Search NASA⌕ Search

SEARCH · Search NASA

Results for “barrier function”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Modeling fission dynamics at the barrier in a discrete-basis formalism

A configuration-interaction model is presented for the barrier region of induced fission. The configuration space is composed of seniority-zero configurations constructed from self-consistent mean-field wave functions. The Hamiltonian matrix elements between configurations include diabatic and pairing interactions between particles. Other aspects of the Hamiltonian are treated statistically, guided by phenomenological input of compound-nucleus transmission coefficients. In this exploratory study the configuration space is restricted to neutron excitations only. A key observable calculated in the model is the fission-to-capture branching ratio. We find that both pairing and diabatic interactions are important for achieving large branching to the fission channels. In accordance with the transition-state theory of fission, the calculated branching ratio is found to be quite insensitive to the fission decay widths of the pre-scission configurations. Furthermore, the barrier-top dynamics appear to be quite different from transition-state theory in that the transport is distributed over many excited configurations at the barrier top.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Adsorption of ethylenediamine on Cu surfaces: attributes of a successful capping molecule using first-principles calculations

The shape-controlled synthesis of Cu nanocrystals can benefit a wide range of applications, though challenges exist in achieving high and selective yields to a particular shape. Capping agents play a pivotal role in controlling shape, but their exact role remains ambiguous. In this study, the adsorption of ethylenediamine (EDA) on Cu(100) and Cu(111) was investigated with quantum density functional theory (DFT) to reveal the complex roles of EDA in promoting penta-twinned Cu nanowire growth. We find EDA has stronger binding on Cu(100) than on Cu(111), which agrees the general expectation that penta-twinned Cu nanowires express facets with stronger capping-molecule binding. Despite this stronger binding, ab initio thermodynamics reveals the surface energy of EDA-covered Cu(111) is lower than that EDA-covered Cu(100) at all solution-phase EDA chemical potentials, so there is no thermodynamic driving force for penta-twinned nanowires. We also investigated the capability of EDA to protect Cu surfaces from oxidation in water by quantifying energy barriers for a water molecule to diffuse through EDA layers on Cu(100) and Cu(111). The energy barrier on Cu(100) is significantly lower, which supports observations of faster oxidation of Cu(100) in electrochemical experiments. Thus, we elucidate another possible function of a capping agent – to enable selective oxidation of crystal facets. This finding adds to the general understanding of successful attributes of capping agents for shape-selective nanocrystal growth.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Grain Boundary‐Derived Cu + /Cu 0 Interfaces in CuO Nanosheets for Low Overpotential Carbon Dioxide Electroreduction to Ethylene

Abstract Electrochemical CO 2 reduction reaction can be used to produce value‐added hydrocarbon fuels and chemicals by coupling with clean electrical energy. However, highly active, selective, and energy‐efficient CO 2 conversion to multicarbon hydrocarbons, such as C 2 H 4 , remains challenging because of the lack of efficient catalysts. Herein, an ultrasonication‐assisted electrodeposition strategy to synthesize CuO nanosheets for low‐overpotential CO 2 electroreduction to C 2 H 4 is reported. A high C 2 H 4 Faradaic efficiency of 62.5% is achieved over the CuO nanosheets at a small potential of −0.52 V versus a reversible hydrogen electrode, corresponding to a record high half‐cell cathodic energy efficiency of 41%. The selectivity toward C 2 H 4 is maintained for over 60 h of continuous operation. The CuO nanosheets are prone to in situ restructuring during CO 2 reduction, forming abundant grain boundaries (GBs). Stable Cu + /Cu 0 interfaces are derived from the low‐coordinated Cu atoms in the reconstructed GB regions and act as highly active sites for CO 2 reduction at low overpotentials. In situ Raman spectroscopic analysis and density functional theory computation reveal that the Cu + /Cu 0 interfaces offer high *CO surface coverage and lower the activation energy barrier for *CO dimerization, which, in synergy, facilitates CO 2 reduction to C 2 H 4 at low overpotentials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Transient kinetic insights into selective propene oxidation over industrial bismuth molybdate catalysts

