Results 211 to 220 of about 522,455 (311)

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Accelerating the Structure Exploration of Diverse Bi-Pt Nanoclusters via Physics-Informed Machine Learning Potential and Particle Swarm Optimization. [PDF]

Chemphyschem
Vangheluwe R, Clavaguéra C, Truong MT, Domin D, Pham HC, Marinica MC, Van-Oanh NT.   +6 more
europepmc   +1 more source

Liquid Phase Transmission Electron Microscopy: A Window into the Early Stages of Complex Material Formation

Advanced Functional Materials, EarlyView.
Liquid‐phase transmission electron microscopy enables direct observation of nucleation and growth processes in solution. This review is dedicated to the remembrance of Helmut Cölfen and highlights recent studies on complex materials—oxides, biominerals, organic–inorganic crystals—which were central to his research activity. It summarizes key milestones,
Charles Sidhoum, Vinavadini Ramnarain, Nathaly Ortiz Peña, Dris Ihiawakrim, Clément Sanchez, Ovidiu Ersen   +5 more
wiley   +1 more source

Machine Learning Potential Analysis of Structural Transition in Cu and Ag Nanoparticles: From Icosahedral to Face-Centered Cubic. [PDF]

J Chem Theory Comput
Yang Y, Han J, Viñes F, Illas F.
europepmc   +1 more source

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Unraveling disorder-to-order transitions and chemical ordering in PtCoM ternary alloys using machine learning potential. [PDF]

Chem Sci
Niu X, Zhen S, Zhang R, Li J, Zhang L.
europepmc   +1 more source

Achieving High ON State Current through Ferroelectric Polarization‐Dependent Interfacial Resistance Switching in Undoped Orthorhombic HfO2 Films

Advanced Functional Materials, EarlyView.
Ferroelectric tunnel junction devices based on epitaxial undoped ferroelectric HfO2 films demonstrate stable switching endurance of over 106 switching cycles, low write voltages of ±3 V, 16 measured resistance states, and neuromorphic capability.
Markus Hellenbrand, Nuno Estrócio, Ji S. Kim, Babak Bakhit, Marian C. Istrate, Corneliu Ghica, Tiago Rebelo, Nives Strkalj, Abin Varghese, Bernardo Almeida, Luís S. Marques, Bipin Rajendran, Judith L. MacManus‐Driscoll, José P. B. Silva   +13 more
wiley   +1 more source

Transferability of MACE Graph Neural Network for Range Corrected Δ-Machine Learning Potential QM/MM Applications. [PDF]

J Phys Chem B
Giese TJ, Zeng J, York DM.
europepmc   +1 more source

Texoskeletons: Developing the Fundamental Technologies for Creating Intelligent Soft Robotic Clothing With Integrated 1D Sensors and Actuators

Advanced Functional Materials, EarlyView.
ABSTRACT Traditional wearable exoskeletons rely on rigid structures, which limit comfort, flexibility, and everyday usability. This work introduces the fundamental technologies to create the first soft, lightweight, intelligent textile‐based exoskeletons (Texoskeletons) built using 1D sensors and actuators.
Amy Lukomiak, Rameesh Bulathsinghala, Jack Varga, Shuxin Meng, Kalana Marasinghe, Imaad Refai, Biyon Fernando, Amitkumar Patel, Chamika M. Halloluwa‐Arachchige, Carlos Oliveira, Arash M. Shahidi, Zahra Rahemtulla, Alexander Turner, Ziyun Ding, Bernard X. W. Liew, Andy Kerr, Ezio Preatoni, Theo Hughes‐Riley, Ishara Dharmasena, Pasindu Lugoda   +19 more
wiley   +1 more source

Revisiting Aspirin Polymorphic Stability Using a Machine Learning Potential. [PDF]

ACS Omega
Hattori S, Zhu Q.
europepmc   +1 more source