Results 131 to 140 of about 3,578 (213)

Uncertainty in aquatic greenhouse gas flux estimates arises from subjective processing of floating chamber time series

open access: yesLimnology and Oceanography: Methods, EarlyView.
Abstract Accurate quantification of greenhouse gas (GHG) fluxes from aquatic systems is essential for constraining regional and global carbon budgets. Closed floating chambers are widely used to measure carbon dioxide (CO2) and methane (CH4) fluxes at the water–air interface, yet large uncertainties persist due to subjective processing of chamber time ...
Camille Minaudo   +16 more
wiley   +1 more source

Efficient First‐Principles Inverse Design of Nanolasers

open access: yesLaser &Photonics Reviews, EarlyView.
This article introduces a first‐principles inverse‐design framework for nanolasers that directly incorporates nonlinear lasing physics. By unifying steady‐state ab‐initio laser theory (SALT) with topology optimization, it reveals how spatial hole burning, gain saturation, and cavity‐emitter coupling shape laser performance, enabling efficient discovery
Beñat Martinez de Aguirre Jokisch   +5 more
wiley   +1 more source

Natural variation in expression of a plant immune receptor mediates elicitor sensitivity. [PDF]

open access: yesPLoS One
Behnken B   +4 more
europepmc   +1 more source

Bayesian Optimization of Grayscale Patterns for Layer‐Height Accuracy in Projection Multi‐Photon 3D Printing

open access: yesLaser &Photonics Reviews, EarlyView.
Bayesian optimization combined with in situ quantitative phase imaging enables autonomous correction of layer‐height deviations in projection multi‐photon lithography. By jointly tuning model parameters and grayscale exposure settings, the method achieves more uniform and accurate layers within 300 prints, offering a fast, data‐efficient route to ...
Jason E. Johnson, Xianfan Xu
wiley   +1 more source

Structure‐Aware Machine Learning for Polymers: A Hierarchical Graph Network for Predicting Properties From Statistical Ensembles

open access: yesMacromolecular Rapid Communications, EarlyView.
This work presents a structure‐aware graph convolutional network that models polymers as statistical ensembles to predict macroscopic properties. By combining topologically realistic graphs generated via kinetic Monte Carlo simulations with explicit molar mass distributions, the framework achieves high accuracy in classifying architectures and ...
Julian Kimmig   +7 more
wiley   +1 more source

Challenges and Opportunities in Machine Learning for Light‐Emitting Polymers

open access: yesMacromolecular Rapid Communications, EarlyView.
The performance of light‐emitting polymers emerges from coupled effects of chemical diversity, morphology, and exciton dynamics across multiple length scales. This Perspective reviews recent design strategies and experimental challenges, and discusses how machine learning can unify descriptors, data, and modeling approaches to efficiently navigate ...
Tian Tian, Yinyin Bao
wiley   +1 more source

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