Results 171 to 180 of about 162,147 (257)

Autonomous navigation in unstructured outdoor environments using semantic segmentation guided reinforcement learning. [PDF]

Sci Rep
Tibermacine A, Tibermacine IE, Akrour D, Rabehi A, Habib M.   +4 more
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

Principal component guided DCGAN for mitigating mode collapse in electromagnetic pulse signal synthesis. [PDF]

Sci Rep
Gao Z, Zhao L, Zheng J, Yi T, Zhang C, Wang Q.   +5 more
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

Trap‐Modified Inverted Organic Photodetectors via Layer‐by‐Layer Processing with Poly(N‐vinylcarbazole) Additives

Advanced Functional Materials, EarlyView.
Trap state engineering in inverted organic photodetectors (OPDs) is achieved via combined layer‐by‐layer (LbL) processing and poly(N‐vinylcarbazole) (PVK) incorporation. LbL reduces the trap density while PVK additives gradually shift trap states from shallow band‐edge to deep mid‐gap levels, tailoring the energy distribution.
Jingwei Yi, Yi Yang, Yusen Pei, Apurva Gadikar, Vahid Mahdikhah, Myratgeldi Kotyrov, Seung Hyun Kim, Kenan Gundogdu, Wei You, Harald Ade, Franky So   +10 more
wiley   +1 more source

Frequency-Dependent Diffusion-Relaxation Distribution MRI: Scan-Rescan Reproducibility Ex Vivo and Caveats. [PDF]

NMR Biomed
Or PSK, Yon M, Narvaez O, Manninen E, Malm T, Sierra A, Topgaard D, Benjamini D.   +7 more
europepmc   +1 more source

Purcell‐Enhanced Spectrally Precise Emission in Dual‐Microcavity Organic Light‐Emitting Diodes

Advanced Functional Materials, EarlyView.
Spectrally precise emission from broadband organic light‐emitting diodes is realized via a dual‐microcavity strategy. This architecture achieves narrowband emission (full width at half maximum, FWHM = 21 nm) with ultrapure color approaching BT.2020 by enhancing the Purcell effect via coupling of excitons with dual‐microcavity resonance.
Jun Yong Kim, Sang Youn Lee, Kwan Hyun Cho, Yun Seon Do   +3 more
wiley   +1 more source

Development and characterization of pNarsenic: a naringenin-inducible biosensor for arsenic in Escherichia coli. [PDF]

Synth Biol (Oxf)
Crabbe V, Unal E, De Graeve S, Guerra DG, Peeters T, de Buyl S, Peeters E, Bervoets I.   +7 more
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

Deep Learning Meets InSAR for Infrastructure Monitoring: A Systematic Review of Models, Applications, and Challenges. [PDF]

Sensors (Basel)
Fontes M, Bakoň M, Cunha A, Sousa JJ.
europepmc   +1 more source