Results 201 to 210 of about 6,104,035 (281)

A Fluorine‐Free, Low Ion Pair Electrolyte for Transition Metal‐Free and Halogen‐Free Sodium Batteries

open access: yesAdvanced Energy Materials, EarlyView.
Fluorine‐containing electrolytes dominate modern rechargeable batteries, yet the fundamental design principles for fluorine‐free systems remain largely unexplored. We demonstrate that fluorine‐free electrolyte chemistry can simultaneously achieve long cycle life, fast charging, and stable interphase formation in sodium‐ion batteries.
Dawei Xia   +7 more
wiley   +1 more source

U.S. Agriculture, Biofuel Markets, and Trade: Challenges and Opportunities

open access: yesApplied Economic Perspectives and Policy, EarlyView.
ABSTRACT Using an enhanced Computable General Equilibrium (CGE) model (GTAP‐BIO), this study assesses how the expansion in demand for Electric Vehicles (EVs) and the reduction in exports of agricultural products induced by trade disputes negatively affect US agriculture.
Rayan Wolf, Farzad Taheripour
wiley   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

open access: yesAdvanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser   +6 more
wiley   +1 more source

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

open access: yesAdvanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta   +3 more
wiley   +1 more source

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

open access: yesAdvanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa   +2 more
wiley   +1 more source

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