Selective oxidation of propene to acrolein over industrial multicomponent bismuth molybdate (BMO) catalysts significantly depends on reaction conditions that include operating parameters and catalyst state. Here, this work investigates selective propene oxidation in the intrinsic kinetic paradigm of Temporal Analysis of Products (TAP) reactor by systematically varying catalyst redox state, temperature, and oxygen-to-propene feed ratio. A 93 % propene conversion with an acrolein yield of 80 % is achieved at elevated temperatures (450 °C) on oxidized catalysts under oxygen-rich conditions (O 2 :C 3 H 6 = 10). However, these conditions diminish acrolein-to-CO 2 selectivity due to enhanced total oxidation to CO 2 . In contrast, a reduced catalyst state, moderate temperature (350 °C), and lower oxygen feed (O 2 :C 3 H 6 = 1) nearly doubles the acrolein to-CO 2 selectivity, albeit at a lower acrolein yield (33 %). Transient kinetic studies together with a kinetic model that simplify the major product formation pathways in lumped non-elementary forms reveal that the availability of surface oxygen species plays a pivotal role in governing reaction pathways. Additionally, density functional theory (DFT) calculations on pure BMO catalysts inform the role of surface redox states on propene and oxygen activation barriers. Lattice oxygen at acrolein-selective sites drives both acrolein and CO 2 formation, while adsorbed oxygen at activation sites favors unselective CO 2 generation. This work establishes a critical relationship between transient product selectivity and surface oxygen availability, which is strongly influenced by catalyst redox state, feed ratio, and reaction temperature. These insights underscore the importance of dynamic reactor operation strategies and offer a foundation for designing next-generation propene oxidation processes with tunable acrolein selectivity.

42 - ENGINEERING↗
DOE OSTI2025

Defect Diffusion Graph Neural Networks for Materials Discovery in High-Temperature Energy Applications

Here, the migration of crystallographic defects dictates material properties and performance for a plethora of technological applications. Density functional theory (DFT)-based nudged elastic band (NEB) calculations are a powerful computational technique for predicting defect migration activation energy barriers, yet they become prohibitively expensive for high-throughput screening of defect diffusivities. Without introducing hand-crafted (i.e., chemistry- or structure-specific) descriptors, we propose a generalized deep learning approach to train surrogate models for NEB energies of vacancy migration by hybridizing graph neural networks with transformer encoders and simply using pristine host structures as input. With sufficient training data, computationally efficient and simultaneous inference of vacancy defect thermodynamics and migration activation energies can be obtained to compute temperature-dependent vacancy diffusivities and to down-select candidates for more thorough DFT analysis or experiments. Thus, as we specifically demonstrate for potential water-splitting materials, candidates with desired defect thermodynamics, kinetics, and host stability properties can be more rapidly targeted from open-source databases of experimentally validated or hypothetical materials.

14 SOLAR ENERGY↗
DOE OSTI2020

Density Functional Theory Investigation of Oxidation Intermediates on Gold and Gold–Silver Surfaces

Gold and gold-silver alloys can be active and selective oxidation catalysts. Previous work has suggested that O 2 dissociation occurs at bimetallic step sites on gold-silver alloys, but the site responsible for the rest of the reaction steps has not been studied. As a first step in gaining insight into this issue, in this work we investigated the adsorption of oxygen and other oxidation intermediates on the (111) and (211) facets of gold-silver alloys using density functional theory. Oxygen and silver coverage effects were analyzed, and different model structures were compared. We also examined the energy barriers for the diffusion of atomic oxygen to gain insight into O migration and spillover. On (111) surfaces, O adsorption is much stronger at low O coverage (less than 0.22 ML), while on (211) surfaces O is strongly bound at both high and low O coverage. O diffusion across the step is faster than diffusion along the step. Ag stabilizes O, both when directly bound to it and when in an adjacent site. Ag also reduces repulsive O-O interactions at low O coverage. Our calculated reaction barriers for O-assisted CH 3 O dehydrogenation suggest that reaction is faster on steps than on terraces. Overall, our findings suggest that spillover of O from Ag-rich steps to Au-rich terraces does not occur, and that oxidation reactions on gold-silver alloys occurs on step sites. More specifically, oxidation likely occurs either on Ag-rich step sites or on Au-rich step sites that are adjacent to Ag-rich step sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Phylogenetic distribution and experimental characterization of corrinoid production and dependence in soil bacterial isolates

