Results 91 to 100 of about 1,679,460 (184)

Canonicalizing Zeta Generators: Genus Zero and Genus One. [PDF]

Commun Math Phys
Dorigoni D, Doroudiani M, Drewitt J, Hidding M, Kleinschmidt A, Schlotterer O, Schneps L, Verbeek B.   +7 more
europepmc   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Evolution's hidden architecture: a non-lipschitz theory of creation and catastrophe. [PDF]

BMC Ecol Evol
Durán-Olivencia MA.
europepmc   +1 more source

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

Advanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang   +3 more
wiley   +1 more source

Psychometric evaluation of the 'Caregiver Factors Influencing Treatment' (Care-FIT) Inventory for child and adolescent eating disorders. [PDF]

J Eat Disord
McCord A, Rock AJ, Davies R, Rice K.
europepmc   +1 more source

Integrative Approaches for DNA Sequence‐Controlled Functional Materials

Advanced Functional Materials, EarlyView.
DNA is emerging as a programmable building block for functional materials with applications in biomimicry, biochemical, and mechanical information processing. The integration of simulations, experiments, and machine learning is explored as a means to bridge DNA sequences with macroscopic material properties, highlighting current advances and providing ...
Aaron Gadzekpo, Ewa Anna Oprzeska‐Zingrebe, Mariana Kozlowska, Lennart Hilbert, Iliya D. Stoev   +4 more
wiley   +1 more source

Reinforcement Operator Learning (ROL): A hybrid DeepONet-guided reinforcement learning framework for stabilizing the Kuramoto-Sivashinsky equation. [PDF]

PLoS One
Ahmed N, Ashraful Babu M, Hossain MS, Fayz-Al-Asad M, Awlad Hossain M, Mortuza Ahmmed M, Mostafizur Rahman M, Mahmud M.   +7 more
europepmc   +1 more source

Photo‐Switching Thermal and Lithium‐Ion Conductivity in Azobenzene Polymers

Advanced Functional Materials, EarlyView.
Light‐responsive azobenzene polymers control thermal and ionic transport simultaneously through structural transitions. UV illumination disrupts π–π stacking, converting crystalline trans states to amorphous cis configurations. Thermal conductivity drops from 0.45 to 0.15 W·m−1·K−1 while Li+ diffusivity increases 100 fold. This dual transport switching
Jaeuk Sung, Jungwoo Shin, Qiujie Zhao, Minjee Kang, Christopher Evans, Cecilia Leal, Paul V. Braun, David G. Cahill   +7 more
wiley   +1 more source

Functional equation modeling of adaptive operant-control systems via Matkowski fixed point theory. [PDF]

PLoS One
Monica S, Ramesh Kumar D.
europepmc   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source