Structural evolution and electronic properties of cerium doped germanium anionic nanocluster CeGen− (n = 5–17): Theoretical investigation DOI

Chenliang Hao,

Caixia Dong, Zhaofeng Yang

et al.

International Journal of Quantum Chemistry, Journal Year: 2023, Volume and Issue: 124(1)

Published: Dec. 15, 2023

Abstract The rare earth element doped germanium cluster represents a fundamental nanomaterial and exhibits potential in next‐generation industrial electronic nanodevices applied semiconductors. Herein, the cerium‐doped anionic nanocluster CeGe n − ( = 5–17) has been comprehensively investigated by double hybrid density functional theory of mPW2PLYP associated with unbiased global searching technique artificial bee colony algorithm. cluster's growth pattern undergoes three stages: 5–9 replaced structure, 10–15 linked ≥ 16 forming Ce‐encapsulated Ge inner cage motif. clusters' PES, IR, Raman spectra were simulated, their HOMO‐LUMO gap, magnetism, charge transfer, relative stability predicted. These theoretical values can serve as reference for future experiments to some extent. Moreover, special D 2 d symmetry geometry leads higher preferred energy making it an ideal candidate further studies on its aromaticity, UV–vis spectra, chemical bonding characteristics. In summary, excellent optical activity that be potentially employed building block development optoelectronic materials.

Language: Английский

Improving the Accuracy of Atomistic Simulations of the Electrochemical Interface DOI
Ravishankar Sundararaman, Derek Vigil‐Fowler, Kathleen Schwarz

et al.

Chemical Reviews, Journal Year: 2022, Volume and Issue: 122(12), P. 10651 - 10674

Published: May 6, 2022

Atomistic simulation of the electrochemical double layer is an ambitious undertaking, requiring quantum mechanical description electrons, phase space sampling liquid electrolytes, and equilibration electrolytes over nanosecond time scales. All models electrochemistry make different trade-offs in approximation electrons atomic configurations, from extremes classical molecular dynamics a complete interface with point-charge atoms to correlated electronic structure methods single electrode configuration no or electrolyte. Here, we review spectrum techniques suitable for electrochemistry, focusing on key approximations accuracy considerations each technique. We discuss promising approaches, such as enhanced configurations computationally efficient beyond density functional theory (DFT) methods, that will push simulations present frontier.

Language: Английский

Citations

84
Dynamic Copper Site Redispersion through Atom Trapping in Zeolite Defects DOI
Stephen C. Purdy, Greg Collinge, Junyan Zhang

et al.

Journal of the American Chemical Society, Journal Year: 2024, Volume and Issue: 146(12), P. 8280 - 8297

Published: March 11, 2024

Single-site copper-based catalysts have shown remarkable activity and selectivity for a variety of reactions. However, deactivation by sintering in high-temperature reducing environments remains challenge often limits their use due to irreversible structural changes the catalyst. Here, we report zeolite-based copper which oxide agglomerates formed after reaction can be repeatedly redispersed back single sites using an oxidative treatment air at 550 °C. Under different environments, single-site Cu–Zn–Y/deAlBeta undergoes dynamic structure oxidation state that tuned promote formation key active while minimizing through Cu sintering. For example, Cu2+ reduces Cu1+ catalyst pretreatment (270 °C, 101 kPa H2) further Cu0 nanoparticles under conditions (270–350 7 EtOH, 94 or accelerated aging (400–450 H2). After regeneration °C air, agglomerated CuO was dispersed presence absence Zn Y, verified imaging, situ spectroscopy, catalytic rate measurements. Ab initio molecular dynamics simulations show solvation monomers water facilitates transport zeolite pore, condensation monomer with fully protonated silanol nest entraps reforms structure. The capability nests trap stabilize oxidizing could extend wider reactions allows simple strategy catalysts.

Language: Английский

Citations

21
Theoretical insights into the surface physics and chemistry of redox-active oxides DOI
Roger Rousseau, Vassiliki‐Alexandra Glezakou, Annabella Selloni

et al.

Nature Reviews Materials, Journal Year: 2020, Volume and Issue: 5(6), P. 460 - 475

Published: May 27, 2020

Language: Английский

Citations

120
Potential Application of Machine-Learning-Based Quantum Chemical Methods in Environmental Chemistry DOI
Deming Xia, Jingwen Chen, Zhiqiang Fu

et al.

Environmental Science & Technology, Journal Year: 2022, Volume and Issue: 56(4), P. 2115 - 2123

Published: Jan. 27, 2022

It is an important topic in environmental sciences to understand the behavior and toxicology of chemical pollutants. Quantum methodologies have served as useful tools for probing pollutants recent decades. In years, machine learning (ML) techniques brought revolutionary developments field quantum chemistry, which may be beneficial investigating However, ML-based methods (ML-QCMs) only scarcely been used studies so far. To promote applications promising methods, this Perspective summarizes progress ML-QCMs focuses on their potential that could hardly achieved by conventional methods. Potential challenges predicting degradation networks pollutants, searching global minima atmospheric nanoclusters, discovering heterogeneous or photochemical transformation pathways well environmentally relevant end points with wave functions descriptors are introduced discussed.

Language: Английский

Citations

41
The application of machine learning to air pollution research: A bibliometric analysis DOI Creative Commons
Yunzhe Li,

Zhipeng Sha,

Aohan Tang

et al.

