Results 91 to 100 of about 52,233 (277)
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
We discovered novel materials with giant dielectric constants by combining first‐principles phonon calculations and machine learning. Screening 525 perovskites identified six candidates. RbNbO3 was synthesized under pressure and showed ε ≈ 800–1000. This validates our framework as a powerful tool for high‐performance dielectric materials discovery.
Hiroki Moriwake +9 more
wiley +1 more source
Localization of the 5D supergravity action and Euclidean saddles for the black hole index
We investigate equivariant localization of the gravitational on-shell action in odd dimensions, focusing on five-dimensional ungauged supergravity. We analyze the conditions for cancellation of boundary terms, so that the full action integral is given in
Davide Cassani +2 more
doaj +1 more source
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
AI‐based tools enable rapid characterization of bacterial ultrastructure in low‐dose cryogenic transmission electron microscopy. The envelope thickness tool quantifies membrane thickness and anisotropy. The flagella module analyzes filament morphology and detects cell‐flagella contacts.
Sita Sirisha Madugula +10 more
wiley +1 more source
Solvable Quantum Circuits in Tree+1 Dimensions
We devise tractable models of unitary quantum many-body dynamics on tree graphs, as a first step toward a deeper understanding of dynamics in non-Euclidean spaces.
Oliver Breach +3 more
doaj +1 more source
A skin‐conformal wearable device based on laser‐induced graphene is developed for continuous strain measurement across the circumference of the forearm for gesture recognition and hand‐tracking applications. Post material optimization, the strain sensor array is integrated with a wearable wireless readout circuit for real‐time control of a robotic arm,
Vinay Kammarchedu +2 more
wiley +1 more source
BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan +7 more
wiley +1 more source
Enabling Metal‐Based Soft Robotics Through Investment Casting
Vacuum investment casting enables manufacturing of compliant soft robotic structures out of AA7075 high‐strength aluminum alloy. Additively manufactured patterns are converted into metal soft robotic structures addressing long lasting challenges like durability and nonlinearity of elastomer‐based soft robotics.
Felix Pancheri, Tim C. Lueth, Yilun Sun
wiley +1 more source
Non-Euclidean Geometry in Nature [PDF]
I describe the manifestation of the non-Euclidean geometry in the behavior of collective observables of some complex physical systems. Specifically, I consider the formation of equilibrium shapes of plants and statistics of sparse random graphs. For these systems I discuss the following interlinked questions: (i) the optimal embedding of plants leaves ...
openaire +2 more sources

