Results 171 to 180 of about 7,849,431 (297)

A Generative Neuro‐Symbolic AI for Protein Sequence Design

open access: yesAdvanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne   +12 more
wiley   +1 more source

Somatic Evolution of a Germline Antibody Expands its Breadth to Neutralize Early SARS‐CoV‐2 Omicron Variants

open access: yesAdvanced Science, EarlyView.
Engineering of the 148‐germline (148‐GL) antibody reveals a roadmap for overcoming SARS‐CoV‐2 viral escape. By introducing four specific somatic hypermutations, the resulting 148‐M4 variant restores potent neutralization against Omicron BA.1 and BA.4/5.
Huibin Lv   +14 more
wiley   +1 more source

NbOx Mott Memristor‐Based Oscillatory P‐trit for Ternary Potts Machine

open access: yesAdvanced Science, EarlyView.
A ternary Potts machine utilizing NbOx‐based probabilistic trits (p‐trits) is demonstrated for efficient combinatorial optimization. By leveraging the electro‐thermal switching dynamics of NbOx memristors, this architecture generates three‐state stochastic fluctuations.
Hakseung Rhee   +10 more
wiley   +1 more source

Covalently Integrated Selenoviologen–N‐Heterocyclic Carbene–Pt Nanoparticles for Visible‐Light‐Driven Hydrogen Evolution

open access: yesAdvanced Science, EarlyView.
A covalently integrated single‐component photocatalyst is constructed by anchoring selenoviologen to platinum nanoparticles via robust N‐heterocyclic carbene ligands. The resulting Pt─C covalent bonds function dually as protective structural scaffolds and direct channels for ultrafast intramolecular electron transfer This precise interfacial ...
Wenxi He   +8 more
wiley   +1 more source

Artificial Intelligence‐Driven Inverse Design of Singlet Fission Candidates in the Acene family

open access: yesAdvanced Science, EarlyView.
In this work, we describe an AI‐driven inverse design platform predicting S1 and T1 energies across acenes with high accuracy. Using Hammett σ constants as descriptors and RNN models coupled with optimization algorithms, it efficiently explores ≈1014 structures, uncovering novel SF candidates from benzene to pentacene. Freely accessible at https://alba.
Rafael G. Uceda   +9 more
wiley   +1 more source

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