction Conditions

Understanding the nonequilibrium transformation of nanocatalysts under reaction conditions is important because metastable atomic structures may be created during the process, which offers unique activities in reactions. Although reshaping of metal nanoparticles (NPs) under reaction conditions has been widely recognized, the dynamic reshaping process has been less studied at the atomic scale. Here, we develop an atomistic kinetic Monte Carlo model to simulate the complete reshaping process of Pt nanoparticles in a CO environment and reveal the in situ formation of atomic clusters on the NP surface, a new type of active site beyond conventional understanding, boosting the reactivities in the CO oxidation reaction. Interestingly, highly active peninsula and inactive island clusters both form on the (111) facets and interchange in varying states of dynamic equilibrium, which influences the catalytic activities significantly. This study provides new fundamental knowledge of nanocatalysis and new guidance for the rational design of nanocatalysts.

Electrochemical Restructuring Driven Catalytic Cycle of Bi-Based Heterojunctions for High-Performance Lithium-Sulfur Batteries

Restructuring is an important phenomenon in catalytic reactions. Conversion-type materials with suitable redox potential may undergo in situ electrochemically driven restructurings and induce highly active catalytic sites in a working lithium-sulfur battery. Herein, driven by the electrochemical conversion reaction of BiVO4, a reversible catalytic cycle of Bi/amorphous Li3VO4 (a-Li3VO4) and Bi2S3/a-Li3VO4 heterojunctions is constructed, which targets the oxidation of Li2S and the conversion of polysulfide, respectively. The heterostructures and electrochemically driven size confinement provide abundant sites for shuttle restraining and sulfur conversion. Especially, the p-block Bi and Bi2S3 could dramatically reduce the conversion energy barriers of Li2S and polysulfide by virtue of the p-p orbital hybridization, promoting bidirectional reactions of the sulfur cathode. As a result, the corresponding sulfur cathode possesses a high reversible capacity of 7.5 mAh cm-2 after 120 cycles under a high sulfur loading of 10.3 mg cm-2 with a current density of 0.38 mA cm-2. This study furnishes a feasible scheme to obtain highly effective catalysts for bidirectional sulfur redox by utilizing the electrochemically induced restructuring.

Theoretical Investigation of the Adsorbate and Potential-Induced Stability of Cu Facets During Electrochemical CO2 and CO Reduction

The activity and product selectivity of electrocatalysts for reactions like the carbon dioxide reduction reaction (CO2RR) are intimately dependent on the catalyst's structure and composition. While engineering catalytic surfaces can improve performance, discovering the key sets of rational design principles remains challenging due to limitations in modeling catalyst stability under operating conditions. Herein, we perform first-principles density functional calculations adopting implicit solvation methods with potential control to study the influence of adsorbates and applied potential on the stability of different facets of model Cu electrocatalysts. Using coverage dependencies extracted from microkinetic models, we describe an approach for calculating potential and adsorbate-dependent contributions to surface energies under reaction conditions, where Wulff constructions are used to understand the morphological evolution of Cu electrocatalysts under CO2RR conditions. We identify that CO*, a key reaction intermediate, exhibits higher kinetically and thermodynamically accessible coverages on (100) relative to (111) facets, which can translate into an increased relative stabilization of the (100) facet during CO2RR. Our results support the known tendency for increased (111) faceting of Cu nanoparticles under more reducing conditions and that the relative increase in (100) faceting observed under CO2RR conditions is likely attributed to differences in CO* coverage between these facets.

Four Generations of Volcano Plots for the Oxygen Evolution Reaction: Beyond Proton-Coupled Electron Transfer Steps?

