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DOE OSTI2023

Can a deep-learning model make fast predictions of vacancy formation in diverse materials?

The presence of point defects, such as vacancies, plays an important role in materials design. Here, we explore the extrapolative power of a graph neural network (GNN) to predict vacancy formation energies. We show that a model trained only on perfect materials can also be used to predict vacancy formation energies (E vac ) of defect structures without the need for additional training data. Such GNN-based predictions are considerably faster than density functional theory (DFT) calculations and show potential as a quick pre-screening tool for defect systems. To test this strategy, we developed a DFT dataset of 530 E vac consisting of 3D elemental solids, alloys, oxides, semiconductors, and 2D monolayer materials. We analyzed and discussed the applicability of such direct and fast predictions. We applied the model to predict 192 494 E vac for 55 723 materials in the JARVIS-DFT database. Our work demonstrates how a GNN-model performs on unseen data.

2D materials↗

DOE OSTI2021

Kohn-Sham Solver (KSSOLV) v2.0

KSSOLV is a MATLAB toolbox for solving Kohn-Sham density functional theory based electronic structure eigenvalue problems. It uses an object oriented features of MATLAB to represent atom, molecules, wavefunctions and Hamiltonians and their operations. It is designed to make it easier for users to prototype and test new algorithms for solving the Kohn-Sham problem. KSSOLV2.0 contains significant improvement over the original KSSOLV described in a paper published in ACM Transaction on Mathematical Software (attached). In addition to performing ground state calculation for small molecules, it can also perform geometry optimization for both molecules and solids. It uses standard pseudopotentials and implements local density approximation, generalized gradient approximation and hybrid functionals. Future releases will also include time-dependent DFT and post DFT calculations such as the GW quasi-particle energy calculation and Bethe-Salpeter equation solver for optical absorption.

Yang, Chao↗

DOE OSTI2025

Solar Decarbonization of Paraffin Dehydrogenation Through Particle Heat Carriers (Final Technical Report)

This project focuses on solutions to decarbonize high-temperature catalytic processes using solar thermal heat. The primary project goal is to show the validity of a moving packed bed reactor for propane dehydrogenation using catalyst particles as the heat carrier for the reaction, which can be heated by concentrated solar energy in a particle receiver. This concept, if further developed, may provide a cost-effective pathway for converting lower value gases to important chemical precursors for industrial materials using only renewable energy. The project was divided into six tasks. In Task 1, DFT calculations were performed to understand the role of Pt and Sn in the catalytic dehydrogenation reaction. In Task 2 chemical kinetics measurements were made for several catalyst formulations at high temperatures. In Task 3, the solar absorptance of catalyst particles was compared to the absorptance of commonly used materials in particle receivers. In Task 4, numerical models were developed which could predict performance of the complete system and predict specific temperatures in the system. In Task 5, a prototype system was designed, fabricated, and tested to show the validity of the concept. Task 6 concerned project management activities. Experiments with the prototype showed repeatable thermal performance at temperatures targeted for the reaction. A limited set of tests were done with active catalyst and propane dehydrogenation, showing conversion of propane to propylene with a range of conversions and selectivities. The results are promising, and the prototype designed was reliable during testing, and the team expects that further development of the prototype would yield improved results. A numerical model framework based on coupled fluid and particle mechanics was developed with high computational efficiency using GPU calculations. The model may prove highly useful for evaluating other high-temperature particle systems. However, it was determined that simpler porous media models were good fits for the needs of the current moving packed bed concept. Data showing strong solar absorption of the particles validates the plan of using existing solar particle receivers with only a change in the particle type. Catalyst investigation showed that Pt 1 Sn 3 is the most viable candidate for developing PtSn catalysts for high temperature propane dehydrogenation, considering the balance of activity, selectivity, and deactivation. This project completed an initial study of various factors needed to incorporate a moving bed catalytic reactor for propane dehydrogenation into a concentrated solar thermal particle system. Future developments may allow this technology to be scaled up and help to use solar thermal energy to decarbonize not only the propane dehydrogenation reaction, but other gas-solid catalytic reactions at similar temperatures.

