Results 181 to 190 of about 1,603 (258)

Morphogenesis of spin cycloids in a noncollinear antiferromagnet. [PDF]

Proc Natl Acad Sci U S A
Ojha SK, Pal P, Prokhorenko S, Husain S, Ramesh M, Li X, Kang D, Meisenheimer P, Schlom DG, Stevenson P, Caretta L, Nahas Y, Han Y, Martin LW, Bellaiche L, Eom CB, Ramesh R.   +16 more
europepmc   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

Advanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison, Kevin Nadaud, Josquin Harrison, Guillaume F. Nataf, Laura Bégon‐Lours   +4 more
wiley   +1 more source

Dispersive determination of nucleon gravitational form factors. [PDF]

Nat Commun
Cao XH, Guo FK, Li QZ, Yao DL.
europepmc   +1 more source

Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture

Advanced Intelligent Systems, EarlyView.
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen, Ali Çalhan, Murtaza Cicioğlu, Oğuzhan Demiryürek   +3 more
wiley   +1 more source

QCD challenges from pp to AA collisions: 4th edition. [PDF]

Eur Phys J C Part Fields
Altmann J, Andres C, Andronic A, Antinori F, Antonioli P, Beraudo A, Berti E, Bianchi L, Boettcher T, Capriotti L, Christiansen P, Contreras Nuño JG, Cunqueiro Mendez L, da Silva C, Dainese A, Dembinski HP, Dobrigkeit Chinellato D, Dubla A, Faggin M, Flett C, Greco V, Grishmanovskii I, Holguin J, Kanakubo Y, Kim DJ, Lea R, Lee SH, Mariani S, Matyja A, Mazeliauskas A, Minissale V, Morsch A, Oliva L, Orusa L, Paakkinen P, Pablos D, Paić G, Pierog T, Plumari S, Prino F, Rossi A, Sestini L, Skands P, Soloveva O, Soramel F, Soto Ontoso A, Spousta M, Stahl Leiton AG, Sun J, Takacs A, Trogolo S, Turrisi R, Verweij M, Vislavicius V, Wang J, Werner K, Zaccolo V, Zhang M, Zhu J, Zuliani D.   +59 more
europepmc   +1 more source

Toward Fully Soft and Multifunctional Shape Sensing via Optical Waveguide Arrays

Advanced Intelligent Systems, EarlyView.
This work develops a sheet made with arrays of soft optical fibers that can reconstruct its 3D surface shape. Synergy of the waveguides’ responses to bending and pressing force allows shape reconstruction with resilience to damage. Applied onto surfaces of robotic or living systems, our design can be implemented in virtual reality, teleoperation ...
Qifan Yu, Nina Cao, Kaitlyn Becker
wiley   +1 more source

Left Ventricular Ejection Fraction in Heart Failure-A Parameter to Be Discontinued? [PDF]

J Clin Med
Freire I, da Silva MV.
europepmc   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Advanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica, Kostya S. Novoselov, Seongmin Kim, Yousung Jung, Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Marivi Fernandez‐Serra, Sara Navarro‐Rodriguez, Aakash Ashok Naik, Janine George, Ömer Hasan Omar, Victor Trinquet, Gian‐Marco Rignanese, Andrey Ustyuzhanin, Sonia Conesa‐Boj, Juan Rojo, Minh‐Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, Jose H. Garcia, Romain Gautier, Rachid Laref, Junfeng Qiao, Giovanni Pizzi, Nicola Marzari, Camilla Coletti, Antonio Rossi, Jean‐Lucas Uslu, Chiara Zanardi, Vincenzo Palermo, Wide Hogenhout, Natalia Konchakova, Peter Klein, Tejs Vegge, Stephan Roche   +38 more
wiley   +1 more source

Revealing atomic-scale switching pathways in van der Waals ferroelectrics. [PDF]

Sci Adv
Li X, Ashen K, Shi C, Mao N, Kolachina S, Yang K, Zhang T, Husain S, Ramesh R, Kong J, Qian X, Han Y.   +11 more
europepmc   +1 more source

Cellular Material Network: A General Machine Learning Architecture for Predicting Mechanical Properties of Cellular Materials

Advanced Intelligent Systems, EarlyView.
This study introduces Cellular Material Network (CM‐Net), a pioneering machine learning architecture integrating physical information, to predict the mechanical properties of cellular materials. Comprehensive validation through simulations and experiments demonstrates its accuracy in predicting nonlinear behaviors, including initial peak compression ...
Sicong Zhou, Qiang Gao, Liuchao Jin, Guoquan Xie, Kang Zhang, Wei‐Hsin Liao   +5 more
wiley   +1 more source