Results 231 to 240 of about 9,056,628 (331)

Molecular Cross‐Linking of MXenes: Tunable Interfaces and Chemiresistive Sensing

Advanced Functional Materials, EarlyView.
In this study, Ti3C2Tx MXenes are initially functionalized using oleylamine ligands to form stable dispersions in an organic solvent. Subsequently ligand exchange with α,ω‐diaminoalkanes enables cross‐linking, along with precise tuning of interfaces. This structural control translates into tunable charge transport and responsive VOC sensing, showing ...
Yudhajit Bhattacharjee, Lukas Mielke, Mahmoud Al‐Hussein, Shivam Singh, Karen Schaefer, Borja Rodriguez‐Barea, Qiong Li, Anik Kumar Ghosh, Artur Erbe, Carmen Herrmann, Yana Vaynzof, Andreas Fery, Hendrik Schlicke   +12 more
wiley   +1 more source

Microplastics from Wearable Bioelectronic Devices: Sources, Risks, and Sustainable Solutions

Advanced Functional Materials, EarlyView.
Bioelectronic devices (e.g., e‐skins) heavily rely on polymers that at the end of their life cycle will generate microplastics. For research, a holistic approach to viewing the full impact of such devices cannot be overlooked. The potential for devices as sources for microplastics is raised, with mitigation strategies surrounding polysaccharide and ...
Conor S. Boland
wiley   +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

Perspective on Using Artificial Intelligence in Alcohol Research and Treatment: Opportunities and Ethical Considerations. [PDF]

Alcohol Res
Moniz-Lewis DIK, Kirouac M, McCool MW, Schwebel FJ, Witkiewitz K.   +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

A Tracer Diffusion Study of Diverse Photo‐Ionic Phenomena in Strontium Titanate

Advanced Functional Materials, EarlyView.
Two strong interfacial photo‐ionic effects are demonstrated for the model system SrTiO3 through the application of isotope exchange experiments: UV illumination is found to enhance the oxygen surface exchange coefficient by several orders of magnitude and to depress the surface space‐charge potential substantially.
David M. Schwenkel, Timon F. Kielgas, George F. Harrington, Roger A. De Souza   +3 more
wiley   +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

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

BLMPred: Predicting linear B-cell epitopes using pre-trained protein language models and machine learning. [PDF]

Comput Struct Biotechnol J
Das B, Frishman D.
europepmc   +1 more source