Toshiaki Taniike

Latest

• The value of negative results in data-driven catalysis research
• Catalyst Informatics: Paradigm Shift towards Data-Driven Catalyst Design
• Designing Catalyst Descriptors for Machine Learning in Oxidative Coupling of Methane
• High-throughput screening and literature data-driven machine learning-assisted investigation of multi-component La 2 O 3-based catalysts for the oxidative coupling of methane
• Machine Learning-Aided Catalyst Modification in Oxidative Coupling of Methane via Manganese Promoter
• Catalysis Gene Expression Profiling: Sequencing and Designing Catalysts
• Constructing catalyst knowledge networks from catalyst big data in oxidative coupling of methane for designing catalysts
• Direct Design of Catalysts in Oxidative Coupling of Methane via High-Throughput Experiment and Deep Learning
• Extraction of catalyst design heuristics from random catalyst dataset and their utilization in catalyst development for oxidative coupling of methane
• Factors to influence low-temperature performance of supported Mn--Na2WO4 in oxidative coupling of methane
• Learning catalyst design based on bias-free data set for oxidative coupling of methane
• Representing catalytic and processing space in methane oxidation reaction via multioutput machine learning
• rsc. li/chemical-science
• Unveiling gas-phase oxidative coupling of methane via data analysis
• Multidimensional classification of catalysts in oxidative coupling of methane through machine learning and high-throughput data