金属纳米催化剂设计数据库

实现基于描述符的催化剂理性设计对于开发新的面向能源和环境催化应用的催化材料具有重要意义。本数据库包括 1252 个能量数据，并基于 323 个金属-载体对进行动力学模拟，产生了大量理论与计算数据。使用了Vienna Ab initio Simulation Package(VASP)第一性原理计算程序对金属原子在金属表面上的扩散势垒和结合能、Ag(100)负载的MgO薄膜的粘附能和结合能、不同厚度的银负载氧化镁(100)薄膜与Au膜的黏附能和Au原子的结合能等进行了DFT计算。除此之外还大量收集了来自文献的金属原子在载体上的扩散势垒和结合能， 24 个金属表面原子在61 个金属表面上的74个自结合能数据，15个原子在76个金属表面上的126个自扩散势垒等数据，并且采集了相应实验上的数据。基于负载金属纳米粒子与载体的结合和金属原子与载体的结合能作为描述符，实现了单组分单功能催化剂载体和双功能双组分催化剂载体（1646种）的筛选。基于负载金属纳米粒子与载体的结合和金属原子与载体的结合能作为描述符，实现了单组分单功能催化剂载体和双功能双组分催化剂载体（1646种）的筛选。发现的描述符：分子表面吸附耦极矩、金属与氧化物载体中金属成键、金属与氧化物载体中氧成键、金属与载体的界面粘附能、金属原子与载体的吸附能、金属粒子在载体表面的接触角、金属的体相内聚能、金属的表面能、金属表面配位数、分子在金属表面的吸附能、电子自旋、光谱指纹、原子耦合分子配体数、金属粒子尺寸和分子吸附电耦极矩、金属原子与载体的结合能、约化后的金属原子与载体结合能、金属纳米催化剂的尺寸分布的标准偏差、分子在金属表面上吸附的振动频率、电子化合物与石墨烯单原子的电荷转移、金属自旋磁矩、金属的配位几何结构、红外光谱振动模式、拉曼光谱振动模式、核磁共振谱位移值、金属的电负性、金属的极化电荷。这些描述符的发现和确认对于描述和预测分子在催化剂的活化、金属自身的表面流动、金属粒子在载体表面的浸润扩散和烧结动力学具有重要意义。

Rational design of descriptor-based catalysts is of great significance for developing novel catalytic materials for energy and environmental catalytic applications. This database contains 1252 energy data points, and conducted kinetic simulations based on 323 metal-support pairs, generating a large amount of theoretical and computational data. The Vienna Ab initio Simulation Package (VASP), a first-principles calculation program, was used to perform DFT calculations for the diffusion barriers and binding energies of metal atoms on metal surfaces, the adhesion energies and binding energies of MgO films supported on Ag(100), the adhesion energies of MgO(100) films supported on Ag with different thicknesses and Au films, and the binding energies of Au atoms, etc. In addition, a large number of data on diffusion barriers and binding energies of metal atoms on supports from literature were collected, including 74 self-binding energy data points of 24 metal surface atoms on 61 metal surfaces, 126 self-diffusion barrier data points of 15 atoms on 76 metal surfaces, as well as corresponding experimental data. Using the binding between supported metal nanoparticles and supports and the binding energy between metal atoms and supports as descriptors, screening of single-component single-functional catalyst supports and bifunctional two-component catalyst supports (1646 types) was achieved. Using the binding between supported metal nanoparticles and supports and the binding energy between metal atoms and supports as descriptors, screening of single-component single-functional catalyst supports and bifunctional two-component catalyst supports (1646 types) was achieved. Identified descriptors include: dipole moment of molecular surface adsorption, metal-metal bonding in oxide supports, metal-oxygen bonding in oxide supports, interfacial adhesion energy between metals and supports, adsorption energy of metal atoms on supports, contact angle of metal particles on support surfaces, bulk cohesive energy of metals, surface energy of metals, coordination number of metal surfaces, adsorption energy of molecules on metal surfaces, electron spin, spectral fingerprints, number of atom-coupled molecular ligands, metal particle size and dipole moment of molecular adsorption, binding energy between metal atoms and supports, reduced binding energy between metal atoms and supports, standard deviation of size distribution of metal nanocatalysts, vibration frequency of molecules adsorbed on metal surfaces, charge transfer between electron compounds and graphene single atoms, metal spin magnetic moment, coordination geometry of metals, infrared spectral vibration modes, Raman spectral vibration modes, nuclear magnetic resonance spectral shift values, electronegativity of metals, and polarized charge of metals. The discovery and validation of these descriptors are of great significance for describing and predicting the activation of molecules on catalysts, the surface migration of metals themselves, the wetting diffusion and sintering kinetics of metal particles on support surfaces.

搜集汇总

背景与挑战

背景概述

该数据集是一个专注于金属纳米催化剂设计的数据库，包含1252个能量数据和基于323个金属-载体对的动力学模拟数据，通过第一性原理计算和文献收集，提供了扩散势垒、结合能等关键参数。数据集基于金属与载体的相互作用描述符，实现了对单组分和双功能催化剂的筛选，共涉及1646种载体，旨在支持催化材料的理性设计和性能预测。