Abstract Soil microbial communities impact carbon sequestration and release, biogeochemical cycling, and agricultural yields. These global effects rely on metabolic interactions that modulate community composition and function. However, the physicochemical and taxonomic complexity of soil and the scarcity of available isolates for phenotypic testing are significant barriers to studying soil microbial interactions. Corrinoids—the vitamin B12 family of cofactors—are critical for microbial metabolism, yet they are synthesized by only a subset of microbiome members. Here, we evaluated corrinoid production and dependence in soil bacteria as a model to investigate the ecological roles of microorganisms involved in metabolic interactions. We isolated and characterized a taxonomically diverse collection of 161 soil bacteria from a single study site. Most corrinoid-dependent bacteria in the collection prefer B12 over other corrinoids, while all tested producers synthesize B12, indicating metabolic compatibility between producers and dependents in the collection. Furthermore, a subset of producers release B12 at levels sufficient to support dependent isolates in laboratory culture at estimated ratios of up to 1000 dependents per producer. Within our isolate collection, we did not find strong phylogenetic patterns in corrinoid production or dependence. Upon investigating trends in the phylogenetic dispersion of corrinoid metabolism categories across sequenced bacteria from various environments, we found that these traits are conserved in 47 out of 85 genera. Together, these phenotypic and genomic results provide evidence for corrinoid-based metabolic interactions among bacteria and provide a framework for the study of nutrient-sharing ecological interactions in microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Exploring Li-Ion Transport Properties of Li 3 TiCl 6 : A Machine Learning Molecular Dynamics Study

We performed large-scale molecular dynamics simulations based on a machine-learning force field (MLFF) to investigate the Li-ion transport mechanism in cation-disordered Li 3 TiCl 6 cathode at six different temperatures, ranging from 25°C to 100°C. In this work, deep neural network method and data generated by ab − initio molecular dynamics (AIMD) simulations were deployed to build a high-fidelity MLFF. Radial distribution functions, Li-ion mean square displacements (MSD), diffusion coefficients, ionic conductivity, activation energy, and crystallographic direction-dependent migration barriers were calculated and compared with corresponding AIMD and experimental data to benchmark the accuracy of the MLFF. From MSD analysis, we captured both the self and distinct parts of Li-ion dynamics. The latter reveals that the Li-ions are involved in anti-correlation motion that was rarely reported for solid-state materials. Similarly, the self and distinct parts of Li-ion dynamics were used to determine Haven’s ratio to describe the Li-ion transport mechanism in Li 3 TiCl 6 . Obtained trajectory from molecular dynamics infers that the Li-ion transportation is mainly through interstitial hopping which was confirmed by intra- and inter-layer Li-ion displacement with respect to simulation time. Ionic conductivity (1.06 mS/cm) and activation energy (0.29eV) calculated by our simulation are highly comparable with that of experimental values. Overall, the combination of machine-learning methods and AIMD simulations explains the intricate electrochemical properties of the Li 3 TiCl 6 cathode with remarkably reduced computational time. Thus, our work strongly suggests that the deep neural network-based MLFF could be a promising method for large-scale complex materials.

Selvaraj, Selva Chandrasekaran (ORCID:000000029023↗
DOE OSTI2024

Overview of Quantum Sensing Materials and Techniques for Energy Sector Applications

The energy sector is dependent upon highly sensitive sensing devices for a wide range of applications. Variables such as temperature, pH, electromagnetic fields, and pressure must be measured with high precision, often in harsh conditions (e.g. high temperature, pressure and humidity). These sensors are deployed in infrastructure such as transformers, pipelines, mines, nuclear power plants, and other areas to ensure safe operating conditions and uninterrupted, optimized service. Moreover, new opportunities for sensors have emerged due to the expansion of smart grids/meters, driverless vehicles, and the discovery of new oil/gas deposits. The continued maturation of quantum sensors offers exciting opportunities for quantum-enhanced measurements to improve sensitivity beyond the classical limit. Here, an overview of established and emerging quantum materials and methods for sensing applications will be provided. Opportunities within the energy sector for quantum sensors will then be analyzed, including oil/gas discovery, greenhouse gas emission monitoring, pH and ion sensing, current measurements, and quantum-enhanced spectroscopy, along with barriers such as quantum sensor platform miniaturization and ruggedization. A specific project at the National Energy Technology Laboratory involving the functionalization of qubits using metal-organic frameworks for enhanced quantum sensing will then be highlighted. Here, nitrogen vacancy centers (NV) in nanodiamonds, a commercially available qubit with long coherence times and utilizable quantum properties at room temperature, are encapsulated using the metal-organic framework ZIF-8. Significantly, the ZIF-8 coating increases the longitudinal spin relaxation lifetime of the NV centers, an important parameter for spin relaxometry-based quantum sensing experiments. These results demonstrate the importance of qubit functionalization as a crucial step for rationally designing high performance quantum sensors.

