Leveraging Machine Learning Potentials for In-Situ Searching of Active sites in Heterogeneous Catalysis

Precision Chemistry, Journal Year: 2024, Volume and Issue: 2(11), P. 570 - 586

Published: Sept. 11, 2024

This Perspective explores the integration of machine learning potentials (MLPs) in research heterogeneous catalysis, focusing on their role identifying

Language: Английский

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Structure and polymerization of liquid sulfur across the λ-transition

Chemical Science, Journal Year: 2024, Volume and Issue: 15(9), P. 3382 - 3392

Published: Jan. 1, 2024

We study the lambda liquid–liquid transition between molecular and polymeric phases of sulfur with dynamics simulations boosted by state-of-the-art enhanced sampling techniques ab initio -quality machine-learning potentials.

Language: Английский

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

JACS Au, Journal Year: 2024, Volume and Issue: 4(4), P. 1405 - 1412

Published: March 12, 2024

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

Language: Английский

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Advancing tribological simulations of carbon-based lubricants with active learning and machine learning molecular dynamics

The European Physical Journal Plus, Journal Year: 2024, Volume and Issue: 139(6)

Published: June 25, 2024

Abstract The need to move toward more sustainable lubricant materials has sparked an ever growing interest on the tribological performances of additives based environmentally friendly molecules, such as carbon-based compounds, and green liquid media aqueous solutions. prediction solubility into tribochemistry decomposition polymerization additive molecules under harsh conditions is essential for understanding atomistic mechanisms leading formation in situ lubricious tribofilms so effective reducing friction wear at solid interfaces. To this extent, application tools like ab initio molecular dynamics first-principle density functional theory severely hindered by size systems interests simulate their over relatively long times. enable simulations with quantum accuracy a first time, we develop workflow smart configuration sampling active learning, obtain machine learning interatomic potentials which are shown be sufficiently robust accurate also characteristic generated high loads shear rates. Focusing glycerol rich lubricants, apply strategy generate neural network potential behavior nanometer thick tribofilms. reveal superior approach respect classical reactive force fields, pave way promising depth exploration novel lubricants.

Language: Английский

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Unveiling the Role of Solvent in Solution Phase Chemical Reactions using Deep Potential-Based Enhanced Sampling Simulations

The Journal of Physical Chemistry Letters, Journal Year: 2024, Volume and Issue: unknown, P. 9932 - 9938

Published: Sept. 23, 2024

We have used a deep learning-based active learning strategy to develop

Language: Английский

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Modeling Dynamic Catalysis at ab Initio Accuracy: The Need for Free-Energy Calculation