ConspectusDue to its importance for electrolyzers or metal-air batteries for energy conversion or storage, there is huge interest in the development of high-performance materials for the oxygen evolution reaction (OER). Theoretical investigations have aided the search for active material motifs through the construction of volcano plots for the kinetically sluggish OER, which involves the transfer of four proton-electron pairs to form a single oxygen molecule. The theory-driven volcano approach has gained unprecedented popularity in the catalysis and energy communities, largely due to its simplicity, as adsorption free energies can be used to approximate the electrocatalytic activity by heuristic descriptors.In the last two decades, the binding-energy-based volcano method has witnessed a renaissance with special concepts being developed to incorporate missing factors into the analysis. To this end, this Account summarizes and discusses the different generations of volcano plots for the example of the OER. While first-generation methods relied on the assessment of the thermodynamic information for the OER reaction intermediates by means of scaling relations, the second and third generations developed strategies to include overpotential and kinetic effects into the analysis of activity trends. Finally, the fourth generation of volcano approaches allowed the incorporation of various mechanistic pathways into the volcano methodology, thus paving the path toward data- and mechanistic-driven volcano plots in electrocatalysis.Although the concept of volcano plots has been significantly expanded in recent years, further research activities are discussed by challenging one of the main paradigms of the volcano concept. To date, the evaluation of activity trends relies on the assumption of proton-coupled electron transfer steps (CPET), even though there is experimental evidence of sequential proton-electron transfer (SPET) steps. While the computational assessment of SPET for solid-state electrodes is ambitious, it is strongly suggested to comprehend their importance in energy conversion and storage processes, including the OER. This can be achieved by knowledge transfer from homogeneous to heterogeneous electrocatalysis and by focusing on the material class of single-atom catalysts in which the active center is well defined. The derived concept of how to analyze the importance of SPET for mechanistic pathways in the OER over solid-state electrodes could further shape our understanding of the proton-electron transfer steps at electrified solid/liquid interfaces, which is crucial for further progress toward sustainable energy and climate neutrality.

Pd Clusters Loaded with Multivalent Cu Foam for Superior Electrochemical Nitrate Reduction and Selective N≡N Bond Formation

The electrochemical denitrification of nitrate (NO3 -) in actual wastewater to nitrogen (N2) is an effective approach to reversing the current imbalance of the nitrogen cycle and the eutrophication of water. However, electrostatic repulsion between NO3 - and the cathode results in the low efficiency of NO3 - reduction reaction (NO3RR). Here, density functional theory (DFT) calculations are used as a theoretical guide to design a Pd cluster-loaded multivalent Cu foam (Pd/Cu2O-CF) electrocatalyst, which achieves a splendid 97.8% NO3 - removal rate, 97.9% N2 selectivity, 695.5 mg N g-1 Pd h-1 reduction efficiency, and 60.0% Faradaic efficiency at -1.3 V versus SCE. The projected density of states (pDOS) indicates that NO3 - and Pd/Cu2O-CF are bonded via strong complexation between the O 2p (in NO3 -) and Cu 3d (in Cu2O) with the input of voltage, which reduces the electrostatic repulsion and enhances the enrichment of NO3 - on the cathode. In-situ characterizations demonstrate that Pd[H] can reduce Cu2O to Cu, and subsequently Cu reduces NO3 - to nitrite (NO2 -) accompanied by in situ reconfiguration of multivalent Cu foam. NO2 - is then transferred to the surface of Pd clusters by the cascade catalysis and accelerates the breaking of N─O bonds to form Pd─N, and eventually achieves the N≡N bond formation.

A US perspective on closing the carbon cycle to defossilize difficult-to-electrify segments of our economy

Electrification to reduce or eliminate greenhouse gas emissions is essential to mitigate climate change. However, a substantial portion of our manufacturing and transportation infrastructure will be difficult to electrify and/or will continue to use carbon as a key component, including areas in aviation, heavy-duty and marine transportation, and the chemical industry. In this Roadmap, we explore how multidisciplinary approaches will enable us to close the carbon cycle and create a circular economy by defossilizing these difficult-to-electrify areas and those that will continue to need carbon. We discuss two approaches for this: developing carbon alternatives and improving our ability to reuse carbon, enabled by separations. Furthermore, we posit that co-design and use-driven fundamental science are essential to reach aggressive greenhouse gas reduction targets.

