Lauren Takahashi

Latest

• Data in Materials and Catalysts Informatics
• Designing Catalyst Descriptors for Machine Learning in Oxidative Coupling of Methane
• Designing transformer oil immersion cooling servers for machine learning and first principle calculations
• Synthesis of Heterogeneous Catalysts in Catalyst Informatics to Bridge Experiment and High-Throughput Calculation
• The Rise of Catalysts Informatics
• 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 active catalysts for low temperature oxidative coupling of methane via machine learning and data mining
• Extraction of catalyst design heuristics from random catalyst dataset and their utilization in catalyst development for 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
• Catalyst Acquisition by Data Science (CADS): a web-based catalyst informatics platform for discovering catalysts
• Data-driven identification of the reaction network in oxidative coupling of the methane reaction via experimental data
• Multidimensional classification of catalysts in oxidative coupling of methane through machine learning and high-throughput data
• Representing the Methane Oxidation Reaction via Linking First-Principles Calculations and Experiment with Graph Theory
• Automatic oxidation threshold recognition of XAFS data using supervised machine learning
• Creating machine learning-driven material recipes based on crystal structure
• Data driven determination in growth of silver from clusters to nanoparticles and bulk
• High-throughput experimentation and catalyst informatics for oxidative coupling of methane
• The rise of catalyst informatics: towards catalyst genomics
• Visualizing scientists’ cognitive representation of materials data through the application of ontology
• Electronic structure of octagonal boron nitride nanotubes
• Functionalized Single-Atom-Embedded Bilayer Graphene and Hexagonal Boron Nitride
• Redesigning the materials and catalysts database construction process using ontologies
• Searching for hidden perovskite materials for photovoltaic systems by combining data science and first principle calculations
• Tuning the Electronic Structure of an Aluminum Phosphide Nanotube through Configuration of the Lattice Geometry
• Descriptors for predicting the lattice constant of body centered cubic crystal
• Designing Mg7 cluster-assembled two dimensional crystal
• Structural stability and electronic properties of an octagonal allotrope of two dimensional boron nitride
• Designing square two-dimensional gold and platinum
• Hydrophobic and antioxidant effects in In, Sn, and Sb based two dimensional materials
• Prediction of the dopant activity of chemical compounds against ammonia borane with key descriptors: electronegativity and crystal structures
• Reactivity of Two-Dimensional Au9, Pt9, and Au18Pt18 against Common Molecules
• Low temperature pollutant trapping and dissociation over two-dimensional tin
• Supporting Information- Low temperature pollutant trapping and dissociation over two-dimensional tin