Predictions of Chemical Shifts for Reactive Intermediates in CO2 Reduction under Operando Conditions

CO2 Reduction to Methane and Ethylene on a Single-Atom Catalyst: A Grand Canonical Quantum Mechanics Study

In recent years, two-dimensional metal-organic frameworks (2D MOF) have attracted great interest for their ease of synthesis and for their catalytic activities and semiconducting properties. The appeal of these materials is that they are layered and easily exfoliated to obtain a monolayer (or few layer) material with interesting optoelectronic properties. Moreover, they have great potential for CO2 reduction to obtain solar fuels with more than one carbon atom, such as ethylene and ethanol, in addition to methane and methanol. In this paper, we explore how a particular class of 2D MOF based on a phthalocyanine core provides the reactive center for the production of ethylene and ethanol. We examine the reaction mechanism using the new grand canonical potential kinetics (GCP-K) or grand canonical quantum mechanics (GC-QM) computational methodology, which obtains reaction rates at constant applied potential to compare directly with experimental results (rather than at constant electrons as in standard QM). We explain the reaction mechanism underlying the formation of methane and ethylene. Here, the key reaction step is direct coupling of CO into CHO, without the usual rate-determining CO-CO dimerization step observed on Cu metal surfaces. Indeed, the 2D MOF behaves like a single-atom catalyst.

Preferential decomposition of the major anion in a dual-salt electrolyte facilitates the formation of organic-inorganic composite solid electrolyte interphase

The performance of a lithium metal battery (LMB) with liquid electrolytes depends on the realization of a stable solid electrolyte interphase (SEI) on the Li anode surface. According to a recent experiment, a high-concentrated (HC) dual-salt electrolyte is effective in modulating the SEI formation and improving the battery performance. However, the underlying reaction mechanism between this HC dual-salt electrolyte and the lithium metal anode surface remains unknown. To understand the SEI formation mechanism, we first performed 95 ps ab initio Molecular Dynamics (AIMD) simulation and then extend this AIMD simulation to another 1 ns by using Hybrid ab Initio and Reactive Molecular Dynamics (HAIR) to investigate the deep reactions of such dual-salt electrolytes consists of lithium difluorophosphate and lithium bis(trifluoromethanesulfonyl)imide in dimethoxyethane (DME) solvent at lithium metal anode surface. We observed the detailed reductive decomposition processes of DFP^- and TFSI^-, which include the formation pathway of CF₃ fragments, LiF, and Li_xPOF_y, the three main SEI components observed experimentally. Furthermore, after extending the simulation to 1.1 ns via the HAIR scheme, the decomposition reactions of DME solvent molecules were also observed, producing LiOCH₃, C₂H₄, and precursors of organic oligomers. These microscopic insights provide important guidance in designing the advanced dual-salt electrolytes for developing high-performance LMB.

Machine Learning Predicts the X-ray Photoelectron Spectroscopy of the Solid Electrolyte Interface of Lithium Metal Battery

X-ray photoelectron spectroscopy (XPS) is a powerful surface analysis technique widely applied in characterizing the solid electrolyte interphase (SEI) of lithium metal batteries. However, experiment XPS measurements alone fail to provide atomic structures from a deeply buried SEI, leaving vital details missing. By combining hybrid ab initio and reactive molecular dynamics (HAIR) and machine learning (ML) models, we present an artificial intelligence ab initio (AI-ai) framework to predict the XPS of a SEI. A localized high-concentration electrolyte with a Li metal anode is simulated with a HAIR scheme for ∼3 ns. Taking the local many-body tensor representation as a descriptor, four ML models are utilized to predict the core level shifts. Overall, extreme gradient boosting exhibits the highest accuracy and lowest variance (with errors ≤ 0.05 eV). Such an AI-ai model enables the XPS predictions of ten thousand frames with marginal cost.

Probing the Dynamics of Low-Overpotential CO2-to-CO Activation on Copper Electrodes with Time-Resolved Raman Spectroscopy

Oxide-derived copper electrodes have displayed a boost in activity and selectivity toward valuable base chemicals in the electrochemical carbon dioxide reduction reaction (CO2RR), but the exact interplay between the dynamic restructuring of copper oxide electrodes and their activity and selectivity is not fully understood. In this work, we have utilized time-resolved surface-enhanced Raman spectroscopy (TR-SERS) to study the dynamic restructuring of the copper (oxide) electrode surface and the adsorption of reaction intermediates during cyclic voltammetry (CV) and pulsed electrolysis (PE). By coupling the electrochemical data to the spectral features in TR-SERS, we study the dynamic activation of and reactions on the electrode surface and find that CO₂ is already activated to carbon monoxide (CO) during PE (10% Faradaic efficiency, 1% under static applied potential) at low overpotentials (−0.35 V_RHE). PE at varying cathodic bias on different timescales revealed that stochastic CO is dominant directly after the cathodic bias onset, whereas no CO intermediates were observed after prolonged application of low overpotentials. An increase in cathodic bias (−0.55 V_RHE) resulted in the formation of static adsorbed CO intermediates, while the overall contribution of stochastic CO decreased. We attribute the low-overpotential CO₂-to-CO activation to a combination of selective Cu(111) facet exposure, partially oxidized surfaces during PE, and the formation of copper-carbonate-hydroxide complex intermediates during the anodic pulses. This work sheds light on the restructuring of oxide-derived copper electrodes and low-overpotential CO formation and highlights the power of the combination of electrochemistry and time-resolved vibrational spectroscopy to elucidate CO2RR mechanisms.