Mn-Based Mullites for Environmental and Energy Applications

Mn-based mullite oxides AMn2O5 (A = lanthanide, Y, Bi) is a novel type of ternary catalyst in terms of their electronic and geometric structures. The coexistence of pyramid Mn3+-O and octahedral Mn4+-O makes the d-orbital selectively active toward various catalytic reactions. The alternative edge- and corner-sharing stacking configuration constructs the confined active sites and abundant active oxygen species. As a result, they tend to show superior catalytic behaviors and thus gain great attention in environmental treatment and energy conversion and storage. In environmental applications, Mn-based mullites have been demonstrated to be highly active toward low-temperature oxidization of CO, NO, volatile organic compounds (VOCs), etc. Recent research further shows that mullites decompose O3 and ozonize VOCs from -20 °C to room temperature. Moreover, mullites enhance oxygen reduction reactions (ORR) and sulfur reduction reactions (SRR), critical kinetic steps in air-battery and Li-S batteries, respectively. Their distinctive structures also facilitate applications in gas-sensitive sensing, ionic conduction, high mobility dielectrics, oxygen storage, piezoelectricity, dehydration, H2O2 decomposition, and beyond. A comprehensive review from basic physicochemical properties to application certainly not only gains a full picture of mullite oxides but also provides new insights into designing heterogeneous catalysts.

Key Ingredients for the Screening of Single Atom Catalysts for the Hydrogen Evolution Reaction: The Case of Titanium Nitride

A computational screening of Single Atom Catalysts (SACs) bound to titanium nitride (TiN) is presented, for the Hydrogen Evolution Reaction (HER), based on density functional theory. The role of fundamental ingredients is explored to account for a reliable screening of SACs. Namely, the formation of H2-complexes besides the classical H* one impacts the predicted HER activity, in line with previous studies on other SACs. Also, the results indicate that one needs to adopt self-interaction-corrected functionals. Finally, predicting an active catalyst is of little help without an assessment of its stability. Thus, it is included in the theoretical framework the analysis of the stability of the SACs in working conditions of pH and voltage. Once unconventional intermediates and stability are considered in a self-interaction corrected scheme, the number of potential good catalysts for HER is strongly reduced since i) some potentially good catalysts are not stable against dissolution and ii) the formation of unconventional intermediates leads to thermodynamic barriers. This study highlights the importance of including ingredients for the prediction of new systems, such as the formation of unconventional intermediates, estimating the stability of SACs, and the adoption of self-interaction corrected functionals. Also, this study highlights some interesting candidates deserving of dedicated work.

Effect of Intrinsic Ferroelectric Phase Transition on Hydrogen Evolution Electrocatalysis

Heterogeneous electrocatalysis closely relies on the electronic structure of the catalytic materials. The ferroelectric-to-paraelectric phase transition of the materials also involves a change in the state of electrons that could impact the electrocatalytic activity, but such correlation remains unexplored. Here, we demonstrate experimentally and theoretically that the intrinsic electrocatalytic activity could be regulated as exampled by hydrogen evolution reaction catalysis over two-dimensional ferroelectric CuInP2S6. The obvious discontinuity in the overpotential and apparent activation energy values for CuInP2S6 electrode are illustrated during the ferroelectric-to-paraelectric phase transition caused by copper displacement around Tc point (318 K), revealing the ferroelectro-catalytic effect on thermodynamics and kinetics of electrocatalysis. When loading Pt single atom on the CuInP2S6, the paraelectric phase one showed an improved hydrogen evolution activity with smaller apparent activation energy over the ferroelectric phase counterpart. This is attributed to the copper hopping between two sulfur planes, which alternate between strong and weak H adsorption at the Pt sites to simultaneously promote H+ reactant adsorption and H2 product desorption.

Demagnetizing Ferromagnetic Catalysts to the Sabatier Optimal of Haber-Bosch Process

Achieving the Sabatier optimal of a chemical reaction has been the central topic in heterogeneous catalysis for a century. However, this ultimate goal was greatly hindered in previous catalyst design strategies since the active sites indeed changed. Fortunately, the magneto-catalytic effect (MCE) provides a promising solution to this long-standing challenge. Recent research suggests that the performance of ferromagnetic catalysts is capable to be promoted without changing its chemical structure. Herein, we use time-dependent density functional perturbation theory (TDDFPT) calculations to elucidate that a partially demagnetized (DM) ferromagnet could be a Sabatier optimal catalyst. Using ammonia synthesis as the model reaction, we determined the activity of Cobalt at each DM state by including the magnetic thermal excitations via magnon analysis, making the 55% DM Co to the genuine Sabatier optimal. As an essential but underexcavated phenomenon in heterogeneous catalysis, the MCE will open a new avenue to design high-performance catalysts.

