Results 211 to 220 of about 167,650 (307)

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Advanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof Wöll   +5 more
wiley   +1 more source

Field Performance and Calibration Strategies for Low-Cost Capacitive Soil Moisture Sensors. [PDF]

Sensors (Basel)
Strypsteen G, Persson M, Miroshnychenko M, Rakonjac N.   +3 more
europepmc   +1 more source

A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons

Advanced Intelligent Discovery, EarlyView.
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam, Ogheneyoma Aghoghovbia, Mohammed Al‐Fahdi, Lingyu Kong, Victor Fung, Ming Hu   +5 more
wiley   +1 more source

Validation of the Effectiveness of Visual Feedback Systems in Respiratory Gating Carbon Ion Radiation Therapy. [PDF]

Int J Part Ther
Umetani R, Miyasaka Y, Souda H, Chai H, Ishizawa M, Hagiwara Y, Kaneko T, Yamazawa Y, Sato H, Koto M, Iwai T.   +10 more
europepmc   +1 more source

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

Integrating NSGA-II and TOPSIS for Stacking Model Optimization in Pursuit of Halide Double Perovskite Screening. [PDF]

Materials (Basel)
Liang G, Zhang J.
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

A machine learning-coupled APSIM model pipeline for projected oil palm yield in Surat Thani, Thailand. [PDF]

PLoS One
Jantaraprasit N, Promchote P, Wang SS, Daengnui S, Motlagh SK, de Lima Moraes AG, França L, Yoon JH, Phumichai C, Kittipadakul P.   +9 more
europepmc   +1 more source

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source

Body placement of inertial measurement units differentially affects physical activity assessment accuracy in drug-naïve Parkinson's disease. [PDF]

Sci Rep
Maetzler C, Abedinifar M, Vinod V, Welzel J, Schaeffer E, Yilmaz R, Hobert MA, Hansen C, Durif F, Corvol JC, Rascol O, Behnke S, Poewe W, Zeuner KE, Ruzicka E, Ferreira JJ, Romijnders R, Berg D, Devos D, Moreau C, Hopfner F, Maetzler W.   +21 more
europepmc   +1 more source