Results 71 to 80 of about 160,416 (217)

Optimal Control Drives Ultrafast and Energy‐Efficient Magnetization Switching in Van der Waals Magnets

Advanced Materials, EarlyView.
ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh, PeiYu Cai, Elton J. G. Santos   +2 more
wiley   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Balancing ethics and statistics: machine learning facilitates highly accurate classification of mice according to their trait anxiety with reduced sample sizes. [PDF]

Transl Psychiatry
Miedema J, Lutz B, Gerber S, Kovlyagina I, Todorov H.   +4 more
europepmc   +1 more source

1‐D Collocated Dual‐Gradient Sensory Fibers for Comprehensive Sensing and Decoding of Complex Human Motion and Physiology

Advanced Materials, EarlyView.
Coupled materials design enables a monolithic fiber that integrates complementary sensing regimes into a single wearable strand. By preserving informative signal features across subtle physiological deformation, large body motion, and mixed mechanical inputs, the dual‐gradient architecture generates synchronized, less redundant outputs that improve ...
Yunheum Lee, Sungha Jeon, Min Kim, Joonhee Won, Jinwook Yeo, Kyunghyun Jo, Soyeon Lee, Kieun Park, Yechan Yang, Chul Kim, Gun‐Hee Lee, Seunghwa Ryu, Sungho Jo, Seongjun Park   +13 more
wiley   +1 more source

Understanding Operando Water Management in Hydroxide‐Exchange‐Membrane Fuel Cells

Advanced Materials Interfaces, EarlyView.
Effective water management is vital for high‐performance hydroxide‐exchange‐membrane fuel cells. Using a custom water‐flux station, this study quantifies how membrane thickness, microporous layers, and operating conditions dictate internal water transport.
Catherine M. Weiss, Shiyi Wang, Brian P. Setzler, Yushan Yan, Adam Z. Weber   +4 more
wiley   +1 more source

Machine Learning Is Not Just for Prediction: Its Role as an Exploratory Analytical Tool in Medicine. [PDF]

Ann Vasc Dis
Komatsu S.
europepmc   +1 more source

A Hybrid Computational Framework for PCF‐based SPR Sensor With Machine Learning and xAI

Advanced Materials Interfaces, EarlyView.
A photonic crystal fiber‐based surface plasmon resonance (SPR) sensor integrating rectangular air holes along with conventional circular air holes achieves exceptional wavelength sensitivity of 15,000 nm/RIU across a broad refractive index range of 1.31–1.39. Integrated machine learning with explainable AI (xAI) models achieves high prediction accuracy
Mahabur Rahman Fahim, Sudeep Paul, Musrat Jahan, Md Abu Shahid Chowdhury   +3 more
wiley   +1 more source

Five views on the foundations of data science. [PDF]

Patterns (N Y)
Kristal BS, McCradden MD, Thiyagalingam J, Zhang Z, Goble C.   +4 more
europepmc   +1 more source

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

Advanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding, Danny E. P. Vanpoucke, Yunus T. Aksoy, Tobias Corthouts, Maria R. Vetrano, Wim Deferme   +5 more
wiley   +1 more source