首页|期刊导航|燃料化学学报(中英文)|过渡金属单晶表面CO-TPD谱图的标准化数据集

过渡金属单晶表面CO-TPD谱图的标准化数据集OA

A standardized dataset of CO-TPD spectra on transition-metal single-crystal surfaces

中文摘要英文摘要

程序升温脱附(TPD)是表征表面吸附行为的关键实验技术,能够获取吸附能等关键参数,在多相催化研究中具有广泛应用.然而,现有TPD数据多以图像形式呈现,缺乏系统、数值化的数据集,限制其定量分析与理论建模的潜力.CO作为典型探针分子,其TPD谱图可用于识别表面活性位点,是研究金属表面性质的有效手段.本研究构建了一个涵盖Cu、Ru等14种过渡金属单晶表面的CO-TPD数据集.通过提取文献谱图的数值点并进行归一化处理,完整保留了峰形等关键信息.数据集中还包含升温速率等实验参数,并建立了标准化的数据采集与质量控制流程.该数据集不仅可作为"指纹谱图库"用于复杂催化剂TPD谱图解卷积,还可作为实验基准,用于理论模型的参数校正.本工作为表面科学与催化研究提供了可靠的数据基础,有助于催化剂活性中心的微观解析与理性设计.

Temperature-programmed desorption(TPD)is a fundamental technique in surface science and heterogeneous catalysis for characterizing adsorption behavior,and for extracting key parameters such as adsorption energy.However,the majority of existing TPD data is accessible in the form of published images,which lacks structured and quantitative datasets.This constrains its utility for rigorous quantitative analysis and computational modelling.Using carbon monoxide(CO)which is a widely adopted probe molecule,a curated and standardized dataset of CO-TPD is constructed,encompassing 14 transition-metal single-crystal surfaces,including copper(Cu)and ruthenium(Ru).By systematically extracting numerical data points from published spectra and applying normalization,essential spectral features such as peak shape are fully preserved.The dataset also documents relevant experimental parameters,including heating rates,and was developed using a standardized protocol for data collection and quality control.This resource serves as both a reference library to support the deconvolution of TPD spectra from complex catalysts and an experimental benchmark for calibrating parameters in theoretical models.By providing a reliable and accessible data function,this work advances the microscopic understanding and the rational design of catalyst active centers.

杨琳;武江红;王鹤

山西财经大学统计学院,山西太原 030006山西能源学院能源化学与材料工程系,山西晋中 030600中国科学院山西煤炭化学研究所煤炭高效低碳利用全国重点实验室,山西太原 030001

化学化工

CO-TPD标准化数据集过渡金属单晶表面

CO-TPDstandardized datasettransition metalsingle-crystal surfaces

《燃料化学学报(中英文)》 2026 (4)

180-190,11

Supported by the Robotic AI-Scientist Platform of Chinese Academy of Sciences,National Natural Science Foundation of China(22372185),Youth Talent Development Program of SKLCC(2025BWZ009),Natural Science Foundation of Shanxi Province(202203021221219),Research on the Construction of Scientific and Technological Innovation Think Tank of Shanxi Association for Science and Technology(KXKT202542).

10.1016/S1872-5813(26)60673-1

评论