Results 161 to 170 of about 148,395 (284)

How Particle Size Affects Consolidation Behavior, Strain and Properties of Li6PS5Cl Fast Ionic Conductors

Advanced Energy Materials, EarlyView.
The densification process of Li6PS5Cl powders with varying particles size distributions reveals differences in smaller and larger distributions. Higher strain is revealed for the smaller particle size distribution from X‐ray diffraction. Discrete element method simulations uncover that the reason for the higher strain is not the particle size itself ...
Vasiliki Faka, Mohammed Alabdali, Martin A. Lange, Franco M. Zanotto, Can Yildirim, Mikael Dahl Kanedal, Jędrzej Kondek, Matthias Hartmann, Oliver Maus, Dominik Daisenberger, Michael Ryan Hansen, Jozef Keckes, Daniel Rettenwander, Alejandro A. Franco, Wolfgang G. Zeier   +14 more
wiley   +1 more source

Acoustic Metasurface for Space-time Reflection Manipulation. [PDF]

Adv Sci (Weinh)
Yang Y, Jia H, Lu J, Yang Y, Liu T, Yang J, Liu Z.   +6 more
europepmc   +1 more source

Experimental validation of the RESPONSE framework against cyberattacks on cyber‐physical process systems

AIChE Journal, EarlyView.
Abstract This work experimentally validates the RESPONSE (Resilient Process cONtrol SystEm) framework as a solution for maintaining safe, continuous operation of cyber‐physical process systems under cyberattacks. RESPONSE implements a dual‐loop architecture that runs a networked online controller in parallel with a hard‐isolated offline controller ...
Luyang Liu, Pu Du, Zaman Sajid, Benjamin Wilhite, Costas Kravaris, Faisal Khan   +5 more
wiley   +1 more source

Geometry-Based Bounds on the Capacity of Peak-Limited and Band-Limited Signals over the Additive White Gaussian Noise Channel at a High SNR. [PDF]

Entropy (Basel)
Peleg M, Shamai S.
europepmc   +1 more source

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source

RF-photonic deep learning processor with Shannon-limited data movement. [PDF]

Sci Adv
Davis R, Chen Z, Hamerly R, Englund D.
europepmc   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Finite set model predictive control of permanent magnet synchronous motor current based on super twisting sliding mode observer. [PDF]

PLoS One
Ren H, Su C, Long R.
europepmc   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Harnessing acoustic topology for dynamic control of liquid crystal defects. [PDF]

Nat Commun
Wu KH, Sun Z, Zhu LT, Li SS, Hu X, Liu QH, Chen LJ.   +6 more
europepmc   +1 more source