14 SOLAR ENERGY↗

DOE OSTI2020

Molecular Recognition at Mineral Interfaces: Implications for the Beneficiation of Rare Earth Ores

Ce-bastnäsite is the single largest mineral source for light rare-earth elements. In view of the growing industrial importance of rare-earth minerals, it is critical to develop more efficient methods for separating the valuable rare-earth-containing minerals from the surrounding gangue. In this work, we employ a combination of periodic density functional theory (DFT) and molecular mechanics (MM) calculations together with the de novo molecular design program HostDesigner to identify bis-phosphinate ligands that preferentially bind to the (100) Ce-bastnäsite surface rather than the (104) calcite surface. DFT calculations for a simple phosphinate ligand were employed to qualitatively understand key behaviors involved in ligand–metal, ligand–solvent, and solvent–metal interactions. These insights were then used to guide the search for flexible, rigid, and semirigid hydrocarbon linkers to identify candidate bis-phosphinate ligands with the potential to bind preferentially to Ce-bastnäsite. Among the five most promising bis-phosphinate ligands suggested by theoretical studies, three ligands were synthesized and their adsorption characteristics to bastnäsite (100) interfaces were characterized using vibrational sum-frequency (vSFG) spectroscopy, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, and isothermal titration calorimetry (ITC). The efficacy of the selective interfacial molecular binding was demonstrated by identifying a bis-phosphinate ligand capable of providing an overall higher surface coverage of alkyl groups relative to a monophosphinate ligand. The results highlight the interplay between adsorption binding strength and maximum surface coverage in determining ligand efficiency to render the mineral surface hydrophobic. DFT calculations further indicate that all tested ligands have higher affinity for Ce-bastnäsite than for calcite. Finally, this is consistent with the ITC data showing stronger adsorption enthalpy to bastnäsite than to calcite, making these ligands promising candidates for selective flotation of Ce-bastnäsite.

58 GEOSCIENCES↗

DOE OSTI2022

Design of a Scavenging Pyrrole Additive for High Voltage Lithium-Ion Batteries

We report 1-(dimethylamino) pyrrole (PyDMA) as an electrolyte additive for high voltage lithium-ion batteries based on LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622)//Graphite with an upper cutoff voltage of 4.4 V. Density Functional Theory (DFT) modeling indicates that the unique structure of PyDMA could be effective in preventing the hydrolysis of LiPF 6 in a carbonate electrolyte, mitigating issues related to HF formation. The calculations also indicated that the additive would oxidize at lower potentials than typical electrolyte solvents, which could lead to protective films at the cathode surface. These expectations were tested using Nuclear Magnetic Resonance (NMR) and extensive electrochemical characterization. NMR studies confirmed the superb dehydrating capability of PyDMA, which successfully prevents HF formation even at high water content. Addition of 0.5 wt% PyDMA resulted in improved capacity retention in full-cells, and also in lower levels of transition metal dissolution from the cathode. Incremental capacity (dQ/dV) analysis indicates that benefits of PyDMA at low concentration (0.5–1 wt%) are associated with decreased rates of Li + -trapping reactions, and that higher concentrations of the additive can lead to isolation of cathode domains. Furthermore, our study indicates that PyDMA could be a promising electrolyte additive for high voltage lithium-ion batteries at a low concentration.

25 ENERGY STORAGE↗

DOE OSTI2025

Strong Correlation DMRG and DFT

This project developed new ways to improve computer simulations of materials where electrons interact strongly with each other, a challenge for today’s most widely used method, density functional theory (DFT). We used an exact numerical method, the density matrix renormalization group (DMRG), to create highly accurate reference results for simple model systems, and used these to test DFT, prove when it will converge, and even train machine-learned functionals. We also invented new kinds of localized basis functions (“gausslets” and “multi-sliced gausslets”) and a “sliced-basis” approach that make high-accuracy simulations faster and more practical. These methods were applied to extended hydrogen systems, enabling the direct derivation of accurate low-energy models from first-principles calculations. We also introduced a new formalism, Conditional-Probability DFT, which could bypass traditional approximations. The tools and results from this work, including open-source software releases, will help scientists design and understand complex quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Accounting for Sustainability and Performance: Contrasting Effects of PET-Derived Modifiers on Asphalt Durability

