Results 171 to 180 of about 26,300 (238)

Data‐Driven Review and Machine Learning Prediction of Diamond Vacancy Center Synthesis

Advanced Intelligent Systems, EarlyView.
A machine learning framework is applied to photoluminescence spectra to extract linewidths and uncover how NV, SiV, GeV, and SnV centers evolve with growth and processing conditions. Unified normalization and k‐fold validation reveal cross‐method trends and enable rapid prediction of defect size and fabrication parameters, offering a data‐driven route ...
Zhi Jiang, Marco Peres, Carlo Bradac, Gil Gonçalves   +3 more
wiley   +1 more source

Design of Fe-Co-Cr-Ni-Mn-Al-Ti Multi-Principal Element Alloys Based on Machine Learning. [PDF]

Materials (Basel)
Xu X, He Z, Zheng K, Che L, Zhao F, Hua D.   +5 more
europepmc   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Intrinsic direct air capture. [PDF]

Chem Sci
McDannald A, Siderius DW, DeCost B, Choudhary K, Ortiz-Montalvo DL.   +4 more
europepmc   +1 more source

A compact model of Escherichia coli core and biosynthetic metabolism. [PDF]

PLoS Comput Biol
Corrao M, He H, Liebermeister W, Noor E, Bar-Even A.   +4 more
europepmc   +1 more source

Machine Learning-Based Multi-Objective Composition Optimization of High-Nitrogen Austenitic Stainless Steels. [PDF]

Materials (Basel)
Wang Y, Chen L, Cheng L, Wang E, Sheng Z, Zhang L.   +5 more
europepmc   +1 more source

Predicting and Validating the Performance of Zn-Al-Mg Coatings through an Integrated Thermodynamic, Molecular Dynamics, and Electrochemical Approach. [PDF]

ACS Omega
Chaouki A, Ben Ali M, Cifuentes SC, Bedmar J, Rams J, Tsipas SA, Sahir Z, Benabdallah I, El Fatimy A, Naamane S.   +9 more
europepmc   +1 more source

Hydrogen Activation via Dihydride Formation on a Rh1/Fe3O4(001) Single‐Atom Catalyst

Angewandte Chemie International Edition, EarlyView.
Deuterium (hydrogen) adsorption on single‐atom Rh1/Fe3O4(001) catalyst does not induce D (H) spillover onto the reducible Fe3O4 support. Instead, a Rh1‐dihydride (Rh−2D or Rh−2H) species forms and D2 or H2desorbs during annealing. ABSTRACT Hydrogen activation is a key elementary step in catalytic hydrogenation.
Chunlei Wang, Panukorn Sombut, Lena Puntscher, Nail Barama, Maosheng Hao, Florian Kraushofer, Jiri Pavelec, Matthias Meier, Florian Libisch, Michael Schmid, Ulrike Diebold, Cesare Franchini, Gareth S. Parkinson   +12 more
wiley   +1 more source

novoStoic2.0: An integrated framework for pathway synthesis, thermodynamic evaluation, and enzyme selection. [PDF]

PLoS Comput Biol
Upadhyay V, Anand M, Maranas CD.
europepmc   +1 more source

Thermo-Flux: generation and analysis of comprehensive thermodynamic-stoichiometric metabolic network models

Smith EN, Fargier N, Losa J, Heinemann M.   +3 more
europepmc   +1 more source