Results 141 to 150 of about 70,475,198 (271)
Identifying Low-Frequency Tree-Ring Variation
I propose an approach to provide 95% confidence intervals for a chronology of low-frequency tree-ring variation so that a level of significance or importance for trends can be inferred.
Sheppard, Paul R.
core +1 more source
Template effect and kinetic control enable crystal‐phase engineering of Ru nanocrystals, granting access to either metastable fcc‐Ru or stable hcp‐Ru with distinct surface structures, thermal stabilities, and catalytic behaviors. Moreover, the hcp‐Ru can further serve as an epitaxial template to direct Pd and Rh nanocrystals into the metastable hcp ...
Jianlong He +3 more
wiley +1 more source
Machine learning prediction of photoionization cross section in GaAs AlGaAs quantum dot ring nanostructures. [PDF]
Jaouane M +5 more
europepmc +1 more source
ABSTRACT Accurately knowing the frontier orbital energies of the structurally disordered small‐molecule organic semiconductors that are used in optoelectronic devices such as organic light‐emitting diodes is required to rationally improve their performance. Here, we show that these energies can be deduced with a large accuracy from the peak energies of
Christian B. McDonald +7 more
wiley +1 more source
Blind single image restoration for ring-array photoacoustic tomography system via physics-aided unsupervised learning. [PDF]
Dong W +5 more
europepmc +1 more source
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh +5 more
wiley +1 more source
Operando state monitoring of diversified lithium-ion batteries via laser-excited ultrasonic sensing with transformer networks. [PDF]
Lv G +11 more
europepmc +1 more source
Inverse Design of Nanoparticulate Materials
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré +5 more
wiley +1 more source
Machine Learning-Driven Refinement of Reactive Force Fields via Hierarchical "Center-Environment" Features for Energetic Molecular Crystals. [PDF]
He Q, Wang P, He X, Zhang J, Liu Y.
europepmc +1 more source
Self‐invalidating multilayer physical unclonable functions (PUFs) integrate fingerprint‐like metal nanopattern bilayers from block copolymer templates with highly reactive reduced graphene oxide (rGO) interlayers. This tamper‐responsive architecture blocks all unauthorized physical and chemical replication attempts while autonomously deactivating ...
Gyu Hui Jo +7 more
wiley +1 more source