The valorization of waste plastics in roadway infrastructure requires careful balance between sustainability and performance, as ineffective modifiers may incur both environmental and financial costs. This study shows that two modifiers derived from the same waste plastic source (PET)-DOTP (N1,N4-(dioctyl)terephthalamide) and HETP (N1,N4-Bis(2-hydroxyethyl)terephthalamide)-exhibit opposite effects on asphalt properties, despite having nearly the same carbon footprint. DOTP improves elastic recovery in multiple creep recovery tests (MCRT), while HETP increases strain accumulation and reduces elasticity. Density functional theory (DFT) shows that DOTP's molecular structure can disperse well in bitumen mixtures by binding to both polar and non-polar components. In contrast, HETP binds only to the binder's polar sites, lacking adequate dispersion. This increases the risk of aggregation of polar compounds in the bitumen mixture, resulting in a more deformation-prone binder. A techno-economic analysis highlights trade-offs between sustainability and performance in industrial-scale synthesis. This study advocates for applying first-principles thinking in material design, coupled with experimental validation, to engineer plastic waste-derived additives that achieve both performance and sustainability goals.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Strategically Modified Ligand Incorporating Mixed Phosphonate and Carboxylate Groups to Enhance Performance in All-Iron Redox Flow Batteries

Iron redox flow batteries (Fe-RFBs) hold significant promise for achieving cost-effectiveness and utilizing abundant materials for stationary energy storage applications. Here, a design of a novel Fe complex utilizing a nitrogenous phosphonate/carboxylate mixed ligand, N,N-Bis(phosphonomethyl)glycine (BMPG), is presented to achieve high performance Fe anolyte. Compared to its all-phosphonate form, nitrilotri(methylphosphonic acid) (NTMPA), the new complex Fe(BPMG) 2 demonstrates a negatively shifted redox potential, resulting in ≈0.07 V (≈10%) increase in battery output voltage. Full battery testing paired with ferrocyanide catholyte demonstrates stable cycling (capacity degradation <0.0001%/cycle) over 730 consecutive charge/discharge cycles with Coulombic Efficiency of 100% at a current density of 20 mA cm -2 under near neutral pH (≈8). Of particular interest, density functional theory (DFT) studies and operando Raman measurements provide strong evidence supporting a molecular structure in BPMG, which reveals the mixed phosphonate/carboxylate groups in BPMG maintain the octahedral coordination of the Fe ion center with phosphonates exclusively, while leaving the carboxylate unbound for both Fe(II) and Fe(III) complexes. This structural similarity between BPMG-based Fe(II) and Fe(III) complexes effectively mitigates the slow redox reaction kinetics observed in Fe(NTMPA) 2 anolyte, where significant ligand reorientation occurs between Fe(II) and Fe(III) complexes.

25 ENERGY STORAGE↗

DOE OSTI2022

Improving Predictive Capability in REHEDS Simulations with Fast, Accurate, and Consistent Non-Equilibrium Material Properties

Predictive design of REHEDS experiments with radiation-hydrodynamic simulations requires knowledge of material properties (e.g. equations of state (EOS), transport coefficients, and radiation physics). Interpreting experimental results requires accurate models of diagnostic observables (e.g. detailed emission, absorption, and scattering spectra). In conditions of Local Thermodynamic Equilibrium (LTE), these material properties and observables can be pre-computed with relatively high accuracy and subsequently tabulated on simple temperature-density grids for fast look-up by simulations. When radiation and electron temperatures fall out of equilibrium, however, non-LTE effects can profoundly change material properties and diagnostic signatures. Accurately and efficiently incorporating these non-LTE effects has been a longstanding challenge for simulations. At present, most simulations include non-LTE effects by invoking highly simplified inline models. These inline non-LTE models are both much slower than table look-up and significantly less accurate than the detailed models used to populate LTE tables and diagnose experimental data through post-processing or inversion. Because inline non-LTE models are slow, designers avoid them whenever possible, which leads to known inaccuracies from using tabular LTE. Because inline models are simple, they are inconsistent with tabular data from detailed models, leading to ill-known inaccuracies, and they cannot generate detailed synthetic diagnostics suitable for direct comparisons with experimental data. This project addresses the challenge of generating and utilizing efficient, accurate, and consistent non-equilibrium material data along three complementary but relatively independent research lines. First, we have developed a relatively fast and accurate non-LTE average-atom model based on density functional theory (DFT) that provides a complete set of EOS, transport, and radiative data, and have rigorously tested it against more sophisticated first-principles multi-atom DFT models, including time-dependent DFT. Next, we have developed a tabular scheme and interpolation methods that compactly capture non-LTE effects for use in simulations and have implemented these tables in the GORGON magneto-hydrodynamic (MHD) code. Finally, we have developed post-processing tools that use detailed tabulated non-LTE data to directly predict experimental observables from simulation output.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Understanding of Active Sites and Interconversion of Pd and PdO during CH 4 Oxidation