Crawford, Scott↗
DOE OSTI2020

Fullerene Negative Ions: Formation and Catalysis

We first explore negative-ion formation in fullerenes C 44 to C 136 through low-energy electron elastic scattering total cross sections calculations using our Regge-pole methodology. Then, the formed negative ions C 44 – to C 136 – are used to investigate the catalysis of water oxidation to peroxide and water synthesis from H 2 and O 2 . The exploited fundamental mechanism underlying negative-ion catalysis involves hydrogen bond strength-weakening/breaking in the transition state. Density Functional Theory transition state calculations found C 60 – optimal for both water and peroxide synthesis, C 100 – increases the energy barrier the most, and C 136 – the most effective catalyst in both water synthesis and oxidation to H 2 O 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Lithium Metal Electrode — Understanding Its Unique Characteristics and Functions

Lithium metal electrode (LME) is attractive for the next generation of commercial high-energy rechargeable lithium battery (RLB) design and development. As a light element with a very reducing electrochemical potential, Li metal certainly has the unique characteristics that also present challenges for its application in RLBs. To overcome technical barriers with LME such as the dendrite formation that causes uneven current distributions, excessive SEI formation that consumes Li inventory, and formation of inactive Li metal in granular forms that induces safety hazards, more fundamental understanding of the unique characteristics of LME and its impact on functions in performance in RLBs is critical. Here, we present some recent work based on temporally-correlated reactive molecular dynamics simulations to understand the Li deposition and the associated nucleation and growth process on the LME or graphitic electrode surfaces. Such a study provides some intriguing perspectives on how Li reacts with electrolytes on LME and conventional graphitic electrodes in the RLB operation. Such an insight could help improving our strategy to deal with LME problems and provide functional improvements for LME’s application in RLBs. This presentation is dedicated to Professor Robert Huggins for his life-long teaching of the fundamentals on solid state ionics and its implications in understanding the electrochemical behavior of Li in RLB applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Hydrodechlorination of 1,2-Dichloroethane on Platinum Catalysts: Insights from Reaction Kinetics Experiments, Density Functional Theory, and Microkinetic Modeling

Catalytic hydrodechlorination is a promising strategy for treating industrial 1,2-dichloroethane wastes, for which Pt and Pt-based alloy catalysts are widely used. Here, we performed a detailed mechanistic study for 1,2-dichloroethane hydrodechlorination on Pt using a synergistic approach combining density functional theory (DFT) calculations, reaction kinetics experiments, and microkinetic modeling. Using planewave DFT calculations, we evaluated the reaction energy and activation energy barrier of each elementary step involved in the reaction network on Pt(111). The calculated energetics were then incorporated into a comprehensive mean-field microkinetic model accounting for a total of 65 elementary steps. The model-predicted reaction rates were compared with the results from our reaction kinetics experiments on SiO2-supported Pt catalysts. Our results indicated that the hydrodechlorination of 1,2-dichloroethane on Pt(111) starts with a H-removal step; then, it proceeds through a sequence of alternating dechlorination and dehydrogenation steps until vinylidene (CH 2 C*) is formed; finally, CH 2 C* is hydrogenated to the final product, ethane, sequentially via vinyl (CH 2 CH*), ethylene, and ethyl (CH 3 CH 2 *) intermediates. After model parameter adjustments, we achieved good agreement between our theoretical model and experimental results; the adjustments to the calculated parameters are consistent with the typically anticipated coverage effects. Furthermore, our study offers valuable mechanistic insights, which are useful for improving catalysts for this chemistry.

