Results 171 to 180 of about 13,251 (243)

From continuous to interruptible distillation: Flexible electric heating column architecture with fast start‐up

AIChE Journal, EarlyView.
Abstract Electrification of distillation offers a promising route to reducing scope‐1 emissions from one of the chemical industry's most energy‐intensive unit operations. However, conventional adiabatic columns are dynamically inflexible: Long, energy‐intensive start‐ups make shutdown and restart impractical under variable electricity prices and ...
Samuel Mercer, Michael Baldea
wiley   +1 more source

Hierarchically engineered electrocatalysts for durable oxygen reduction in zinc–air batteries

AIChE Journal, EarlyView.
Abstract Rechargeable zinc–air batteries (ZABs) are promising energy storage systems but are limited by sluggish oxygen reduction reaction (ORR) kinetics at the air cathode. Herein, we report hierarchically engineered cobalt tetraaminophthalocyanine/MXene (CoPc/MXene) electrocatalysts prepared via cetyltrimethylammonium bromide‐mediated self‐assembly ...
Rui Guo, Houting Xie, Zhen Liu, Jiamin Lan, Bufeng Zhang, Omid Mazaheri, Shuaijun Pan   +6 more
wiley   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

Advanced Intelligent Discovery, EarlyView.
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri, Leala Carbonneau, Eric M. Roberts, Alison W. Roberts, Candace H. Haigler, Alexey V. Gulyuk, Yaroslava G. Yingling   +6 more
wiley   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Research on the Physiological Response Mechanism and Expression of Key Leaf Color Genes in 'Duojiao' Crabapple Under Partial Shading. [PDF]

Plants (Basel)
Chen B, Wang M, Yang Y, Li L, Fan Y, Zong X, Guo X, Zou F, Lin Q, Yu H, Yu J, Zhang M, Mao Y, Shen X.   +13 more
europepmc   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source

Convergent Evolution towards High Net Carbon Gain Efficiency Contributes to the Shade Tolerance of Palms (Arecaceae). [PDF]

PLoS One, 2015
Ma RY, Zhang JL, Cavaleri MA, Sterck F, Strijk JS, Cao KF.   +5 more
europepmc   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Will It Survive? Evaluating the Effects of Damage and Silviculture on Tree Seedling Survival Using Multi-State Models. [PDF]

Ecol Evol
Champagne E, Dumais D, Picher G, Raymond P.   +3 more
europepmc   +1 more source