Pd-based catalysts are widely used in the oxidation of CH 4 and have a significant impact on global warming. However, understanding their active sites remains controversial, because interconversion between Pd and PdO occurs consecutively during the reaction. Understanding the intrinsic active sites under reaction conditions is critical for developing highly active and selective catalysts. In this study, we demonstrated that partially oxidized palladium (PdO x ) on the surface plays an important role for CH 4 oxidation. Regardless of whether the initial state of Pd corresponds to oxides or metallic clusters, the topmost surface is PdO x , which is formed during CH4 oxidation. A quantitative analysis using CO titration, diffuse reflectance infrared Fourier-transform spectroscopy, X-ray diffraction, and scanning transmission electron microscopy demonstrated that a surface PdO layer was formed on top of the metallic Pd clusters during the CH 4 oxidation reaction. Furthermore, the time-on-stream test of CH 4 oxidation revealed that the presence of the PdO layer on top of the metallic Pd clusters improves the catalytic activity. Our periodic density functional theory (DFT) calculations with a PdO x slab and nanoparticle models aided the elucidation of the structure of the experimental PdO particles, as well as the experimental C-O bands. The DFT results also revealed the formation of a PdO layer on the metallic Pd clusters. This study helps achieve a fundamental understanding of the active sites of Pd and PdO for CH 4 oxidation and provides insights into the development of active and durable Pd-based catalysts through molecular-level design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Predicting Bond Dissociation Energies and Bond Lengths of Coordinatively Unsaturated Vanadium–Ligand Bonds

Understanding the electronic structure of coordinatively unsaturated transition-metal compounds and predicting their physical properties are of great importance for catalyst design. Bond dissociation energy D e and bond length r e are two of the fundamental quantities for which good predictions are important for a successful design strategy. In the present work, recent experimentally measured bond energies and bond lengths of VX diatomic molecules (X = C, N, S) are used as a gauge to consider the utility of a number of electronic structure methods. Single-reference methods are one focus because of their efficiency and utility in practical calculations, and multireference configuration interaction (MRCISD) methods and a composite coupled cluster (CCC) method are a second focus because of their potential high accuracy. The comparison is especially challenging because of the large multireference M diagnostics of these molecules, in the range 0.15–0.19. For the single-reference methods, Kohn–Sham density functional theory (KS-DFT) has been tested with a variety of approximate exchange-correlation functionals. Of these, MOHLYP provides the bond dissociation energies in best agreement with experiments, and BLYP provides the bond lengths that are in best agreement with experiments; but by requiring good performance for both the D e and r e of the vanadium compounds, MOHLYP, MN12-L, MGGA_MS1, MGGA_MS0, O3LYP, and M06-L are the most highly recommended functionals. The CCC calculations include up to connected pentuple excitations for the valence electrons and up to connected quadruple excitations for the core–valence terms; this results in highly accurate dissociation energies and good bond lengths. In conclusion, averaged over the three molecules, the mean unsigned deviation of CCC bond energies from experimental ones is only 0.4 kcal/mol, demonstrating excellent convergence of theory and experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

In-situ synthesized N-doped ZnO for enhanced CO 2 sensing: Experiments and DFT calculations

Chemiresistive CO 2 sensing is attractive due to low cost and ease of chip-level integration. Our previous studies (Yong Xia, 2021) showed the well-developed ZnO material fabricated by in-situ annealing exhibited good CO 2 sensing performance. Here, we have expanded on those studies, including CO 2 cyclic tests under both dry air and N 2 background whereby a much higher response to CO 2 in N 2 background was observed. In this study, detailed density functional theory calculations were conducted to understand the behavior. The results indicated nitrogen doping is mainly responsible for the observed response. In the presence of pre-adsorbed O 2 , N-doped ZnO can no longer interact with CO 2 , which agrees well with the observation of higher response in N 2 background. Furthermore, density of states analysis showed N sp 2 hybridized orbital and N 2p orbital of the N dopant mixed with sp 2 hybridized orbital of C atom and 2p orbitals of C/O atoms in CO 2 to form σ and π bonds, respectively. However, they mixed with O 2s/2p orbitals of O atom in O 2 when pre-adsorbed O 2 was present, hindering CO 2 interaction with N-doped ZnO, and resulting in limited response in air. The illustrated mechanism does not only further the understanding of metal oxide-based CO 2 sensing, but also guide the design of new functional materials for CO 2 sensing or capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Reactivity of Carbonate Solvent Electrolytes on Lithium Silicon Anodes

