Results 91 to 100 of about 561 (185)

From Flexible to Conformable Pressure Sensors: Mechanisms, Materials, and Biomedical Applications

Advanced Electronic Materials, EarlyView.
This review highlights recent progress, challenges and future opportunities in pressure sensing for advanced biomedical applications. We summarize key transduction mechanisms and emerging material strategies, discuss representative wearable and implantable applications for continuous physiological monitoring and provide a focused perspective on barrier
Rishabh B. Mishra, Andrea Ottomaniello, Virgilio Mattoli   +2 more
wiley   +1 more source

On the Modeling of Nonlinear Wind-Induced Ice-Drift Ocean Currents at the North Pole. [PDF]

J Math Fluid Mech
Puntini C.
europepmc   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Artificial Intelligence Informed Hydrogel Biomaterials in Additive Manufacturing. [PDF]

Gels
Zhang Z, Tao ZZ, Du R, Huo R, Zheng X.
europepmc   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Numerical Investigation of Buckling Behavior of MWCNT-Reinforced Composite Plates. [PDF]

Materials (Basel)
Singh J, Kumar A, Sadowska-Buraczewska B, Andrzejuk W, Barnat-Hunek D.   +4 more
europepmc   +1 more source

Modeling the separation of water‐in‐oil emulsions in continuously fed gravity settlers using millifluidic experiments

AIChE Journal, EarlyView.
Abstract Emulsion separation remains a persistent challenge in chemical and process industries due to the metastable nature of dispersed droplets. In gravity separators, the overall separation rate is governed by the formation of a densely packed zone (DPZ) of deforming and coalescing droplets that mediates between the dispersed and continuous phases ...
Andrei Zlobin, José Esteban Andino‐Enriquez, Thomas Gouëzec, Maurice Bourrel, Enric Santanach‐Carreras, Nicolas Passade‐Boupat, Laurence Talini, François Lequeux, Pascal Panizza   +8 more
wiley   +1 more source

Modification of a poroelastic model for zero porosity: finite element implementation and investigation of fluid mechanics in the perivascular space. [PDF]

Biomech Model Mechanobiol
Jannesari M, Ghitti B, Gluckman BJ, Costanzo F.   +3 more
europepmc   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Mechanistic neural operator framework for multi-objective optimization of Ti-6Al-4 V metal matrix composites. [PDF]

Sci Rep
Lakshmaiya N, Chakrapani G, Sagar V, Rajendran A, Maranan R, Rajhi AA, Duhduh AA, Khan WA.   +7 more
europepmc   +1 more source