ACS Catalysis, Journal Year: 2024, Volume and Issue: 14(21), P. 16086 - 16097

Published: Oct. 17, 2024

InfoMetricsFiguresRef. ACS CatalysisASAPArticle This publication is free to access through this site. Learn More CiteCitationCitation and abstractCitation referencesMore citation options ShareShare onFacebookX (Twitter)WeChatLinkedInRedditEmailJump toExpandCollapse ViewpointOctober 17, 2024Modeling Dynamic Catalysis at ab Initio Accuracy: The Need for Free-Energy CalculationClick copy article linkArticle link copied!Qi-Yuan FanQi-Yuan FanEngineering Research Center of Ministry Education Fine Chemicals, School Chemistry Chemical Engineering, Shanxi Key Laboratory Coal-based Value-added Chemicals Green Synthesis, University, Taiyuan 030006, ChinaMore by Qi-Yuan FanFu-Qiang GongFu-Qiang GongState Physical Solid Surface, Collaborative Innovation Energy Materials (iChEM), College Xiamen 361005, Fu-Qiang GongYun-Pei LiuYun-Pei LiuState ChinaLaboratory AI Electrochemistry (AI4EC), IKKEM, Yun-Pei LiuHao-Xuan ZhuHao-Xuan ZhuState Hao-Xuan ZhuJun Cheng*Jun ChengState ChinaInstitute Artificial Intelligence, China*Email: [email protected]More Jun Chenghttps://orcid.org/0000-0001-6971-0797Open PDFACS CatalysisCite this: Catal. 2024, 14, XXX, 16086–16097Click citationCitation copied!https://pubs.acs.org/doi/10.1021/acscatal.4c05372https://doi.org/10.1021/acscatal.4c05372Published October 2024 Publication History Received 4 September 2024Accepted 8 2024Revised 7 2024Published online 17 2024article-commentary© American Society. available under these Terms Use. Request reuse permissionsThis licensed personal use Publications© SocietySubjectswhat are subjectsArticle subjects automatically applied from the Subject Taxonomy describe scientific concepts themes article.CatalystsChemical reactionsFree energyMetal clustersStructural dynamics1. IntroductionClick section linkSection copied!Heterogeneous catalysis plays an increasingly important role in modern chemical industry. active site, as proposed Taylor, (1) one most fundamental heterogeneous key understanding catalytic mechanisms. Over years, considerable effort has been dedicated exploring identifying atomic compositions geometric configurations sites. In traditional surface science studies conducted low temperatures, sites often regarded certain fixed structures with well-defined arrangements, such terrace, step, edge (Figure 1A), assumed remain unchanged reaction conditions. However, recent decades, it widely accepted that undergo dynamic changes proceeds, challenging notion static 1B).Figure 1Figure 1. Schematic illustration catalyst catalysis. (A) site nanocatalysts special arrangement. (B) evolution structures. (C) energy profiles stable metastable structures.High Resolution ImageDownload MS PowerPoint SlideUnderstanding crucial precise design catalysts. situ or operando experimental measurements essential capturing nature Among used techniques electron microscopy spectroscopy high spatial temporal resolution. former, exemplified transmission (TEM), can directly capture structural catalysts conditions scale, enabling real-time tracking rearrangements on including reconstruction, phase transition, size variations. latter provides detailed information about structures, charge transfer, bond vibration, coordination number, etc. For example, extended X-ray absorption fine structure (EXAFS) be obtain number interatomic distances. Combining allows a comprehensive analysis behaviors, providing novel insights into obtaining thermodynamic kinetic reactions remains challenging.In addition techniques, theoretical calculations initio accuracy statistical sampling configurational space allow us visualize study underlying mechanisms Global optimization (GO) molecular dynamics (MD) two common approaches modeling dynamics. These methods have significantly enriched our behavior GO commonly explore potential (PES) determine catalyst. instance, various approaches, genetic algorithms, basin hopping, stochastic walking (SSW), extensively developed studying cluster (2,3) Once shape identified, global minimum several other possible low-energy isomers selected further corresponding With efficient algorithm, approach reliably generate located PES; however, implies higher probability occurrence does not necessarily represent largest contribution activity finite temperatures. contrast, some high-energy may contribute more process 1C). mentioned above confirmed significance isomers, while mechanistic still depends initially using 0 K. based assumption: time scale elementary (typically order picoseconds) shorter than (which occur macroscopic scales). disparity decoupling when scales comparable, strong coupling would unavoidable. mode, becomes part coordinate. Thus, perspective required accurately understand intrinsic activity.Different GO, MD employed examine calculate properties ensemble. Classical typically employs predefined empirical potentials. due their oversimplified representations interactions, no force fields formation breaking types bonds. classical suitable simulations reactions. Ab (AIMD) assesses forces accurate electronic calculations. Consequently, exactly take account contributions reactions, thereby reflection realistic conditions.A series Cheng et al. (4,5) reinvigorated dynamics, which they described ensemble many rather solely focusing one. By combining AIMD calculation methods, rigorously calculated energies entropy caused Their findings revealed highly flexible temperatures substantial impact profiles. Notably, observed anomalous nonlinear curve increasing temperature, attributed adsorption-induced solid-to-liquid transition Importantly, entropic effect help optimize working reactions.Although successfully conditions, limited its computational cost only relatively small systems, comprising hundreds atoms tens picoseconds. inefficient processes complex Recently, machine learning methodologies, especially potentials (MLPs), emerged promising tools MLPs decompose total system sum contributions, each being function local environment. constructing one-to-one mapping environments forces, enable reproduction PES. Using accelerate simulations, i.e. (MLMD), enhance efficiency orders magnitude maintaining accuracy. achieved because trained high-quality data derived quantum mechanical calculations, density functional theory (DFT). Nowadays, shown powerful tool chemistries, (6−9) networks. (10−12)In