DFT-ReaxFF hybrid molecular dynamics investigation of the decomposition effects of localized high-concentration electrolyte in lithium metal batteries: LiFSI/DME/TFEO

Due to its low electrochemical potential and high theoretical specific energy, lithium-metal batteries (LMBs) have been considered as a promising advanced energy storage system for portable applications such as electric vehicles (EVs). However, the uncontrolled growth of lithium dendrites during cycling has remained a challenge. By utilizing an inert solvent to "dilute" the high concentration electrolytes, the concept of localized high-concentration electrolytes (LHCEs) has recently been demostrated as an effective solution to enable the dendrite-free cycling of LMBs. In this work, we investigated the reactions of 2 M lithium bis(fluorosulfonyl)imide (LiFSI) in a mixture of dimethoxyethane (DME)/tris(2,2,2-trifluoroethyl) orthoformate (TFEO) electrolyte at a Li metal anode. The SEI formation mechanism is investigated using a hybrid ab initio and reactive force field (HAIR) method. The 1n reactive HAIR trajectory reveals the important initial reduction reactions of LiFSI, TFEO, and DME. Particularly, both FSI anions and TFEO decompose quickly to release a considerable amount of F^-, which leads to a LiF-rich SEI inorganic inner layer (IIL). Furthermore, TFEO produces a significant amount of unsaturated carbon products, such as thiophene, which can potentially increase the conductivity of SEI to increase the battery performance. Meanwhile, XPS analysis is utilized to further investigate the evolution of the atomic environment in SEI. Future designs of better electrolytes can be greatly aided by these results.

Multiscale Simulation of Solid Electrolyte Interface Formation in Fluorinated Diluted Electrolytes with Lithium Anodes

Lithium metal batteries (LMBs) hold great promise in facilitating high-energy batteries due to their merits such as high specific capacity, low reduction potential, and so forth. However, the realizations of practical LMBs are hindered by severe problems such as undesirable dendrite growth, poor Coulombic efficiency, and so forth. A recently proposed fluorinated electrolyte based on 1 M lithium bis(fluorosulfonyl)imide (LiFSI) dissolved in designed fluorinated 1,4-dimethoxybutane (FDMB) solvent has attracted significant attention because of its excellent electrochemical performance that origins from its superior physical and chemical properties, especially its unique ability in forming a robust, stable solid electrolyte interphase (SEI). However, the detailed structure and reaction mechanism of the SEI formation in such a novel electrolyte remains unclear. In this work, we carry out a hybrid ab initio and reactive molecular dynamics (HAIR) simulation to investigate the elementary reactions that regulate the formation of the primitive SEI, paying special attention to the process that involves FDMB, the fluorinated solvent. HAIR simulation reveals that both FSI^- anion and FDMB provide F that is adequate to form a uniformed LiF layer that resembles the inorganic inner layer (IIL) of the SEI. N and S radicals from the FSI^- anion, which do not deposit on the electrode interface to form lithium-containing inorganic substances, promote the polymerization reaction of unsaturated carbon chains produced by FDMB defluorination, forming the organic outer layer (OOL) of the SEI. The combination of the LiF-rich IIL and polymer-rich organic OOL explains the superior performance of the FDMB-based electrolyte in the device. The detailed reaction mechanism and SEI observed in this work provide insights into the atomic scale for the rational design of F-rich electrolytes in the near future.

Realistic Modelling of Dynamics at Nanostructured Interfaces Relevant to Heterogeneous Catalysis

The focus of this short review is directed towards investigations of the dynamics of nanostructured metallic heterogeneous catalysts and the evolution of interfaces during reaction—namely, the metal–gas, metal–liquid, and metal–support interfaces. Indeed, it is of considerable interest to know how a metal catalyst surface responds to gas or liquid adsorption under reaction conditions, and how its structure and catalytic properties evolve as a function of its interaction with the support. This short review aims to offer the reader a birds-eye view of state-of-the-art methods that enable more realistic simulation of dynamical phenomena at nanostructured interfaces by exploiting resource-efficient methods and/or the development of computational hardware and software.

Exploring the materials space in the smallest particle size range: From heterogeneous catalysis to electrocatalysis and photocatalysis

Ultrasmall clusters of subnanometer size can possess unique and even unexpected physical and chemical propensities which make them interesting in various fields of basic science and for potential applications, such...