Silicon (Si) is promising for lithium-ion battery (LIB) anodes due to their high theoretical capacity and low electrochemical potential. However, significant challenges remain, including severe volumetric expansion during cycling and the electrochemical instability of electrolytes, which leads to the formation of a nonuniform solid electrolyte interphase (SEI). To investigate SEI formation mechanisms, computational molecular dynamics simulations offer valuable insights. In this work, we examine the trajectories and charge transfer behavior of lithium hexafluorophosphate (LiPF 6 ) salt with various solvent compositions using density functional theory (DFT) and ab initio molecular dynamics (AIMD). Among the tested electrolyte systems, LiPF 6 with vinylene carbonate (VC) added to ethyl methyl carbonate (EMC) exhibits the lowest reactivity with the Si anode. In contrast, the effects of fluoroethylene carbonate (FEC) and VC depend on whether the primary solvent is EMC alone or a mixture of ethylene carbonate (EC) and EMC. Moreover, we show that electrolyte reactivity varies with the degree of lithiation of the Si anode (LiSi vs Li 15 Si 4 ) and under different charge states. To decouple electrolyte reactivity from surface effects, we analyze the dissociation and formation energies of individual species from solvated configurations. Overall, these first-principles-based findings provide a strategic foundation for electrolyte design to improve cycling stability and extend calendar life in LIBs using Si anodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2006

NASA Crew Launch Vehicle Flight Test Options

Options for development flight testing (DFT) of the Ares I Crew Launch Vehicle (CLV) are discussed. The Ares-I Crew Launch Vehicle (CLV) is being developed by the U.S. National Aeronautics and Space Administration (NASA) to launch the Crew Exploration Vehicle (CEV) into low Earth Orbit (LEO). The Ares-I implements one of the components of the Vision for Space Exploration (VSE), providing crew and cargo access to the International Space Station (ISS) after retirement of the Space Shuttle and, eventually, forming part of the launch capability needed for lunar exploration. The role of development flight testing is to demonstrate key sub-systems, address key technical risks, and provide flight data to validate engineering models in representative flight environments. This is distinguished from certification flight testing, which is designed to formally validate system functionality and achieve flight readiness. Lessons learned from Saturn V, Space Shuttle, and other flight programs are examined along with key Ares-I technical risks in order to provide insight into possible development flight test strategies. A strategy for the first test flight of the Ares I, known as Ares I-1, is presented.

Cockrell, Charles E., Jr.↗

DOE OSTI2025

Transferable predictions of energetic and structural properties for refractory solid solution alloys across chemical compositions

We present a data-efficient approach to train graph neural networks (GNNs) on density functional theory (DFT) data for accurate and transferable predictions of energetic and structural properties of refractory solid solution alloys in the niobium-tantalum-vanadium (Nb-Ta-V) chemical space. We start by training the GNN model only on DFT data that describes refractory binary alloys niobium-tantalum (Nb-Ta), niobium-vanadium (Nb-V), and tantalum-vanadium (Ta-V) to predict formation enthalpy and root mean squared displacement. Once trained, the GNN predictions are tested on DFT data describing refractory ternary alloys Nb-Ta-V. While, unsurprisingly, direct transferability from binary to ternary is not sufficiently accurate, augmenting the training with only 1% of the available ternary data (uniformly distributed across the entire range of chemical compositions) improves significantly the quality of the GNN predictions. For comparison, we assess the transferability in the opposite direction by training GNN models on ternary Nb-Ta-V data and making predictions on binaries Nb-Ta, Nb-V, and Ta-V, which exhibits notably higher predictive errors. The proposed methodology, which favors transferability from lower-component to higher-component alloys, offers an efficient path towards avoiding the curse of dimensionality incurred when collecting DFT data for discovery and design of multi-component disordered alloys.