Research progress of dual-atom site catalysts for photocatalysis

Dual-atom site catalysts (DASCs) have sparked considerable interest in heterogeneous photocatalysis as they possess the advantages of excellent photoelectronic activity, photostability, and high carrier separation efficiency and mobility. The DASCs involved in these important photocatalytic processes, especially in the photocatalytic hydrogen evolution reaction (HER), CO2 reduction reaction (CO2RR), N2/nitrate reduction, etc., have been extensively investigated in the past few years. In this review, we highlight the recent progress in DASCs that provides fundamental insights into the photocatalytic conversion of small molecules. The controllable preparation and characterization methods of various DASCs are discussed. Subsequently, the reaction mechanisms of the formation of several important molecules (hydrogen, hydrocarbons and ammonia) on DASCs are introduced in detail, in order to probe the relationship between DASCs's structure and photocatalytic activity. Finally, some challenges and outlooks of DASCs in the photocatalytic conversion of small molecules are summarized and prospected. We hope that this review can provide guidance for in-depth understanding and aid in the design of efficient DASCs for photocatalysis.

Surface Charge Effects for the Hydrogen Evolution Reaction on Pt(111) Using a Modified Grand-Canonical Potential Kinetics Method

Surface charges of catalysts have important influences on the thermodynamics and kinetics of electrochemical reactions. Herein, we develop a modified version of the grand-canonical potential kinetics (GCP-K) method based on density functional theory (DFT) calculations to explore the effect of surface charges on reaction thermodynamics and kinetics. Using the hydrogen evolution reaction (HER) on the Pt(111) surface as an example, we show how to track the change of surface charge in a reaction and how to analyze its influence on the kinetics. Grand-canonical calculations demonstrate that the optimum hydrogen adsorption energy on Pt under the standard hydrogen electrode condition (SHE) is around -0.2 eV, rather than 0 eV established under the canonical ensemble, due to the high density of surface negative charges. By separating the surface charges that can freely exchange with the external electron reservoir, we obtain a Tafel barrier that is in good agreement with the experimental result. During the Tafel reaction, the net electron inflow into the catalyst leads to a stabilization of canonical energy and a destabilization of the charge-dependent grand-canonical component. This study provides a practical method for obtaining accurate grand-canonical reaction energetics and analyzing the surface charge induced changes.

Spontaneous Charge Separation at the Metal-Water Interface

Reactions at the metal-water interface are essential in a range of fundamental and technological processes. Using Density Functional Theory calculations, we demonstrate that water substantially affects the adsorption of H and O2 on Cu(111), Ag(111), Au(111), Pd(111) and Pt(111). In water, H is found to undergo a spontaneous charge separation, where a proton desorbs to the water solution while an electron is donated to the surface. The reaction is exothermic over Au and Pt and associated with low barriers. The process is facile also over Pd, albeit slightly endothermic. For O2, water is found to increase the metal-to-adsorbate charge transfer, enhancing the adsorption energy and O-O bond length as compared to the adsorption in the absence of water. The magnitudes of the effects are system dependent, which implies that calculations should treat water explicitly. The results elucidate previous experimental results and highlights the importance of charge-transfer effects at the metal-water interface; both to describe the potential energy landscape, and to account for alternative reaction routes in the presence of water.