Viewpoint, we will provide brief overview field well challenges, aiming achieve following section, first briefly introduce research terms separately. Subsequently, compare illustrate importance rigorous end, discuss effects transitions reactions.2. Structural Dynamics CatalystsClick copied!Elucidating how specific arrangements facilitate central goals chemists across generations. combination advanced makes characterize unravel level. summarize applications characterization Experimental Characterizations Catalyst DynamicsThe long rooted approach, where experiments single-crystal surfaces ultrahigh-vacuum (UHV) Ertl co-workers made outstanding research. They emphasized complexity catalysis, typical examples: ammonia synthesis CO oxidation. (13) adsorption facet Pt(110), scanning tunneling (STM) UHV 300 K missing row reconstruction clean K, showing static. (14) addition, Somorjai frequency generation (SFG), diffraction (LEED), auger (AES) monitor different kinds single crystal low-pressure environments. built high-pressure cells investigate C–H activation ethylene Pt(111) surface, (15) C–O Pt surfaces, (16) (17) indicate during those vacuum, emergence new sites.While investigations provided valuable mechanisms, highlighted limitations fully complexities real systems. To bridge gap between ideal model systems industrially relevant researchers turned toward measurements, catalysis.Over past decade, numerous metal nanoparticles (e.g., Au, Pt, Cu, Ni), shed light impacts (18−21) general, behaviors include changes, transitions, composition studies, play since direct visualization over time. Hansen (22) performed atom-resolved change supported Cu environmental microscope (ETEM). work Later, Hakeda (23) also ETEM CeO2-supported Au(100) adsorbed molecules room temperature. demonstrated Au undergoes response surrounding gas Additionally, were Wang co-workers. (24) found larger sizes rigid whereas ultrasmall clusters liquid-like disordered 2A). size-dependent critical enhancing reactivity selectivity, emphasizing designing performance.Figure 2Figure 2. CeO2(111) vacuum CO+O2 atmosphere. models images nm NPs CeO2 (a–c), <2 (d–f), ∼2 layer (g–i). melting Au561 particle temperature characterized high-angle annular dark-field STEM. Pt@MCM-22 Panel reprinted permission ref (24). Copyright 2018, National Academy Sciences. reproduced (25). Available CC-BY 4.0 license. 2019 Author Name(s). (28). 2018 Name(s).High SlideAnother factor influencing offer thermal energy, enhances ability overcome barriers reconstruction. Previous works (2–5 diameter) carbon films occurs heating stage aberration-corrected (ac-STEM); (25) elevated form solid core-liquid shell 2B), confirming transformation sensitive temperature.In photoelectron (XPS), (XAS), EXAFS, track distance, state. Tao (26) dramatic reversible core–shell Rh0.5Pd0.5 state XPS Torr pressure range. It worth noting difficult reach technique. Instead, integration multiple necessary complementary aspects, establishing correlation performance. Liu (27) recently conversion Ni@Au bimetallic CO2 hydrogenation combined variety synchrotron XAS, infrared spectroscopy, simulations. selectivity was transiently reconfigured alloy promoted adsorption.In cases, rearrangement migration accompanied sizes. Corma (28−30) confined inside zeolite among isolated species, clusters, oxidation water–gas shift 2C). Such Al2O3 TiO2-supported catalysts, (31,32) zeolite-confined PtSn clusters. (33,34)Other changes. Matsuda his (35) TEM Ni hydrocarbon reformation. observations 250 350 °C, close-packed plane expanded, dissolve nanocatalysts, leading FCC HCP Ni. Besides, optimizing (36) investigated carburization, oxidation, coking Fe particles Fischer–Tropsch (FT) high-resolution ETEM. Fe5C2, dynamically formed Fe5C2 responsible FT reaction. Luo (37) captured conditions; exposure leads roughening consequently low-coordinated atoms, O2 induces quasi-crystalline CuOx phase. highlight significant influence gaseous environments, composition, Computational Modeling DynamicsIn parallel microscopic level, giving Recent years witnessed efforts subnanometer garnering particular attention distinct physical properties. smaller intriguing counterparts unique PESs rich minima comparable energies. Under high-temperature energetically similar equilibrium, exhibiting fluxionality, interconvert configurations.In attempting methods. (3,38) (39) utilized SSW method search lowest 3A). yielded thousands candidate size, demonstrating Alexandrova Sautet interesting (40−42) isomerization identified both Pt7/Al2O3 exhibit fluxional 3B). Moreover, Pt13 methane compared lowest-energy suggesting even dominate activity. (43) A phenomenon, show Mo/Al2O3 (44) mentioning sampled usually limited, e.g., configurations. Furthermore, generally consider ensemble, comprehensively.Figure 3Figure 3. PtN search. Isomerization network connecting 30 via paths. Initial final snapshots Au20 eight adsorption. (D) workflow, composed training potential, exploration configuration spaces, labeling (39). 2016 (41). (47). 2015 aspect technique purpose. address issue perspective. Salahub (45) (QM/MM) simulate taking pressure, solvent environment account. very having great advancements application elucidated Li (24,46,47) studied ceria-supported gold varying AIMD. atom upon molecular, could reintegrate back once complete 3C). results understanding. Similar single-atom Rh exposed (48) Beyond proven invaluable nanoporous Speybroeck (49,50) within channels zeolite/MOF included stability, diffusion behavior, nucleation reactant. striking example metal-zeolite become mobilized interaction species. (51)Additionally, Monte Carlo (KMC) effective incorporates events adsorption, desorption, diffusion. advantage KMC lies inhomogeneities correlations reactant distributions (52) realm grown popularity performance scale. Xu phenomenological kinetics (XPK) method, (53,54) KMC, syngas Rh(111) surface; (55) intermediate induce optimizes own pathways, overall selectivity. carried out migrations atoms; Mavrikakis (56) Cu(111) As another Gao (57) simulated reshaping atomistic nanoparticle surface. Despite fact demonstrates technical features wide faces expense develop chemistries lack general framework effects.It coupled coordinates differs re-equilibration before after much dramatically affect mechanism. context, along coordinate obtained, owing thus influences considered. poi

