Results 121 to 130 of about 36,894 (295)

Advances in Magnesium‐Based Thermoelectrics: A Critical Review

Advanced Materials, EarlyView.
Magnesium‐based thermoelectric materials have emerged as promising candidates for low‐to‐mid‐temperature energy conversion due to their abundance, low cost, and competitive performance. This review summarizes recent advances in Mg3X2, MgAgSb, and Mg2X systems, covering transport mechanisms, fabrication strategies, stability challenges, and device ...
Li‐Min Zhang, Li Zhang, Nan‐Hai Li, Yan‐Ling Yang, Xiao‐Lei Shi, Zhi‐Gang Chen   +5 more
wiley   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Designable van der Waals Crystal for Artificial Neuronal Cell Mimicking

Advanced Materials, EarlyView.
Designable van der Waals crystal has been demonstrated for device‐scale neuronal cell mimicking. The structural similarity between ion‐channel in biological membranes and layered vdW lattices is realized with nano‐crystallization via Ar + H2S plasma sulfurization.
Jinhyoung Lee, Gunhyoung Kim, Dongho Lee, Seowoo Son, Hyunho Seok, Sihoon Son, Hyunbin Choi, Geonwook Kim, Geumji Back, Hyunkyu Kim, Chaerin Park, Junmin Ahn, Seongyun Je, Chaeyoung Im, Junil Cho, Magdalena Grzeszczyk, Seongho Kim, Eunseo Go, Hyunwoo Shim, Donghwan Choi, Muyoung Kim, Hyoeng‐U. Kim, Won‐Jun Jang, Taesung Kim   +23 more
wiley   +1 more source

On some global aspects of manifold learning

, 2017
International audienceWith the dual purpose of helping place in perspective the diverse approaches to manifold learning, and facilitating future research, this paper steps back and describes the manifold learning problem from a holistic perspective.
Manton, Jonathan, Le Bihan, Nicolas, J. H. Manton, N. Le Bihan   +3 more
core   +1 more source

Deep Learning Inverse Design of Phase‐Change Reconfigurable Terahertz Metadevices for Multidimensional Secure Communication

Advanced Materials, EarlyView.
A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong, Xieyu Chen, Aarthy Nagarajan, Yi Yang, Zhihao Wang, Rui Yu, Chuang Zheng, Chunmei Ouyang, Xueqian Zhang, Tun Cao, Ranjan Singh, Zhen Tian   +11 more
wiley   +1 more source

Unsupervised manifold embedding to encode molecular quantum information for supervised learning of chemical data

Communications Chemistry
Molecular representation is critical in chemical machine learning. It governs the complexity of model development and the fulfillment of training data to avoid either over- or under-fitting. As electronic structures and associated attributes are the root
Tonglei Li, Nicholas J. Huls, Shan Lu, Peng Hou   +3 more
doaj   +1 more source

Semi-Supervised Manifold Learning for Hyperspectral Data

, 2019
There are real world data sets where a linear approximation like the principalcomponents might not capture the intrinsic characteristics of the data.
Becker, Florian
core   +1 more source

Manifold Learning

This Open Access book reviews recent theoretical and numerical developments in nonlinear model order reduction in continuum mechanics, being addressed to Master and PhD students, as well as to researchers, lecturers and instructors. The aim of the authors is to provide tools for a better understanding and implement reduced order models by using ...
David Ryckelynck, Fabien Casenave, Nissrine Akkari   +2 more
openaire   +3 more sources

Soft Hardware, Flowing Software: Reconfigurable Microfluidics for Adaptable Chemical Computation

Advanced Materials, EarlyView.
A reconfigurable microfluidic platform based on soft, photo‐printable, and chemically erasable hydrogel structures printed and erased in situ is used to control flow routing, mixing, chemical patterning, and even chemical computing. Using hardware to control chemical computations decouples logic function from molecular composition, demonstrated via ...
Piet J. M. Swinkels, Brigitta Dúzs, Oliver Skarsetz, Kohei Nishiyama, Andreas Walther   +4 more
wiley   +1 more source

Manifold Learning in Computational Biology

, 2008
This thesis deals with manifold learning techniques and their application in gene expression data analysis. Manifold learning is the study of methods that aim to infer geometrical structure from data sampled from manifolds, enabling nonlinear solutions ...
Nilsson, Jens
core