Results 161 to 170 of about 1,193,111 (325)

Local Thermal Conductivity Patterning in Rotating Lattice Crystals of Anisotropic Sb2S3

Advanced Functional Materials, EarlyView.
Microscale control of thermal conductivity in Sb2S3 is demonstrated via laser‐induced rotating lattice crystals. Thermal conductivity imaging reveals marked thermal transport anisotropy, with the c axis featuring amorphous‐like transport, whereas in‐plane directions (a, b) exhibit 3.5x and 1.7x larger thermal conductivity.
Eleonora Isotta, Rosemary Wynnychenko, Binayak Mukherjee, Jack Kaman, Hrushikesh Sahasrabuddhe, Jiongzhi Zheng, Anubhav Jain, Geoffroy Hautier, Alexandra Zevalkink, Evan Musterman, Volkmar Dierolf, Himanshu Jain, G. Jeffrey Snyder, Oluwaseyi Balogun   +13 more
wiley   +1 more source

Electrosynthesis of Bioactive Chemicals, From Ions to Pharmaceuticals

Advanced Functional Materials, EarlyView.
This review discusses recent advances in electrosynthesis for biomedical and pharmaceutical applications. It covers key electrochemical materials enabling precise delivery of ions and small molecules for cellular modulation and disease treatment, alongside catalytic systems for pharmaceutical synthesis.
Gwangbin Lee, Sojin Kim, Myeongeun Lee, Kyoungsuk Jin, Jimin Park   +4 more
wiley   +1 more source

Tuning the Electronic Structure and Spin State of Fe─N─C Catalysts Using an Axial Oxygen Ligand and Fe Clusters for High‐Efficiency Rechargeable Zinc–Air Batteries

Advanced Functional Materials, EarlyView.
A FeN4─O/Clu@NC‐0.1Ac catalyst containing atomically‐dispersed FeN4─O sites (medium‐spin Fe2+) and Fe clusters delivered a half‐wave potential of 0.89 V for ORR and an overpotential of 330 mV at 10 mA cm−2 for OER in 0.1 m KOH. When the catalyst was used in a rechargeable Zn–air battery, a power density of 284.5 mW cm−2 was achieved with excellent ...
Yongfang Zhou, Yu Mao, Mengyao Chang, Ziyun Wang, Wenke Xie, Cuizhu Ye, Shanghai Wei, Lars Thomsen, Geoffrey I. N. Waterhouse   +8 more
wiley   +1 more source

Atomically Revealing Bulk Point Defect Dynamics in Hydrogen‐Driven γ‐Fe2O3 → Fe3O4 → FeO Transformation

Advanced Functional Materials, EarlyView.
In situ TEM uncovers the atomic‐scale mechanisms underlying hydrogen‐driven γ‐Fe2O3→Fe3O4→FeO reduction. In γ‐Fe2O3, oxygen vacancies cluster around intrinsic Fe vacancies, leading to nanopore formation, whereas in Fe3O4, vacancy aggregation is suppressed, preserving a dense structure.
Yupeng Wu, Dongxiang Wu, Wenhui Zhu, Xiaobo Chen, Zhikang Zhou, Zhilu Liang, Shuonan Ye, Meng Li, Xiao Tong, Kim Kisslinger, Sooyeon Hwang, Dmitri Zakharov, Renu Sharma, Judith C. Yang, Guangwen Zhou   +14 more
wiley   +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

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

A Transdisciplinary Review of Deep Learning Research and Its Relevance for Water Resources Scientists [PDF]

, 2018
Chaopeng Shen
openalex   +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

Optimum exploitation of a demersal resource in the western Mediterranean: the fishery of the deep-water shrimp Aristeus antennatus (Risso, 1816)

, 1993
This study was partially financed by bthe Commission of the European Communities (DG XIV) and by grants from the CIRIT (Generalitat de Catalunya) and Caixa de ...
Demestre, Montserrat, Martín, Paloma
openaire   +1 more source

From Waste to Value: Conversion of Calcium Sulfate to Vaterite via Carbon Capture and Storage

Advanced Functional Materials, EarlyView.
This study introduces a new concept for carbon management that relies on the carbonation of industrial gypsum waste and yields phase‐pure vaterite at ambient conditions without any additives. The obtained vaterite is further shown to be a reactive material that develops compressive strength in aqueous suspensions like conventional cements.
Carlos Pimentel, German Montes‐Hernández, Pablo Almarza‐Cifuentes, Matthias Kellermeier, Alexander E.S. Van Driessche   +4 more
wiley   +1 more source