Results 141 to 150 of about 42,588 (304)

Convex Co-Embedding for Matrix Completion with Predictive Side Information

, 2017
Matrix completion as a common problem in many application domains has received increasing attention in the machine learning community. Previous matrix completion methods have mostly focused on exploiting the matrix low-rank property to recover missing ...
Guo, Yuhong
core   +1 more source

Tough, Ductile, and Strong Hard‐Soft Cementitious Composite Enabled by Multi‐Material Additive Manufacturing

Advanced Materials, EarlyView.
Drawing inspiration from the layered hard‐soft architecture found in sea sponges, this work establishes a new framework for architected cementitious composites (ACC) through multi‐material additive manufacturing (MMAM) process. The integration of mortar and elastomer phases into layered architectures enables synergistic toughening mechanisms, including
Aimane Najmeddine, Shashank Gupta, William Makinen, Zayvinn Lin, Krystal Delnoce, Reza Moini   +5 more
wiley   +1 more source

Structured low-rank approximation with missing data

The approach of SIAM J. Matrix Anal. Appl., 26(4):1083--1099 for solving structured total least squares problems is generalized to weighted structured low-rank approximation with missing data. The method proposed is based on elimination of the correction
Markovsky, Ivan, Usevich, Konstantin
core  

Topology and Material Optimization in Ultra‐Soft Magneto‐Active Structures: Making Advantage of Residual Anisotropies

Advanced Materials, EarlyView.
Residual magnetization induces pronounced mechanical anisotropy in ultra‐soft magnetorheological elastomers, shaping deformation and actuation even without external magnetic fields. This study introduces a computational‐experimental framework integrating magneto‐mechanical coupling into topology optimization for designing soft magnetic actuators with ...
Carlos Perez‐Garcia, Rogelio Ortigosa, Jesús Martínez‐Frutos, Daniel Garcia‐Gonzalez   +3 more
wiley   +1 more source

A block completion problem for matrix-valued inner functions

, 1997
In this paper, several block completion problems for matrix-valued inner functions are ...
Müller, K., Fritzsche, B., Kirstein, B.
core   +1 more source

Numerical simulation study on the coal-bed methane displacement effect of different gas injection components

Gong-kuang zidonghua
The main components of gas injection to promote methane extraction are N2, CO2, and air, but there is currently limited research on the comparison of displacement effects for different injection components.
XU Xiaoma, YAN Xiangxiang, HUANG Shuyu
doaj   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Matrix sandwich problems

, 1998
The Π Matrix Sandwich Problem (Π-MSP) is introduced here as follows: Given a {0, 1, ∗} valued matrix A, where ∗ is interpreted as “do not care”, does there exist a fill-in of the asterisks ∗ with 0s and 1s such that the completed {0, 1} valued matrix M ...
Golumbic, Martin Charles
core   +1 more source

Viral Infection‐Inspired Autonomous Detection of Fusion‐Competent Viruses for Screening and Environmental Surveillance

Advanced Materials, EarlyView.
Inspired by viral entry mechanisms, the FUSION assay enables autonomous detection of respiratory viruses via membrane fusion–triggered CRISPR‐Cas13a activation. VEACON selectively fuses with fusion‐competent viruses, triggering fluorescence within confined vesicles.
Jae Chul Park, Yidam Song, Hyun‐Woo Choi, Jaeuk Sung, Harin Jin, WonSeok Gwak, Kirim Yoo, Soohwang Lee, Jongeon Park, Jeongmin Kim, Hye‐Jun Jo, Jahyun Koo, Youngdo Jeong, Kwan Hyi Lee, Seung‐Jung Kee, Hojun Kim   +15 more
wiley   +1 more source

Inverse Design of Amorphous Materials With Targeted Properties

Advanced Materials, EarlyView.
AMDEN is a diffusion model framework for the inverse design of amorphous materials with targeted properties. By incorporating Hamiltonian Monte Carlo refinement into the denoising process, the framework overcomes the challenge of generating thermally relaxed disordered structures.
Jonas A. Finkler, Yan Lin, Tao Du, Jilin Hu, Morten M. Smedskjaer   +4 more
wiley   +1 more source