Results 151 to 160 of about 120,389,537 (218)

Exploring tumorigenesis as a process of phenotypic state-space exploration and selective funneling. [PDF]

open access: yesEvol Med Public Health
Thomas F   +11 more
europepmc   +1 more source

In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs

open access: yesAdvanced Intelligent Discovery, EarlyView.
A vision‐based add‐on transforms commercial spin coaters into autonomous modules of Self‐Driving Labs. Combining a width‐scaled U‐Net with classical geometric analysis, the system simultaneously measures contact angles and estimates substrate pose using a single camera.
Sven Fischer, Micha Hiegle, Holger Röhm
wiley   +1 more source

Particle Filtering-Based In-Flight Icing Detection for Unmanned Aerial Vehicles. [PDF]

open access: yesSensors (Basel)
Souanef T   +4 more
europepmc   +1 more source

Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network

open access: yesAdvanced Intelligent Discovery, EarlyView.
We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang   +16 more
wiley   +1 more source

A theoretical framework for brain-computer interfaces: decodability, performance limits, and closed-loop adaptation. [PDF]

open access: yesFront Hum Neurosci
Fu Y   +10 more
europepmc   +1 more source

Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation

open access: yesAdvanced Intelligent Discovery, EarlyView.
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei   +9 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

open access: yesAdvanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne   +5 more
wiley   +1 more source

PRISM, a Bidirectional NMR Foundation Model: From Peak List to Structure and Back

open access: yesAngewandte Chemie, EarlyView.
Structure elucidation from NMR can consume an expert for hours or even days. PRISM addresses this with a bidirectional transformer trained on 1.19 M real experimental spectra: it translates 1H and 13C peak lists into structures with 60.1% stereo‐aware top‐1 accuracy (72.5% stereo‐unaware), and, working in reverse, predicts spectra back from structures,
Ajnabiul Hoque, Frank Glorius
wiley   +2 more sources

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