1,2-dichloroethane↗
DOE OSTI2025

ReaxFF Parameter Set for Boron Clusters and Icosahedral Boron Crystals: Comparison with Density Functional Theory and Machine-Learning Potentials

Icosahedral boron materials, which include regular icosahedra of 12 boron atoms have gained increasing attention due to their potential applications as superhard materials, semiconductors, and energy storage media. However, the synthesis of high quality crystals of these materials has been a major barrier to the development of these applications. To enable computational prediction of synthesis conditions yielding high-quality icosahedral boron crystals, herein we tested and refined a set of ReaxFF parameters for the nucleation and growth of such crystals. We focused on matching the relative energies of small boron clusters obtained by density functional theory since such small clusters and similar motifs are likely present in crystal nuclei and at the interface of growing crystals. Using a training set of B 80 clusters, including a low-energy core–shell structure containing a B 12 icosahedron core and a high-energy single-shell structure produced in preliminary ReaxFF simulations, the ReaxFF parameter set was refined to better reproduce energies calculated by density functional theory (DFT). Among existing ReaxFF parameter sets and the machine-learning interatomic potentials MACE-MP-0, MACE-MP-0b3, MACE-MPA-0, PFP v7.0.0, and SevenNet-MF-ompa, only our new parameter set and PFP v7.0.0 correctly ranked these B 80 clusters. This refinement led to improved agreement with DFT for a test set of 58 clusters consisting of 8–103 boron atoms. Furthermore, our refined parameter set yielded greater local icosahedral structure than the previously existing ReaxFF parameter set for larger scale simulations of crystallization from supercooled liquid boron. Additionally, simulations of solid boron in contact with molten nickel using our refined ReaxFF parameters yielded a boron solubility value that agrees moderately well with experimental expectations, while the previous boron parameters gave a value that was much too low.

boron↗
DOE OSTI2020

A Novel NASICON‐Type Na 4 MnCr(PO 4 ) 3 Demonstrating the Energy Density Record of Phosphate Cathodes for Sodium‐Ion Batteries

Abstract Sodium‐ion batteries (SIBs) have attracted incremental attention as a promising candidate for grid‐scale energy‐storage applications. To meet practical requirements, searching for new cathode materials with high energy density is of great importance. Herein, a novel Na superionic conductor (NASICON)‐type Na 4 MnCr(PO 4 ) 3 is developed as a high‐energy cathode for SIBs. The Na 4 MnCr(PO 4 ) 3 nanoparticles homogeneously embedded in a carbon matrix can present an extraordinary reversible capacity of 160.5 mA h g −1 with three‐electron reaction at ≈3.53 V during the Na + extraction/insertion process, realizing an unprecedentedly high energy density of 566.5 Wh kg −1 in the phosphate cathodes for SIBs. It is intriguing to reveal the underlying mechanism of the unique Mn 2+ /Mn 3+ , Mn 3+ /Mn 4+ , and Cr 3+ /Cr 4+ redox couples via X‐ray absorption near‐edge structure spectroscopy. The whole electrochemical reaction undergoes highly reversible single‐phase and biphasic transitions with a moderate volume change of 7.7% through in situ X‐ray diffraction and ex situ high‐energy synchrotron X‐ray diffraction. Combining density functional theory (DFT) calculations with the galvanostatic intermittent titration technique, the superior performance is ascribed to the low ionic‐migration energy barrier and desirable Na‐ion diffusion kinetics. The present work can offer a new insight into the design of multielectron‐reaction cathode materials for SIBs.

