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Wei, Ziyang

Publications and source records attributed to Wei, Ziyang.

11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Structure Sensitivity and Catalyst Restructuring for CO2 Electro-reduction on Copper

Abstract Cu is the most promising metal catalyst for CO 2 electroreduction (CO 2 RR) to multi-carbon products, yet the structure sensitivity of the reaction and the stability versus restructuring of the catalyst surface under reaction conditions remain controversial. Here, atomic scale simulations of surface energies and reaction pathway kinetics supported by experimental evidence unveil that CO 2 RR does not take place on perfect planar Cu(111) and Cu(100) surfaces but rather on steps or kinks. These planar surfaces tend to restructure in reaction conditions to the active stepped surfaces, with the strong binding of CO on defective sites acting as a thermodynamic driving force. Notably, we identify that the square motifs adjacent to defects, not the defects themselves, as the active sites for CO 2 RR via synergistic effect. We evaluate these mechanisms against experiments of CO 2 RR on ultra-high vacuum-prepared ultraclean Cu surfaces, uncovering the crucial role of step-edge orientation in steering selectivity. Overall, our study refines the structural sensitivity of CO 2 RR on Cu at the atomic level, highlights the self-activation mechanism and elucidates the origin of in situ restructuring of Cu surfaces during the reaction.

Science & Technology - Other Topics↗
DOE OSTI2024

Atomic-scale identification of active sites of oxygen reduction nanocatalysts

Heterogeneous nanocatalysts play a crucial role in both the chemical and energy industries. Despite substantial advancements in theoretical, computational and experimental studies, identifying their active sites remains a major challenge. Here we utilize atomic electron tomography to determine the three-dimensional atomic structure of PtNi and Mo-doped PtNi nanocatalysts for the electrochemical oxygen reduction reaction. We then employ the experimental atomic structures as input to first-principles-trained machine learning to identify the active sites of the nanocatalysts. Through the analysis of the structure–activity relationships, we formulate an equation termed the local environment descriptor, which balances the strain and ligand effects to provide physical and chemical insights into active sites in the oxygen reduction reaction. The ability to determine the three-dimensional atomic structure and chemical composition of realistic nanoparticles, combined with machine learning, could transform our fundamental understanding of the active sites of catalysts and guide the rational design of optimal nanocatalysts.

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

First-Principles Insights into the Thermodynamics of Variable-Temperature Ammonia Synthesis on Transition-Metal-Doped Cu (100) and (111)

Ammonia (NH 3 ) is one of the most produced chemicals worldwide. NH 3 synthesis predominantly utilizes the Haber–Bosch (HB) process, requiring high temperatures and pressures. Despite significant process advances, ample opportunity remains for improving the rate, selectivity, catalyst stability, and energy efficiency. Inspired by a recently developed programmable heating and quenching (PHQ) technique, we present in this paper a first-principles screening of candidate single-atom alloy catalysts generated from doping (111) and (100) surfaces of copper (Cu), an ineffective HB catalyst in its pure form. We predict the thermodynamics of two rate-limiting reactions, N 2 dissociative adsorption and the final hydrogenation step leading up to NH 3 release, at 400 and 900 K. Thermodynamically, the former reaction is favored at low temperatures, while the latter is favored at high temperatures. Vanadium-, chromium-, and molybdenum-doped Cu surfaces, due to intermediate M–N covalent bonding character, emerge as appealing candidate catalysts for PHQ NH 3 synthesis, as they balance the thermodynamics of the above-mentioned reaction steps at their respective optimal temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Introducing the embedded random phase approximation: H 2 dissociative adsorption on Cu(111) as an exemplar

