Results 191 to 200 of about 1,242,716 (272)

A machine learning approach to wastewater treatment: Gaussian process regression and Monte Carlo analysis. [PDF]

Nanoscale Adv
Nadeem N, Khaliq Z, Bentalib A, Qadir MB, Ahmad F, Shahzad MW, Jumah AB.   +6 more
europepmc   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

DMoVGPE: predicting gut microbial associated metabolites profiles with deep mixture of variational Gaussian Process experts. [PDF]

BMC Bioinformatics
Weng Q, Hu M, Peng G, Zhu J.
europepmc   +1 more source

Mixed‐Metal Promotion in a Manganese‐Molybdenum Oxynitride as Catalyst to Integrate C─C and C─N Coupling Reactions for the Direct Synthesis of Acetonitrile from Syngas and Ammonia

Advanced Materials, EarlyView.
Transition metal oxy/carbo‐nitrides show great promise as catalysts for sustainable processes. A Mn‐Mo mixed‐metal oxynitride attains remarkable performance for the direct synthesis of acetonitrile, an important commodity chemical, via sequential C─N and C─C coupling from syngas (C1) and ammonia (N1) feedstocks.
M. Elena Martínez‐Monje, Wilson Henao, Tania Rodenas, Patricia Concepción, Virginia Pérez Dieste, Alexander Missyul, Giovanni Agostini, Gonzalo Prieto   +7 more
wiley   +1 more source

Precise small deviations in L 2 of some Gaussian processes appearing in the regression context

Open Mathematics, 2014
Kirichenko Alisa, Nikitin Ya.
doaj   +1 more source

Sea Surface Temperature Prediction Enhanced by Exploring Spatiotemporal Correlation Based on LSTM and Gaussian Process. [PDF]

Sensors (Basel)
Li Z, Zhu Q, Zhang D, Wu H, Peng Y.
europepmc   +1 more source

Kelvin Probe Force Microscopy in Bionanotechnology: Current Advances and Future Perspectives

Advanced Materials, EarlyView.
Kelvin probe force microscopy (KPFM) enables the nanoscale mapping of electrostatic surface potentials. While widely applied in materials science, its use in biological systems remains emerging. This review presents recent advances in KPFM applied to biological samples and provides a critical perspective on current limitations and future directions for
Ehsan Rahimi, Mario Palacios‐Corella, Arjan Mol, Salvador Pané, Josep Puigmartí‐Luis   +4 more
wiley   +1 more source

Modeling Many-Body Interactions in Water with Gaussian Process Regression. [PDF]

J Phys Chem A
Manchev YT, Popelier PLA.
europepmc   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Toward Gaussian Process Regression Modeling of a Urea Force Field. [PDF]

J Phys Chem A
Bukowy T, Brown ML, Popelier PLA.
europepmc   +1 more source