Results 241 to 250 of about 159,168 (308)

Neural Network‐Based Permittivity Engineering of Magnetic Absorbers for Customizable Microwave Absorption

open access: yesAdvanced Science, EarlyView.
A neural network‐enabled permittivity engineering paradigm is introduced, transcending traditional trial‐and‐error design. By decoupling electromagnetic parameters and screening a high‐throughput feature space, an ultrathin (1.0 mm) magnetic absorber is inversely designed, experimentally achieving a superior and customizable 5.1 GHz bandwidth and ...
Chenxi Liu   +9 more
wiley   +1 more source

Lattice Genome Framework for Regionally Tailored Component‐Level Multi‐Objective Design in Additive Manufacturing

open access: yesAdvanced Science, EarlyView.
A Lattice Genome framework links geometric and process “genes” to lattice “phenotypes” via correction‐calibrated high‐throughput simulations and a growing performance database. Genome‐driven retrieval and recombination of unit cells enables component‐level, regionally tailored multi‐objective design: stress fields are programmed under constant relative
Haoyuan Deng   +8 more
wiley   +1 more source

The floral morphology of <i>Pseudosasa nanunica</i> (Poaceae, Bambusoideae). [PDF]

open access: yesPhytoKeys
Niu ZY   +5 more
europepmc   +1 more source

Adult Sex Ratio as a Demographic Feedback Linking Mating Systems, Parental Care, and Evolution

open access: yesAdvanced Science, EarlyView.
Breeding systems are some of the most diverse social behavior, and our team is investigation the evolutionary causes of this diversity. This review summarises our research carried out at the University of Bath. We argue that demographic components of wild populations, especially the adult sex ratio, plays a key role driving breeding system variation ...
Tamás Székely, Oscar G. Miranda
wiley   +1 more source

Understanding Fabrication Variability in Core‐Shell Soft Biomaterials Using Stochastic Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Fabrication‐induced variability remains a fundamental limitation in the scalable design of soft biomaterials. In this work, a stochastic machine learning approach based on Gaussian processes modeling is employed to establish quantitative links between biofabrication parameters, material properties, and their intrinsic variability.
Maria Alexaki   +8 more
wiley   +1 more source

Forecasting Root Rot Disease through Predictive Microbial Functional Profiling

open access: yesAdvanced Science, EarlyView.
Predicting soil‐borne disease moves beyond observation with a framework that elevates microbial functional genes into reliable forecasting biomarkers. By coupling targeted qPCR assays for core stress‐response genes with machine learning, this method detects root rot risks in pre‐symptomatic soils with over 80% accuracy.
Chuan You   +11 more
wiley   +1 more source

Bioinspired Microphase‐Engineered Binders for Silicon Anodes

open access: yesAdvanced Science, EarlyView.
Inspired by the tough exoskeleton of Phloeodes diabolicus, a bio‐based binder featuring LRA–click chemistry and hierarchical crosslinking forms well‐defined microphase‐separated structures that enable robust silicon anodes. This system promotes the formation of a LiF–rich, ultrathin SEI (∼17 nm) with high modulus and ionic conductivity, ensuring long ...
Lirong Tang   +15 more
wiley   +1 more source

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