Results 151 to 160 of about 801,900 (223)

Photoswitchable Conductive Metal–Organic Frameworks

Advanced Functional Materials, EarlyView.
A conductive material where the conductivity can be modulated remotely by irradiation with light is presented. It is based on films of conductive metal–organic framework type Cu3(HHTP)2 with embedded photochromic molecules such as azobenzene, diarylethene, spiropyran, and hexaarylbiimidazole in the pores.
Yidong Liu, Mersad Mostaghimi, Abhinav Chandresh, Saibal Jana, Wolfgang Wenzel, Lars Heinke   +5 more
wiley   +1 more source

Deep-ProBind: binding protein prediction with transformer-based deep learning model. [PDF]

BMC Bioinformatics
Khan S, Noor S, Awan HH, Iqbal S, AlQahtani SA, Dilshad N, Ahmad N.   +6 more
europepmc   +1 more source

Role of Pressure and Expansion on the Degradation in Solid‐State Silicon Batteries: Implementing Electrochemistry in Particle Dynamics

Advanced Functional Materials, EarlyView.
A simulation technique for assessing both the fabrication and operation of a solid‐state Si battery is demonstrated by integrating particle dynamics with mass/charge transport. Although, the fabrication pressure (Pfab) increased the inter‐particle contacts and reduced the concentration (ηconc) and Li‐ion (ηLi+) overpotentials during discharging, it ...
Magnus So, Takeru Yano, Agnesia Permatasari, Van Lap Nguyen, Gen Inoue   +4 more
wiley   +1 more source

Artificial Intelligence in Biomedical Engineering and Its Influence on Healthcare Structure: Current and Future Prospects. [PDF]

Bioengineering (Basel)
Tripathi D, Hajra K, Mulukutla A, Shreshtha R, Maity D.   +4 more
europepmc   +1 more source

Self‐organized Criticality in Neuromorphic Nanowire Networks With Tunable and Local Dynamics

Advanced Functional Materials, EarlyView.
Memristive nanowire networks (NWNs) are shown to be electrically tunable to a critical state where specific local dynamics evaluated by multiterminal characterization are exploited as feature selection in nonlinear transformation (NLT) tasks.
Fabio Michieletti, Davide Pilati, Gianluca Milano, Carlo Ricciardi   +3 more
wiley   +1 more source

Mini review on skin biopsy: traditional and modern techniques. [PDF]

Front Med (Lausanne)
Alwahaibi N, Alwahaibi M.
europepmc   +1 more source

Roulette‐Inspired Physical Unclonable Functions: Stochastic yet Deterministic Multi‐Bit Patterning through the Solutal Marangoni Effect

Advanced Functional Materials, EarlyView.
Geometric multi‐bit patterning based on dynamic wetting and dewetting phenomena creates roulette‐like Physical Unclonable Function (PUF) labels with stochastic yet deterministic properties. This method leverages the solutal‐Marangoni effect for high randomness while achieving deterministic multinary patterns through polygonal confinement of binary ...
Yeongin Cho, Jeongsu Pyeon, Hanhwi Jang, Gwangsik Mun, Jaimin Kang, Byong‐Guk Park, Geon Yeong Kim, Hyoungsoo Kim, Yeon Sik Jung   +8 more
wiley   +1 more source

Generative artificial intelligence and machine learning methods to screen social media content. [PDF]

PeerJ Comput Sci
Sharp K, Ouellette RR, Singh RSR, DeVito EE, Kamdar N, de la Noval A, Murthy D, Kong G.   +7 more
europepmc   +1 more source

Autonomous Control of Extrusion Bioprinting Using Convolutional Neural Networks

Advanced Functional Materials, EarlyView.
This work presents a novel computer vision system for high‐fidelity monitoring of extrusion‐based bioprinting and a correction system utilizing convolutional neural networks for error mitigation. This system has demonstrated high detection accuracy and extrusion correction abilities that advance the state of the art toward accelerated printing ...
Daniel Kelly, Vasileios Sergis, Laura Ventura i Blanco, Karl Mason, Andrew C. Daly   +4 more
wiley   +1 more source

Active Learning‐Driven Discovery of Sub‐2 Nm High‐Entropy Nanocatalysts for Alkaline Water Splitting

Advanced Functional Materials, EarlyView.
High‐entropy nanoparticles (HENPs) hold great promise for electrocatalysis, yet optimizing their compositions remains challenging. This study employs active learning and Bayesian Optimization to accelerate the discovery of octonary HENPs for hydrogen and oxygen evolution reactions.
Sakthivel Perumal, Da Bean Han, Thandapani Marimuthu, Taewaen Lim, Hyun Woo Kim, Junhyeok Seo   +5 more
wiley   +1 more source