Results 51 to 60 of about 4,693 (246)
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Light‐Imprinted Chirality in Nanomaterials: From Principles to Applications
Light‐induced chirality represents a transformative paradigm for fabricating chiral nanostructures. This review provides a comprehensive framework encompassing light‐based strategies for imprinting and tuning chirality in nanomaterials, which guides researchers in harnessing light to create next‐generation functional materials.
Xinru Jin +3 more
wiley +1 more source
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li +8 more
wiley +1 more source
Fault Attacks on the Authenticated Encryption Stream Cipher MORUS
This paper investigates the application of fault attacks to the authenticated encryption stream cipher algorithm MORUS. We propose fault attacks on MORUS with two different goals: one to breach the confidentiality component, and the other to breach the ...
Iftekhar Salam +4 more
doaj +1 more source
Advances and Perspectives in Graphene‐Based Quantum Dots Enabled Neuromorphic Devices
Graphene‐based QDs are zero‐dimensional carbon nanomaterials with pronounced quantum confinement and tunable electronic structures. Herein, we summarize their synthesis strategies and functionalization methods, and highlight their functional roles and operating mechanisms in devices, as well as recent advances in neuromorphic electronics. We anticipate
Yulin Zhen +9 more
wiley +1 more source
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei +7 more
wiley +1 more source
Wireless sensor networks (WSNs) are progressive ad hoc networks that comprise of distributed sensors that are typically and randomly deployed over the target region.
Majid Alotaibi
doaj +1 more source
Precursor stoichiometry programs the surface chemistry of carbon dots, directing their self‐assembly into distinct aggregation modes. Aldehyde‐enriched surfaces form ordered, hydrogen‐bonded assemblies that enable bright red solid‐state fluorescence, whereas amine‐rich surfaces promote compact π–π stacked aggregates with broadband visible‐light ...
Gaixia Yang +8 more
wiley +1 more source
This work presents a programmable multimodal information encryption device that harnesses the dynamic wetting behavior of liquid metal to achieve secure, reconfigurable, and high‐precision encryption and decryption of diverse data types, including text and images.
Xuedong Qiang +10 more
wiley +1 more source