Density functional theory calculations↗

NASA NTRSDate not supplied

Overview of Ablative TPS Modeling at NASA Ames

Over the past decade, NASA has invested in efforts to build predictive thermal protection system (TPS) material models from the micro-scale to the macro-scale. To complement the mission design cycle process and reduce the need for extensive testing, NASA is developing modeling and simulation tools that enable characterizing material properties and response to hot plasma experienced during atmospheric entry. Traditional material response and ablation modeling tools, such as the heritage code FIAT, and its multidimensional siblings, TITAN and 3dFIAT, are being complemented with newly developed software such as Icarus and PATO. Both of these programs are three-dimensional, finite-volume solvers that use unstructured meshes and 21st century programming paradigms to allow for efficient parallel simulations. FIAT and Icarus are also used for TPS sizing purposes. Today, these traditional tools are being supplemented with computational materials models at the atomistic level. The scales of interest range from computational chemistry (Density Functional Theory [DFT]), to atomistic simulations (Molecular Dynamics [MD]), to the microscale with the Porous Microstructure Analysis (PuMA) software that was recently awarded the 2022 NASA Software of the Year award. Finally, thermo-structural modeling is also of interest to the TPS Materials branch and done using commercial tools such as MSC MARC, MENTAT, NASTRAN and PATRAN. The present talk will also link the use of these computational tools to current NASA missions and projects associated with challenging and complex vehicles entries/reentries.

materials modeling↗

DOE OSTI2025

Chromium enhances the mechanical performance of 3d transition metal high entropy alloys

A comprehensive examination of the compositional effects on the deformation behavior of high entropy alloys (HEAs) was conducted through nanoindentation, indentation creep, and stress relaxation experiments at ambient temperature. The alloys investigated included NiCoFe, NiCoCr, NiCoCrFe, and NiCoCrFeMn, all of which underwent identical thermomechanical processing. From the experimental results, NiCoCr exhibited the highest maximum shear stress for dislocation nucleation (13 GPa) and nanoindentation hardness (3.8 GPa) among the alloys tested. It also showed the lowest stress sensitivity (0.02) and activation volume (3–4 b 3 ) under creep and stress relaxation conditions, indicative of its superior plastic flow properties. Density functional theory (DFT) calculations further revealed an uneven charge density and larger bonding-length variation in NiCoCr due to the presence of Cr, which increased lattice distortion, impeding dislocation movement. Furthermore, in this study, post-deformation microscopy using transmission electron microscopy (TEM) revealed a high density of stacking faults and twins in NiCoCr that effectively enhanced its creep strength. The results highlight the significance of specific elemental effects, particularly from Cr in this study, over configurational entropy effect (i.e., compositional complexity) in governing the deformation microstructure and mechanical properties of HEAs. Finally, these insights will be instrumental for the design and optimization of advanced alloys for load-bearing applications.

36 - MATERIALS SCIENCE↗

DOE OSTI2025

Understanding of Ag Nanocatalysts for Electrocatalytic CO2 Conversion: Effects of Particle Size and Carbon Support

In this talk, we combined ultrahigh vacuum (UHV) surface science techniques, electrochemical measurements, and computational modeling to investigate Ag based electrocatalysts for CO2 reduction reaction (CO2RR). Our goal is to understand the critical characteristics governing the activity and selectivity of Ag electrocatalysts. Ag electrocatalysts were grown on highly oriented pyrolytic graphite (HOPG) in the UHV chamber, characterized with X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM), and then tested in a custom-built gastight H-cell. Supported by computational modeling based on density functional theory (DFT) calculations and microkinetic modeling (MKM), our studies revealed a strong size-dependent electrocatalytic CO2-to-CO conversion of the Ag nanoparticle electrocatalysts with average particle diameter between 2 to 6 nm. Smaller diameter (< 3 nm) particles favored H2 evolution reaction (HER) due to a high population of Ag edge sites, whereas larger diameter particles favored CO2RR as the population of Ag(100) surface sites grew. We further discovered that electronic interactions between small diameter Ag particles and highly defective carbon supports could break the size-dependent CO2RR reactivity, resulting in highly selective (CO Faradaic Efficiency > 90%) and active Ag nanoparticle electrocatalysts with sizes < 2 nm diameter. This knowledge is key to understand electrocatalysts performance and to ultimately guide electrocatalyst design

Ag nanoparticles↗