Results 201 to 210 of about 1,043,746 (297)

In Materia Shaping of Randomness with a Standard Complementary Metal‐Oxide‐Semiconductor Transistor for Task‐Adaptive Entropy Generation

Advanced Functional Materials, EarlyView.
This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak, Ryun‐Han Koo, Youngchan Cho, Changhyeon Han, Dongbin Kim, Soi Jeong, Yunho Shin, Joonhyeok Choi, Jiseong Im, Jonghyun Ko, Jong‐Ho Lee, Jangsaeng Kim, Youngho Kang, Wonjun Shin, Daewoong Kwon   +14 more
wiley   +1 more source

Special Issue "Raman Spectroscopy and Machine Learning in Human Disease". [PDF]

Int J Mol Sci
Bratchenko I.
europepmc   +1 more source

From In‐Silico Optimized Microfabrication to Experimental Validation: Engineering a Tridimensional Epi‐Intraneural Interface

Advanced Functional Materials, EarlyView.
An epi‐intraneural interface is developed through in silico optimization and a novel tridimensional microfabrication pipeline. The device integrates penetrating and epineural contacts on a flexible substrate. Mechanical, electrochemical, and in vivo testing in rat and pig reveal robust implantation, low‐threshold activation, and site‐dependent ...
Federico Ciotti, Andrea Cimolato, Noemi Gozzi, Pietro Palopoli, Luca Brugnoli, Natalija Katic Secerovic, Rebecca Gallivan, Alexander Shokurov, Carlo Menon, Johannes Weichart, Ignacio Delgado‐Martinez, Weiguo Song, Stavros Zanos, Xavier Navarro, Stanisa Raspopovic   +14 more
wiley   +1 more source

Toward Scalable Solutions for Silver‐Based Gas Diffusion Electrode Fabrication for the Electrochemical Conversion of CO2 – A Perspective

Advanced Functional Materials, EarlyView.
In this study, the preparation techniques for silver‐based gas diffusion electrodes used for the electrochemical reduction of carbon dioxide (eCO2R) are systematically reviewed and compared with respect to their scalability. In addition, physics‐based and data‐driven modeling approaches are discussed, and a perspective is given on how modeling can aid ...
Simon Emken, K. Ashoke Raman, Alexander Bauer, Violeta Karyofylli, Eva Jodat, André Karl, Rüdiger‐A. Eichel   +6 more
wiley   +1 more source

A Combinatorial Approach to Synthetic Data Generation for Machine Learning. [PDF]

SN Comput Sci
Khadka K, Chandrasekaran J, Lei Y, Kacker R, Kuhn DR.   +4 more
europepmc   +1 more source

Machine Learning-Assistant Colorimetric Sensor Arrays for Intelligent and Rapid Diagnosis of Urinary Tract Infection

Jianyu Yang, Ge Li, Shihong Chen, Xiaozhi Su, Dong Xu, Yueming Zhai, Yuhang Liu, Guangxuan Hu, Chunxian Guo, Hong Bin Yang, Luigi G. Occhipinti, Fang Hu   +11 more
openalex   +2 more sources

Does a Morphotropic Phase Boundary Exist in ZrxHf1‐xO2‐Based Thin Films?

Advanced Functional Materials, EarlyView.
This study investigates 6 nm zirconium‐rich hafnium‐zirconium oxide thin–film metal–insulator–metal capacitors using a combination of experimental methods and machine learning–based molecular dynamics simulations to provide insight into the physical mechanisms that enhance the dielectric constant near 0 V and attribute it to the field‐induced ...
Pramoda Vishnumurthy, Richard Ganser, Dong‐Gyu Kim, Intak Jeon, Chang Hwa Jung, Hanjin Lim, Thomas Mikolajick, Susan Trolier‐McKinstry, Alfred Kersch, Uwe Schroeder   +9 more
wiley   +1 more source

Enhancing data transmission efficiency in wireless sensor networks through machine learning-enabled energy optimization: A grouping model approach

I. Surenther, Kandi Sridhar, Michaelraj Kingston Roberts   +2 more
openalex   +1 more source

Optimizing the Layout of Service Facilities for Older People Based on POI Data and Machine Learning: Guangzhou City as an Example [PDF]

Huicheng Feng, Xiaoxiang Tang, Cheng Zou
openalex   +1 more source

Rational Design of Printable Carbon Nanotube Transparent Conductive Films via Data‐Driven and Mechanistic Insights

Advanced Functional Materials, EarlyView.
A machine learning and simulation‐guided strategy is demonstrated for gentle, non‐sonication dispersion of carbon nanotubes, preserving structural integrity and performance. This approach enables transparent conductive films with low sheet resistance, high transmittance, and sub‐20 µm printability.
Ying Zhou, Ken‐ichi Nomura, Shun Muroga, Makoto Yoneya, Don N. Futaba, Takeo Yamada, Reiko Azumi, Kenji Hata   +7 more
wiley   +1 more source