Language: Английский

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Machine Learning Potentials for Heterogeneous Catalysis

ACS Catalysis, Journal Year: 2025, Volume and Issue: 15(3), P. 1616 - 1634

Published: Jan. 15, 2025

The production of many bulk chemicals relies on heterogeneous catalysis. rational design or improvement the required catalysts critically depends insights into underlying mechanisms atomic scale. In recent years, substantial progress has been made in applying advanced experimental techniques to complex catalytic reactions operando, but order achieve a comprehensive understanding, additional information from computer simulations is indispensable cases. particular, ab initio molecular dynamics (AIMD) become an important tool explicitly address atomistic level structure, dynamics, and reactivity interfacial systems, high computational costs limit applications systems consisting at most few hundred atoms for simulation times up tens picoseconds. Rapid advances development modern machine learning potentials (MLP) now offer promising approach bridge this gap, enabling with accuracy small fraction costs. Perspective, we provide overview current state art MLPs relevant catalysis along discussion prospects use science years come.

Language: Английский

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A Molecular View of Methane Activation on Ni(111) through Enhanced Sampling and Machine Learning

The Journal of Physical Chemistry Letters, Journal Year: 2024, Volume and Issue: 15(39), P. 9852 - 9862

Published: Sept. 19, 2024

A combination of machine learned interatomic potentials (MLIPs) and enhanced sampling simulations is used to investigate the activation methane on a Ni(111) surface. The work entails development iterative refinement MLIPs, initially trained data set constructed via ab initio molecular dynamics simulations, supplemented by adaptive biasing forces, enrich catalytically relevant configurations. Our results reveal that upon incorporation collective variables capture behavior reactant molecule, as well additional frames describe dynamic response catalytic surface, it possible enhance considerably accuracy predicted energies forces. By employing schemes in MLIP, we systematically explore potential energy leading refined MLIP capable predicting density functional theory-level forces replicating key geometric characteristics system. resulting free landscapes at several temperatures provide detailed view thermodynamics activation. Specifically, approaches dissociates process involves interplay CH4 Ni catalyst includes both enthalpic entropic contributions. progression toward transition state moiety increasingly restrained its ability rotate or translate, while stage following characterized notable rise atom interacts with cleaved C-H bond. This leads an increase mobility adsorbed species, feature becomes more pronounced higher temperatures.

Language: Английский

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Determining the Magnetic Status of Active Sites on Nanocatalysts

The Journal of Physical Chemistry Letters, Journal Year: 2025, Volume and Issue: 16(6), P. 1447 - 1452

Published: Jan. 31, 2025

Identifying the atomic structure and chemical composition of active sites on nanocatalysts has been a long pursuit in heterogeneous catalysis. Yet, determining magnetic well-defined site is even more challenging. However, explicit morphology reaction temperature have not considered identifying behaviors nanocatalysts, especially theoretical studies. Herein, we determined status nanoscale catalysts at finite temperatures by using atomistic spin models. The size dependence Curie point premelting discussed, indicating that properties over localized center can greatly differ from bulk. Therefore, phase transitions its concomitant magneto-catalytic effect be induced considerably low temperature. Our analysis demonstrated an 8 nm cobalt-based core-shell nanoparticle achieve optimal magnetization with Sabatier activity for ammonia synthesis 523 K, which accord condition Haber-Bosch process. We believe our findings elucidate importance configuration sites. Furthermore, including this unexcavated dimension dynamical simulations catalytic process provide us complete comprehensive understanding mechanism under working conditions.

Language: Английский

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First-Principles Insights into the Thermocatalytic Cracking of Ammonia-Hydrogen Blends on Fe(110). 2. Kinetics

The Journal of Physical Chemistry C, Journal Year: 2025, Volume and Issue: unknown

Published: March 31, 2025

Language: Английский

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