Results 191 to 200 of about 88,039 (271)

Carbon nanofiber-reinforced 3D porous aerogels for tunable low-frequency electromagnetic wave absorption. [PDF]

iScience
Shen X, Wang P, Chen Y, Jin R, Xie L, He B, Lu X, Wen Y, Quan B.   +8 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

Dual-Band, Dual-Mode, Circularly Polarized Fully Woven Textile Antenna for Simultaneous Wireless Information and Power Transfer in Wearable Applications. [PDF]

Sensors (Basel)
Fernández M, Vázquez C, Ver Hoeye S.
europepmc   +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

In-Situ Growth of Carbon Nanotubes on MOF-Derived High-Entropy Alloys with Efficient Electromagnetic Wave Absorption. [PDF]

Materials (Basel)
Wang Z, Meng B, Ping X, Yang Q, Wang K, Wang S.   +5 more
europepmc   +1 more source

DNA‐Templated 2D Heterostructures as Phototriggered Dynamic Nanohybrids: From Releasing Molecular Loads to Controlling Enzyme Biocatalytic Function

Advanced Functional Materials, EarlyView.
DNA strands are employed both as dynamic linkers and nanoscale templates for the integration of Ag2S nanoparticles on MoS2, which in turn imparted photothermal responsiveness; this feature permits the selective cargo (fluorophore, quantum dots or an enzyme) release from the MoS2 surface in response to local heat induced by light irradiation.
Kai Chen, Haosen Miao, Weiying Hong, Matteo Palma   +3 more
wiley   +1 more source

Microwave absorption properties of CoS₂/TiO₂/Ti₃C₂T_x MXene composites. [PDF]

iScience
Hosseini SA, Masoudpanah SM, Derakhshani M, Sarkar T, Aslibeiki B.   +4 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

Investigating the Structural, Thermal, Electric, Dielectric, and EMI Shielding Properties of Porous Thermoplastic Polyurethane Reinforced with Carbon Fiber/Magnetite Fillers. [PDF]

Polymers (Basel)
Kaftelen Odabaşı H, Kaya Ü, Odabaşı A, Helhel S, Ruiz-Perez F, Caballero-Briones F.   +5 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