Site-selective sulfur anchoring produces sintering-resistant intermetallic ORR electrocatalysts for membrane electrode assemblies

Intermetallic compounds are emerging as promising oxygen reduction reaction (ORR) catalysts for fuel cells due to their typically higher activity and durability compared to disordered alloys. However, the preparation of intermetallic catalysts often requires high-temperature annealing, which unfortunately leads to adverse sintering of the metal nanoparticles. Herein, we develop a scalable site-selective sulfur anchoring strategy that effectively suppresses alloy sintering, ensuring the formation of efficient intermetallic electrocatalysts with small sizes and high ordering degrees. The alloy-support interactions are precisely modulated by selectively modifying the alloy-support interfaces with oxidized sulfur species, thus simultaneously blocking both the nanoparticle migration and Oswald ripening pathways for sintering. Using this strategy, sub-5 nm PtCo intermetallic electrocatalysts enclosed by two atomic layers of Pt shells have been successfully prepared even at a metal loading higher than 30 wt%. The intermetallic catalysts exhibit excellent ORR performances in both rotating disk electrode and membrane electrode assembly conditions with a mass activity of 1.28 A mgPt-1 at 0.9 V (vs. RHE) and a power density of 1.0 W cm-2 at a current density of 1.5 A cm-2. The improved performances result from the enhanced Pt-Co electronic interactions and compressive surface strain generated by the highly ordering structure, while the atomic Pt shells prevent the dissolution of Co under highly acidic conditions. This work provides new insights to inhibit the sintering of nanoalloys and would promote the scalable synthesis and applications of platinum-based intermetallic catalysts.

Reversible Hydrogen Electrode (RHE) Scale Dependent Surface Pourbaix Diagram at Different pH

In the analysis of electrocatalysis mechanisms and the design of catalysts, the effect of electrochemistry-induced surface coverage is a critical consideration that should not be overlooked. The surface Pourbaix diagram emerges as a fundamental tool in this context, providing essential insights into the surface coverage of adsorbates generated via electrochemical potential-driven water activation. A classic surface Pourbaix diagram considers the pH effects by correcting the free energy of H+ ions by the concentration-dependent term: -kBT ln(10) × pH, which is independent of the reversible hydrogen electrode (RHE) scale. However, this is sometimes inconsistent with the experimentally observed potential-dependent surface coverage at an RHE scale, especially under high-pH conditions. Here, we derived the pH-dependent surface Pourbaix diagram at an RHE scale by considering the energetics computed by density functional theory with the Bayesian Error Estimation Functional with van der Waals corrections (BEEF-vdW), the electric field effects, the derived adsorption-induced dipole moment and polarizability, and the potential of zero-charge. Using Pt(111) as the typical example, we found that the surface coverage predicted by the proposed RHE-dependent surface Pourbaix diagram can significantly minimize the discrepancy between theory and experimental observations, especially under neutral-alkaline, moderate-potential conditions. This work provides a new methodology and establishes guidelines for the precise analysis of the surface coverage prior to the evaluation of the activity of an electrocatalyst.

Design Strategies towards Advanced Hydrogen Evolution Reaction Electrocatalysts at Large Current Densities

Hydrogen (H2), produced by water electrolysis with the electricity from renewable sources, is an ideal energy carrier for achieving a carbon-neutral and sustainable society. Hydrogen evolution reaction (HER) is the cathodic half-reaction of water electrolysis, which requires active and robust electrocatalysts to reduce the energy consumption for H2 generation. Despite numerous electrocatalysts have been reported by the academia for HER, most of them were only tested under relatively small current densities for a short period, which cannot meet the requirements for industrial water electrolysis. To bridge the gap between academia and industry, it is crucial to develop highly active HER electrocatalysts which can operate at large current densities for a long time. In this review, the mechanisms of HER in acidic and alkaline electrolytes are firstly introduced. Then, design strategies towards high-performance large-current-density HER electrocatalysts from five aspects including number of active sites, intrinsic activity of each site, charge transfer, mass transfer, and stability are discussed via featured examples. Finally, our own insights about the challenges and future opportunities in this emerging field are presented.