Ecotoxicology and Environmental Safety, Journal Year: 2023, Volume and Issue: 257, P. 114911 - 114911

Published: April 15, 2023

Machine learning (ML) is an advanced computer algorithm that simulates the human process to solve problems. With explosion of monitoring data and increasing demand for fast accurate prediction, ML models have been rapidly developed applied in air pollution research. In order explore status applications research, a bibliometric analysis was made based on 2962 articles published from 1990 2021. The number publications increased sharply after 2017, comprising approximately 75% total. Institutions China United States contributed half all with most research being conducted by individual groups rather than global collaborations. Cluster revealed four main topics application ML: chemical characterization pollutants, short-term forecasting, detection improvement optimizing emission control. rapid development algorithms has capability characteristics multiple analyze reactions their driving factors, simulate scenarios. Combined multi-field data, are powerful tool analyzing atmospheric processes evaluating management quality deserve greater attention future.

Language: Английский

Citations

29
Global optimization of chemical cluster structures: Methods, applications, and challenges DOI Creative Commons
Jun Zhang, Vassiliki‐Alexandra Glezakou

International Journal of Quantum Chemistry, Journal Year: 2020, Volume and Issue: 121(7)

Published: Nov. 21, 2020

Abstract Chemical clusters are relevant to many applications in catalysis, separations, materials, and energy sciences. Experimentally, the structure of is difficult determine, but it very important understanding their chemistry properties. Computational methods can be used examine cluster structure, however finding most stable not simple, particularly as size increases. Global optimization techniques have long been tackle problem such approaches would look for a global minimum, while sampling local minima over whole potential surface well. In this review, state‐of‐the‐art theory summarized. First, definition, significance, relation experiments, brief history presented. We then discuss, more detail, three versatile methods: basin hopping, artificial bee colony algorithm, genetic algorithm. close with some representative application examples since 2016 challenges, open questions opportunities field.

Language: Английский

Citations

54
Dynamics of Heterogeneous Catalytic Processes at Operando Conditions DOI Creative Commons
Xiangcheng Shi, Xiaoyun Lin,

Ran Luo

et al.

JACS Au, Journal Year: 2021, Volume and Issue: 1(12), P. 2100 - 2120

Published: Nov. 4, 2021

The rational design of high-performance catalysts is hindered by the lack knowledge structures active sites and reaction pathways under conditions, which can be ideally addressed an in situ/operando characterization. Besides experimental insights, a theoretical investigation that simulates conditions─so-called operando modeling─is necessary for plausible understanding working catalyst system at atomic scale. However, there still huge gap between current widely used computational model concept modeling, should achieved through multiscale modeling. This Perspective describes various modeling approaches machine learning techniques step toward followed selected examples present thermo- electrocatalytic processes. At last, remaining challenges this area are outlined.

Language: Английский

Citations

53
Atmospheric clusters to nanoparticles: Recent progress and challenges in closing the gap in chemical composition DOI Creative Commons
James N. Smith, Danielle C. Draper,

Sabrina Chee

et al.

Journal of Aerosol Science, Journal Year: 2020, Volume and Issue: 153, P. 105733 - 105733

Published: Dec. 11, 2020

Language: Английский

Citations

48
Computational Tools for Handling Molecular Clusters: Configurational Sampling, Storage, Analysis, and Machine Learning DOI Creative Commons
Jakub Kubečka, Vitus Besel, Ivo Neefjes

et al.

ACS Omega, Journal Year: 2023, Volume and Issue: 8(47), P. 45115 - 45128

Published: Nov. 14, 2023

Computational modeling of atmospheric molecular clusters requires a comprehensive understanding their complex configurational spaces, interaction patterns, stabilities against fragmentation, and even dynamic behaviors. To address these needs, we introduce the Jammy Key framework, collection automated scripts that facilitate streamline cluster workflows. handles file manipulations between varieties integrated third-party programs. The framework is divided into three main functionalities: (1) for sampling (JKCS) to perform systematic clusters, (2) quantum chemistry (JKQC) analyze commonly used output files database construction, handling, analysis, (3) machine learning (JKML) manage methods in optimizing modeling. This automation utilization significantly reduces manual labor, greatly speeds up search configurations, thus increases number systems can be studied. Following example Atmospheric Cluster Database (ACDB) Elm (ACS Omega, 4, 10965–10984, 2019), modeled our group using have been stored an improved online GitHub repository named ACDB 2.0. In this work, present package alongside its assorted applications, which underline versatility. Using several illustrative examples, discuss how choose appropriate combinations methodologies treating particular types, including reactive, multicomponent, charged, or radical as well containing flexible multiconformer monomers heavy atoms. Finally, detailed tools acid–base clusters.

Language: Английский

Citations

11
Modified Halloysite as Catalyst for the Conversion of Hydroxymethylfurfural to Furandicarboxylic Acid: A DFT Investigation DOI
Marco Bertini, Francesco Ferrante,

Ludovico Guercio

et al.

ChemCatChem, Journal Year: 2024, Volume and Issue: 16(15)

Published: April 2, 2024

Abstract The reaction steps involved in the 5‐hydroxymethylfurfural to 2,5‐furandicarboxylic acid conversion by means of H 2 O were investigated employing a dedicated computational protocol based on density functional theory. catalytic environment choice was molecular model representing portion halloysite nanotube outer surface, functionalized an organosilane, 3‐aminopropyltriethoxysilane, whose amino group bonds one gold atom. At this stage investigation, process fully detailed terms interactions between intermediates and catalyst, standard free energies. In addition, energy barriers elementary involving hydrogen migration from adsorbed organic species atom analyzed. On basis interaction geometries, certain distinction among preferred path can be inferred as function net negative charge characterizing catalyst surface. Since inner surface represent needed obtain through dehydration fructose, present study is framed wider research field where possibility consider one‐pot reactor for valorization biomass explored.

Language: Английский

Citations

4