The random phase approximation (RPA) as a means of treating electron correlation recently has been shown to outperform standard density functional theory (DFT) approximations in a variety of cases. However, the computational cost of the RPA is substantially more than DFT, especially when aiming to study extended surfaces. Properly accounting for sufficient surface ensemble size, Brillouin zone sampling, and vacuum separation of periodic images in standard periodic-planewave-based DFT code raises the cost to achieve converged results. Here, we show that sub-system embedding schemes enable use of the RPA for modeling heterogeneous reactions at reduced computational cost. Further, we explore two different embedded RPA (emb-RPA) approaches, periodic emb-RPA and cluster emb-RPA. We use the (experimentally and theoretically) well-studied H 2 dissociative adsorption on Cu(111) as our exemplar, and first perform full periodic RPA calculations as a benchmark. The full RPA results match well the semi-empirical barrier fit to experimental observables and others derived from high-level computations, e.g., from recent embedded n-electron valence second order perturbation theory [Zhao et al., J. Chem. Theory Comput. 16(11), 7078–7088 (2020)] and quantum Monte Carlo [Doblhoff-Dier et al., J. Chem. Theory Comput. 13(7), 3208–3219 (2017)] simulations. Among the two emb-RPA approaches tested, the cluster emb-RPA accurately reproduces the energy profile (maximum error of 50 meV along the reaction pathway) while reducing the computational cost by approximately two orders of magnitude. We therefore expect that the embedded cluster approach will enable wider RPA implementation in heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Revisiting the link between magnetic properties and chemisorption at graphene nanoribbon zigzag edge

Graphene has received tremendous interest in both chemical and physical fields. Among different edges of the graphene system, the zigzag edge terminated graphene nanoribbons (ZGNRs) show unique magnetic properties in the antiferromagnetic (AFM) state. However, to date, the understanding of ZGNR chemical properties is mainly based on the partial radical concept, and in previous studies, the energy differences between the ferromagnetic (FM) and AFM states are smaller than experimental evidence. Here, we report that the strongly constrained and appropriately normed functional gives a significantly larger energy difference, which matches the experimental observation. Furthermore, utilizing the energetics in the large difference case, we propose a conceptual supplement to the previous partial radical concept: the overall stabilization of the AFM state compared to the nonmagnetic (NM) state consists of two parts that affect the adsorption energy conversely. The NM-FM energy differences will strengthen the adsorption, being in line with the previous partial radical concept. The FM-AFM energy differences will instead weaken the adsorption. Here, we perform calculations of H, OH, and LiS radical adsorption energies on ZGNRs to show that this weakening effect is numerically non-negligible: at least a ~0.2 eV difference in the adsorption energies is found. We expect that this refinement of the partial radical concept can provide a more comprehensive understanding of the chemical properties of ZGNRs. The differences in adsorption energies for the H, OH, and LiS radicals found here lead to significant changes in the predicted reactivity of the ZGNR models.

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

A fundamental look at electrocatalytic sulfur reduction reaction

The fundamental kinetics of the electrocatalytic sulfur reduction reaction (SRR), a complex 16-electron conversion process in lithium–sulfur batteries, is so far insufficiently explored. In this study, by directly profiling the activation energies in the multistep SRR, we reveal that the initial reduction of sulfur to the soluble polysulfides is relatively easy owing to the low activation energy, whereas the subsequent conversion of the polysulfides into the insoluble Li 2 S 2 /Li 2 S has a much higher activation energy, contributing to the accumulation of polysulfides and exacerbating the polysulfide shuttling effect. We use heteroatom-doped graphene as a model system to explore electrocatalytic SRR. We show that nitrogen and sulfur dual-doped graphene considerably reduces the activation energy to improve SRR kinetics. Density functional calculations confirm that the doping tunes the p-band centre of the active carbons for an optimal adsorption strength of intermediates and electroactivity. This study establishes electrocatalysis as a promising pathway to tackle the fundamental challenges facing lithium–sulfur batteries.

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

A Perspective on interfacial engineering of lithium metal anodes and beyond

This Perspective reviews interfacial engineering of lithium metal anodes. Critical issues and open scientific questions related to coatings on the lithium metal anode are discussed. Essential features for ideal coatings, especially those that can potentially enable lithium plating underneath the coating, are highlighted. While most existing approaches use kinetic control to regulate the coating thickness, here we offer a Perspective on thermodynamically controlled interfacial engineering, focusing on spontaneously formed 2D interfacial phases (also known as “complexions”). This approach has been applied to other battery systems but has yet to be realized for lithium metal anodes.

25 ENERGY STORAGE↗