Results 131 to 140 of about 25,770 (266)

Explainable Ensemble Machine Learning for the Prediction and Optimization of Pozzolanic Concrete Compressive Strength. [PDF]

Polymers (Basel)
Jueyendah S, Ağcakoca E.
europepmc   +1 more source

Coupling Selective Organic Oxidation With Hydrogen Evolution Over Metal Halide Perovskite Photocatalysts: Halide‐Dependent Design, Mechanisms, and Stability Challenges

EcoEnergy, EarlyView.
This Review highlights how metal halide perovskites enable coupled selective organic oxidation and hydrogen evolution under visible light. It summarizes halide‐dependent design principles, surface engineering strategies, reaction mechanisms, and stability challenges, providing guidance for developing efficient and durable photocatalytic systems ...
Jutarat Jitrada, Lizhen Liu, Patchanita Thamyongkit, Yanfa Yan, Jun Huang   +4 more
wiley   +1 more source

Reliability-based mix design for concrete compressive strength using a physics-prior residual-learning surrogate with calibrated uncertainty. [PDF]

PLoS One
Qu P, Song L, Wang S.
europepmc   +1 more source

Compressive Strength of Lightweight Concrete

, 2020
openaire   +2 more sources

The Compressive Strength of the Lean-Concrete

Shin sabo, 1964
Ote, Keiji, Takahashi, Tetsuo
openaire   +1 more source

The Effect of Rainwater in Concrete Mixture on Concrete Compressive Strength

Fondasi : Jurnal Teknik Sipil, 2023
Adde Currie Siregar, Ulwiyah Wahdah Mufassirin Liana, Santi Yatnikasari, Fitriyati Agustina, Annisa Rahma   +4 more
openaire   +1 more source

Generative Models in Inorganic Crystals Discovery and Inverse Design

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Generative inverse‐design samples from the vast inorganic crystal design space by starting from target properties such as band gap, stability, and ion transport. This Review examines the representations, generative models, and validation workflows needed to translate candidate structures into stable, potentially synthesizable materials for applications
Tao Li, Xiaolin Liu, Fei Wang, Yan Xiong, Yu Chen, Yan Zhao   +5 more
wiley   +1 more source

Predicting concrete compressive strength using optimized deep learning and large language models. [PDF]

Sci Rep
Zaman S, Eid MM, Mattar EA, Khafaga DS, Towfek SK.   +4 more
europepmc   +1 more source

ZnO Nanowires by Chemical Bath Deposition: A Review on Doping and Functional Devices

Electron, EarlyView.
This review reports the most recent and well‐established state‐of‐the‐art and scientific challenges related to the doping of ZnO nanowires by chemical bath deposition, encompassing native point and hydrogen‐related defects, as well as extrinsic dopants.
Clément Lausecker, Adrien Baillard, Estelle Appert, Vincent Consonni   +3 more
wiley   +1 more source

Machine learning based optimization of fly ash content for improving geopolymer concrete compressive strength. [PDF]

Sci Rep
Sichani MN, Dehkordi OM, Khorshidi M, Teimortashlu A, Nejatipour P.   +4 more
europepmc   +1 more source