Results 211 to 220 of about 98,405 (300)

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

Artificial intelligence approaches in biological age prediction: current status and challenges. [PDF]

Br J Biomed Sci
Wang G, Ding P, Li Z, Tang Q, Tu L, Jiang T, Zhang L, Su B, Xu J, An H.   +9 more
europepmc   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

Characterizing gene perturbations in single cells via network divergence analysis. [PDF]

Nat Commun
Huang C, Li Y, Fa B, Zhu J, Liu Z, Ma Y, Zhang Z, Xu Y, Xu Q, Xiao Z.   +9 more
europepmc   +1 more source

Extrusion‐Based Additive Manufacturing of Advanced Ceramics: Strengthening Mechanisms and Process Optimization Review

Advanced Engineering Materials, EarlyView.
This review comprehensively evaluates extrusion‐based additive manufacturing for advanced ceramics, detailing feedstock options and key process parameters. By critically addressing defect mechanisms like porosity and cracking, the work highlights optimization strategies through machine learning and advanced postprocessing.
Meisam Bakhtiari, Mohammad Hadi Sheikh‐Ansari, Avinash Borgaonkar, Mehran Dadkhah, Abdollah Saboori   +4 more
wiley   +1 more source

Decoding Skin Aging Through Transcriptomic Clocks: Gene Expression Signatures, Associated Pathways, and Explainable AI. [PDF]

Genes (Basel)
Kefala V, Grech VS, Tertipi N, Sfyri E, Beloukas A, Rallis E.   +5 more
europepmc   +1 more source

Enhancing Fatigue Crack Growth Resistance in Heterostructured Aluminum Bimetals by Tailored Interface Design

Advanced Engineering Materials, EarlyView.
Different Al/Al bimetals with a single engineered interface reveal how mechanical mismatch governs fatigue crack growth under cyclic loading. Additionally, loading–unloading–reloading tests link the microyielding behavior to the fatigue crack growth resistance, while crack‐path analysis reveals toughening mechanisms at the interface, highlighting ...
Sebastian Vollath, Philip Manuel Pohl, Heinz Werner Höppel   +2 more
wiley   +1 more source

Beyond Oncogenes: Selectively Targeting Whole-Tumor Cell Growth Regulation. [PDF]

Drug Des Devel Ther
Qin A.
europepmc   +1 more source

Composites of Shellac and Silver Nanowires as Flexible, Biobased, and Corrosion‐Resistant Transparent Conductive Electrodes

Advanced Functional Materials, EarlyView.
Shellac, a centuries‐old natural resin, is reimagined as a green material for flexible electronics. When combined with silver nanowires, shellac films deliver transparency, conductivity, and stability against humidity. These results position shellac as a sustainable alternative to synthetic polymers for transparent conductors in next‐generation ...
Rahaf Nafez Hussein, Tiago Carneiro Gomes, Eliza Ng, Simon Rondeau‐Gagné, Tricia Breen Carmichael   +4 more
wiley   +1 more source

Challenges and Advances in Bioinformatics and Computational Biology. [PDF]

Curr Issues Mol Biol
Si T, Gong H.
europepmc   +1 more source