Results 101 to 110 of about 1,286,262 (236)

Quantitative 3D Real‐Space Analysis of Photonic Supraparticles

Advanced Materials, EarlyView.
This work shows that through quantitative 3D real‐space analysis, photonic supraparticles can be investigated in detail. By clustering and classifying all particles, structure features can easily be detected, and the internal structure can be quickly investigated. This methodology allows for quick identification of different crystal structures, such as
Jesse Ian Bückmann, Leroy Daniël Hoitink, Ruizhi Yang, Alptuğ Ulugöl, Laura Filion, Alfons van Blaaderen   +5 more
wiley   +1 more source

Author Correction: UKB-MDRMF: a multi-disease risk and multimorbidity framework based on UK biobank data. [PDF]

Nat Commun
Jiang Y, Zhao B, Wang X, Tang B, Peng H, Luo Z, Shen Y, Wang Z, Jiang Z, Wang J, Ye J, Wang X, Zhu H.   +12 more
europepmc   +1 more source

Self‐Powered Flexible Triboelectric‐Gated Ion‐Gel Transistor for Neuromorphic Tactile Sensing and Human Activity Recognition

Advanced Materials, EarlyView.
A fully flexible ion‐gel‐gated graphene‐channel transistor driven by a triboelectric nanogenerator enables self‐powered tactile sensing and synaptic learning. Mimicking spike‐rate‐dependent plasticity, the device exhibits frequency‐selective potentiation and depression, supporting rate‐coded neuromorphic computation even under flex.
Hanseong Cho, Seoyeon Park, Youngmin Lee, Sejoon Lee   +3 more
wiley   +1 more source

Enhanced cricket match prediction using kernel methods for feature extraction and back-propagation neural networks. [PDF]

Sci Rep
Dhinakaran K, Anbuchelian S.
europepmc   +1 more source

All‐Optical Reconfigurable Physical Unclonable Function for Sustainable Security

Advanced Materials, EarlyView.
An all‐optical reconfigurable physical unclonable function (PUF) is demonstrated using plasmonic coupling–induced sintering of optically trapped gold nanoparticles, where Brownian motion serves as a robust entropy source. The resulting optical PUF exhibits high encoding density, strong resistance to modeling attacks, and practical authentication ...
Jang‐Kyun Kwak, Changgyun Moon, Hyun‐Bin Yu, Sunkook Kim, Dong‐Hwan Kim   +4 more
wiley   +1 more source

Classifying Delayed Dental Care Using Machine Learning: A National Health Interview Survey Analysis. [PDF]

Int Dent J
Vu G, Chandra A, Salvi S, King C, Gurupur V.   +4 more
europepmc   +1 more source

Generative Models for Crystalline Materials

Advanced Materials, EarlyView.
Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich   +15 more
wiley   +1 more source

Efficient talent identification in women's football: A ranking-based approach for goal scoring analysis. [PDF]

PLoS One
Song S, Kim HS.
europepmc   +1 more source

Hydrogel‐Based 3D‐Printable Stretchable Pressure Sensor

Advanced Materials Technologies, EarlyView.
We present a carbon‐black‐functionalized double‐network granular hydrogel (DNGH) pressure sensor capable of detecting pressures from 200 Pa, equivalent to a light finger touch, up to 500 kPa. The sensor exhibits signal drifts below 3.5% after 800 cycles and response times around 80 ms. Leveraging this broad sensing range, we 3D print this material into
Tianyu Yuan, Chenzhuo Li, Antonia Georgopoulou, John M. Kolinski, Esther Amstad   +4 more
wiley   +1 more source

Flow‐Adaptive Gas Sensing Enabled Using a Uniform Au Nanosheet Sensor Array and a Neural Network Inference

Advanced Materials Technologies, EarlyView.
Integrated Au nanosheet sensor array enables simultaneous inference of gas concentration and flow rate via deep neural network analysis, without external flow control. ABSTRACT Gas sensor responses are considerably affected by gas flow rates, thereby inhibiting the accurate detection of target gas concentrations in variable‐flow applications such as ...
Taro Kato, Takahisa Tanaka, Yusuke Hamanaka, Ryo Toyoshima, Ken Uchida   +4 more
wiley   +1 more source