Results 21 to 30 of about 7,593 (215)

Traction Force Microscopy for Viscoelastic Substrates: A Semi‐Analytical Method

Advanced Science, EarlyView.
A semi‐analytical viscoelastic traction force microscopy framework is introduced for quantifying time‐resolved cell tractions on flat finite‐thickness substrates. The method generalizes elastic traction force microscopy to Generalized Maxwell materials, identifies when elastic approximations remain valid and, when they do not, shows that inferred ...
Adrià Villacrosa‐Ribas, Daniëlle C. A. Duffhues, Pim van den Bersselaar, Sarah Pragnere, Bart G. W. Groenen, Mariana Azevedo Gonzalez Oliva, Giuseppe Ciccone, Manuel Salmeron‐Sanchez, Carlijn V. C. Bouten, Jose J. Muñoz, Vito Conte   +10 more
wiley   +1 more source

A Triple‐Nanoparticle System for Controlled Graphene Nanosheet Stacking: Enabling K/Na‐Ion Battery Anodes with Ultra‐Fast Charging Exceeding Petroleum Vehicle Refueling

Advanced Science, EarlyView.
ABSTRACT Large‐ion (K, Na) battery systems mitigate uneven global lithium distribution, while their ability to attain recharge time shorter than refueling would remove the final barrier for secondary batteries to replace petroleum vehicles. However, their large‐ion chemistry makes ultra‐fast charging an even significant challenge.
Shukai Ding, Le Zhang, Hang Li, Yang Zhang, Guoquan Suo, Bin Han, Dongfeng Sun, Wenqi Zhao, Gaohui Du, Qingmei Su, Bingshe Xu, Zhen Xu, Wei Wang   +12 more
wiley   +1 more source

Multiscale Architecture and Mechanics of the Cell Nucleus: Implications for Disease, Bioengineering and Nanomedicine

Advanced Science, EarlyView.
Nuclear mechanical properties are inherently scale‐dependent, arising from a hierarchical architecture that spans DNA, chromatin, the nuclear envelope, and condensates. Experimental techniques and theoretical models are integrated into a cohesive multiscale framework linking nanoscale structural features to organelle‐level mechanical behavior.
Xinran Liu, Xin Chen, Qingyang Zhao, Weikang Tan, Lingrui Zhu, Kin Liao, Vincent Chan, Nicolae Goga, Winfred O. Larkotey, Yang Li, Yinghui Shi, Wenya Shu, Lin Wang, Weiqing Wang, Tian Jian Lu, Yulong Han   +15 more
wiley   +1 more source

Making Sweat Measurable: Induction, Sampling, and Refreshment in Wearable Biofluid Sensing

Advanced Science, EarlyView.
Wearable sweat sensing relies not only on chemical detection but also on controlled biofluid management. This Review integrates sweat physiology, induction strategies, and microfluidic sampling architectures, demonstrating how flux, transport, and refreshment shape measurement reliability.
Soyoung Shin, Wei Gao
wiley   +1 more source

Enhanced Stability in Zero‐Excess Li‐Metal Batteries via Prelithiated Carbon Nanofiber Interlayers

Advanced Science, EarlyView.
Carbon nanofibers carbonized at 700°C show Li metal deposition predominantly on the side facing the Cu current collector. During delithiation, Li agglomerates remain as inactive lithium on the fiber surface. This behavior can be changed by a modified n‐Buli prelithiation without a washing step, suppressing dead Li formation and therefore enabling ...
Sandro Schöner, Marius Ast, Vera Michaela Barysch, Rebecca Erkes, Jule Meier‐Merziger, Pengfei Cao, Joachim Mayer, Josef Granwehr, Fabian Jeschull, Hermann Tempel, Shicheng Yu, Rüdiger‐A. Eichel   +11 more
wiley   +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

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
wiley   +1 more source

Classroom note: Fourier method for Laplace transform inversion [PDF]

Journal of Applied Mathematics and Decision Sciences, 2001
A method is described for inverting the Laplace transform. The performance of the Fourier method is illustrated by the inversion of the test functions available in the literature. Results are shown in the tables.
openaire   +1 more source

ParamNet: A Physics‐Guided Deep Learning Framework for Intelligent Self‐Inversion of Vacuum Optical Levitation Systems

Advanced Intelligent Systems, EarlyView.
A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng, Wenfeng Fan, Feng Li, Jian Wu, Wei Quan   +4 more
wiley   +1 more source