Zhang, Jian↗
DOE OSTI2025

UnigeneFinder: An Automated Pipeline for Gene Calling From Transcriptome Assemblies Without a Reference Genome

ABSTRACT For most species, transcriptome data are much more readily available than genome data. Without a reference genome, gene calling is cumbersome and inaccurate because of the high degree of redundancy in de novo transcriptome assemblies. To simplify and increase the accuracy of de novo transcriptome assembly in the absence of a reference genome, we developed UnigeneFinder. Combining several clustering methods, UnigeneFinder substantially reduces the redundancy typical of raw transcriptome assemblies. This pipeline offers an effective solution to the problem of inflated transcript numbers, achieving a closer representation of the actual underlying genome. UnigeneFinder performs comparably or better, compared with existing tools, on plant species with varying genome complexities. UnigeneFinder is the only available transcriptome redundancy solution that fully automates the generation of primary transcript, coding region, and protein sequences, analogous to those available for high‐quality reference genomes. These features, coupled with the pipeline’s cross‐platform implementation, focus on automation, and an accessible, user‐friendly interface, make UnigeneFinder a useful tool for many downstream sequence‐based analyses in nonmodel organisms lacking a reference genome, including differential gene expression analysis, accurate ortholog identification, functional enrichments, and evolutionary analyses. UnigeneFinder also runs efficiently both on high‐performance computing (HPC) systems and personal computers, further reducing barriers to use.

Xue, Bo [Plant Resilience Institute Michigan State↗
DOE OSTI2025

Quantum Simulation of Molecular Dynamics Processes─A Benchmark Study Using a Classical Simulator and Present-Day Quantum Hardware

Here, we explore how the fundamental problems in quantum molecular dynamics can be modeled using classical simulators (emulators) of quantum computers and the actual quantum hardware available to us today. The list of problems we tackle includes propagation of a free wave packet, vibration of a harmonic oscillator, and tunneling through a barrier. Each of these problems starts with the initial wave packet setup. Although Qiskit provides a general method for initializing wave functions, in most cases it generates deep quantum circuits. While these circuits perform well on noiseless simulators, they suffer from excessive noise on quantum hardware. To overcome this issue, we designed a shallower quantum circuit for preparing a Gaussian-like initial wave packet, which improves the performance of real hardware. Next, quantum circuits are implemented to apply the kinetic and potential energy operators for the evolution of a wave function over time. The results of our modeling on classical emulators of quantum hardware agree perfectly with the results obtained using the traditional (classical) methods. This serves as a benchmark and demonstrates that the quantum algorithms and Qiskit codes we developed are accurate. However, the results obtained on the actual quantum hardware available today, such as IBM’s superconducting qubits and IonQ’s trapped ions, indicate large discrepancies due to hardware limitations. This work highlights both the potential and challenges of using quantum computers to solve fundamental quantum molecular dynamics problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Tunneling current modulation in atomically precise graphene nanoribbon heterojunctions

Lateral heterojunctions of atomically precise graphene nanoribbons (GNRs) hold promise for applications in nanotechnology, yet their charge transport and most of the spectroscopic properties have not been investigated. Here, we synthesize a monolayer of multiple aligned heterojunctions consisting of quasi-metallic and wide-bandgap GNRs, and report characterization by scanning tunneling microscopy, angle-resolved photoemission, Raman spectroscopy, and charge transport. Comprehensive transport measurements as a function of bias and gate voltages, channel length, and temperature reveal that charge transport is dictated by tunneling through the potential barriers formed by wide-bandgap GNR segments. The current-voltage characteristics are in agreement with calculations of tunneling conductance through asymmetric barriers. We fabricate a GNR heterojunctions based sensor and demonstrate greatly improved sensitivity to adsorbates compared to graphene based sensors. This is achieved via modulation of the GNR heterojunction tunneling barriers by adsorbates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Single-atom Rh/N-doped carbon electrocatalyst for formic acid oxidation

To meet the requirements of potential applications, it is of great importance to explore new catalysts for formic acid oxidation that have both ultra-high mass activity and CO resistance. In this work, we successfully synthesize atomically dispersed Rh on N-doped carbon (SA-Rh/CN) and discover that SA-Rh/CN exhibits promising electrocatalytic properties for formic acid oxidation. The mass activity shows 28- and 67-fold enhancements compared with state-of-the-art Pd/C and Pt/C, respectively, despite the low activity of Rh/C. Interestingly, SA-Rh/CN exhibits greatly enhanced tolerance to CO poisoning, and Rh atoms in SA-Rh/CN resist sintering after long-term testing, resulting in excellent catalytic stability. Density functional theory calculations suggest that the formate route is more favourable on SA-Rh/CN. According to calculations, the high barrier to produce CO, together with the relatively unfavourable binding with CO, contribute to its CO tolerance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