CO2 electroreduction on single atom catalysts: the role of the DFT functional

One key process involving single atom catalysts (SACs) is the electroreduction of CO2 to fuels. The chemistry of SACs differs largely from that of extended catalytic surfaces, presenting an opportunity to improve the ability to activate very stable molecules, such as CO2. In this work, we performed a density functional theory (DFT) study of CO2 activation on a series of SACs, focusing on the role played by the adopted functional in activity predictions. The role of the exchange-correlation functional has been widely investigated in heterogenous catalysts, but it is less explored in SACs. We tested the widely used PBE and the PBE+U corrected functionals against the more robust hybrid PBE0 functional. The results show that PBE is reliable if one is interested in qualitative predictions, but it leads to some inaccuracies in other cases. A possible way to attenuate this effect is by adopting the PBE+U framework, as it gives results that are very similar to PBE0 at an acceptable computational cost. The results of this study further underline the importance of the computational framework adopted in predicting the activity of SACs. The work suggests that one needs to go beyond PBE for quantitative estimates, an important consideration when performing screening and high-throughput calculations.

Sub-10-nm-sized Au@AuxIr1-x metal-core/alloy-shell nanoparticles as highly durable catalysts for acidic water splitting

The absence of efficient and durable catalysts for oxygen evolution reaction (OER) is the main obstacle to hydrogen production through water splitting in an acidic electrolyte. Here, we report a controllable synthesis method of surface IrOx with changing Au/Ir compositions by constructing a range of sub-10-nm-sized core-shell nanocatalysts composed of an Au core and AuxIr1-x alloy shell. In particular, Au@Au0.43Ir0.57 exhibits 4.5 times higher intrinsic OER activity than that of the commercial Ir/C. Synchrotron X-ray-based spectroscopies, electron microscopy and density functional theory calculations revealed a balanced binding of reaction intermediates with enhanced activity. The water-splitting cell using a load of 0.02 mgIr/cm2 of Au@Au0.43Ir0.57 as both anode and cathode can reach 10 mA/cm2 at 1.52 V and maintain activity for at least 194 h, which is better than the cell using the commercial couple Ir/C‖Pt/C (1.63 V, 0.2 h).

Unsupervised machine learning reveals eigen reactivity of metal surfaces

The reactivity of metal surfaces is a cornerstone concept in chemistry, as metals have long been used as catalysts to accelerate chemical reactions. Although fundamentally important, the reactivity of metal surfaces has hitherto not been explicitly defined. For example, in order to compare the activity of two metal surfaces, a particular probe adsorbate, such as O, H, or CO, has to be specified, as comparisons may vary from probe to probe. Here we report that the metal surfaces actually have their own intrinsic/eigen reactivity, independent of any probe adsorbate. By employing unsupervised machine learning algorithms, specifically, principal component analysis (PCA), two dominant eigenvectors emerged from the binding strength dataset formed by 10 commonly used probes on 48 typical metal surfaces. According to their chemical characteristics revealed by vector decomposition, these two eigenvectors can be defined as the covalent reactivity and the ionic reactivity, respectively. Whereas the ionic reactivity turns out to be related to the work function of the metal surface, the covalent reactivity cannot be indexed by simple physical properties, but appears to be roughly connected with the valence-electron number normalized density of states at the Fermi level. Our findings expose that the metal surface reactivity is essentially a two-dimensional vector rather than a scalar, opening new horizons for understanding interactions at the metal surface.

Structured Catalysts and Catalytic Processes: Transport and Reaction Perspectives

The structure of catalysts determines the performance of catalytic processes. Intrinsically, the electronic and geometric structures influence the interaction between active species and the surface of the catalyst, which subsequently regulates the adsorption, reaction, and desorption behaviors. In recent decades, the development of catalysts with complex structures, including bulk, interfacial, encapsulated, and atomically dispersed structures, can potentially affect the electronic and geometric structures of catalysts and lead to further control of the transport and reaction of molecules. This review describes comprehensive understandings on the influence of electronic and geometric properties and complex catalyst structures on the performance of relevant heterogeneous catalytic processes, especially for the transport and reaction over structured catalysts for the conversions of light alkanes and small molecules. The recent research progress of the electronic and geometric properties over the active sites, specifically for theoretical descriptors developed in the recent decades, is discussed at the atomic level. The designs and properties of catalysts with specific structures are summarized. The transport phenomena and reactions over structured catalysts for the conversions of light alkanes and small molecules are analyzed. At the end of this review, we present our perspectives on the challenges for the further development of structured catalysts and heterogeneous catalytic processes.