Results 201 to 210 of about 7,731 (299)

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

Understanding Peelle's Pertinent Puzzle bias in generalized least squares regression through eigenspectrum analysis. [PDF]

Sci Rep
Walton NAW, Fritsch WN, Lewis AM, Forbes J, Neudecker D, Sobes V.   +5 more
europepmc   +1 more source

Laser‐Induced Graphene from Waste Almond Shells

Advanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova, Anna Chiara Bressi, Marina Galliani, Attilio Marino, Gianni Ciofani, Eduardo Machado‐Charry, Hilda Gomez Bernal, Alessandra Francini, Luca Sebastiani, Francesco Greco   +9 more
wiley   +1 more source

Geospatial Patterning of Hypertension and High Cholesterol Prevalence in Inland Southern California: An Ecological ZIP-Code-Level Study. [PDF]

Cureus
Andricioaei A, Bogdan A, Dutt E, Sodtuya S, Motamedi Azari A.   +4 more
europepmc   +1 more source

Counterion Dependent Side‐Chain Relaxation Stiffens a Chemically Doped Thienothiophene Copolymer

Advanced Functional Materials, EarlyView.
Oxidation of a thienothiophene copolymer, p(g3TT‐T2), via different doping strategies and dopant molecules resulted in materials with similar oxidation levels and a high electrical conductivity of ≈100 S cm−1. However, mechanical properties varied significantly, with sub‐glass transition temperatures and elastic moduli spanning from –44°C to –3°C and ...
Mariavittoria Craighero, Meghna Jha, Elsa Veronica Flores‐Vela, Joost Kimpel, Andreas Schaefer, Jiali Guo, Jesika Asatryan, Alberto Peinador Veiga, Shuichi Haraguchi, Per‐Anders Carlsson, Jaime Martín, Mariano Campoy‐Quiles, Christian Müller   +12 more
wiley   +1 more source

Center-specific causal inference with multicenter trials-Interpreting trial evidence in the context of each participating center. [PDF]

Stat Methods Med Res
Robertson SE, Steingrimsson JA, Joyce NR, Stuart EA, Dahabreh IJ.   +4 more
europepmc   +1 more source

Intermediate Resistive State in Wafer‐Scale Vertical MoS2 Memristors Through Lateral Silver Filament Growth for Artificial Synapse Applications

Advanced Functional Materials, EarlyView.
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa, Milan Buttberg, Ke Ran, Rana Walied Ahmad, Dennis Braun, Lukas Völkel, Jimin Lee, Sofía Cruces, Bart Macco, Bárbara Canto, Holger Lerch, Thorsten Wahlbrink, Holger Kalisch, Michael Heuken, Andrei Vescan, Joachim Mayer, Zhenxing Wang, Ilia Valov, Stephan Menzel, Max C. Lemme   +19 more
wiley   +1 more source

Robust Distributed High-Dimensional Regression: A Convoluted Rank Approach. [PDF]

Entropy (Basel)
Wu M.
europepmc   +1 more source

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

Identifying the Best Predictive Biomarker in Pharmacogenomics Through Multiple Comparisons With the Best. [PDF]

Biom J
Zhai S, Shen J, Hsu JC, Cui X.
europepmc   +1 more source