Results 171 to 180 of about 613,067 (261)

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Responses of Groundwater Bacterial Communities to Extreme Rainfall in the Western North China Plain Based on 16S rRNA Sequencing. [PDF]

Microorganisms
Gao Y, Li S, An R, Zhang Y, Piao H, Tai T, Zhu Q, Su Q, Fei Y, Han C, Li W, Liu K.   +11 more
europepmc   +1 more source

Enhancement of the Through‐Thickness Electrical Conductivity of Carbon‐Fiber‐Reinforced Plastics Using Large Graphite Particles

Advanced Engineering Materials, EarlyView.
To enhance through‐thickness conductivity without sacrificing impregnation, large spherical graphite particles are intentionally employed in a low‐viscosity resin. Unlike finer conductive fillers, these particles remain outside the fiber bundles and accumulate in resin‐rich interlaminar regions during molding.
Keito Hosoe, Yu Zhou, Shintaro Kamiyama, Takao Okada, Tomohiro Yokozeki, Ryoma Tokonami, Tatsuhiro Takahashi   +6 more
wiley   +1 more source

Natural and Technological Risk Analysis in European Cross-Border Regions: An Integrated Approach to Hazards and Vulnerability. [PDF]

Risk Anal
Lopes D, De Diego E, Àgueda A, Almeida M, Ribeiro LM, Torres L, Lopes M, Miranda AI.   +7 more
europepmc   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

Enhancing Arabica and Robusta coffee prices forecasting through machine learning approaches. [PDF]

Sci Rep
Suela MM, Nascimento M.
europepmc   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source

Understanding preparedness for extreme weather events among adults with chronic diseases: the interplay of illness perceptions, threat appraisal, and weather-related worry. [PDF]

Front Public Health
Hamama-Raz Y, Shinan-Altman S.
europepmc   +1 more source

Enhancing Low‐Temperature Performance of Sodium‐Ion Batteries via Anion‐Solvent Interactions

Advanced Functional Materials, EarlyView.
DOL is introduced into electrolytes as a co‐solvent, increasing slat solubility, ion conductivity, and the de‐solvent process, and forming an anion‐rich solvent shell due to its high interaction with anion. With the above virtues, the batteries using this electrolyte exhibit excellent cycling stability at low temperatures. Abstract Sodium‐ion batteries
Cheng Zheng, Qian Yao, Yanan Sun, Hongyu Lv, Zhongchao Bai, Guoliang Zhang, Nana Wang, Jian Yang   +7 more
wiley   +1 more source

A Vision Transformer- and Radiomics-based Model for Predicting Liver Metastasis-Free Survival in Patients with Rectal Cancer. [PDF]

Radiol Imaging Cancer
Li Z, Sun C, Wang X, Tian S, Ye Z.
europepmc   +1 more source