Data driven performance prediction of titanium-based matrix composites DOI Creative Commons
Xiaoling Wu, Yunfeng Zhou, Jinxian Zhang

et al.

Alexandria Engineering Journal, Journal Year: 2023, Volume and Issue: 85, P. 300 - 306

Published: Nov. 23, 2023

Titanium matrix composites (TMCs) offer superior specific mechanical properties compared to monolithic alloys. However, the complex interdependent effects of composition and processing on resulting microstructure make experimental determination optimal TMC formulations challenging. This work explored a materials informatics approach integrating machine learning (ML) modeling with targeted fabrication characterization for accelerated data-driven design TMCs. A dataset 368 data points composition, method various TMCs was compiled from literature. Five ML regression algorithms were implemented predict density, hardness strength composition-processing features. Among models, random forest achieved highest accuracy R2 scores above 0.93 low errors. Fabrication Ti-6Al-4 V/SiC using ML-guided parameters showed excellent agreement between predicted experimentally measured properties. The models outperformed conventional empirical predictions by structure-property linkages data. integrated computational-experimental framework can guide rapid identification property-optimized reducing trial-and-error. Further should focus physics-based feature engineering active learning. demonstrated here shows promise accelerating development high-performance

Language: Английский

A global meta-analysis of phthalate esters in drinking water sources and associated health risks DOI Creative Commons
Yasser Vasseghian,

Monireh Alimohamadi,

Elena-Niculina Drăgoi

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 903, P. 166846 - 166846

Published: Sept. 9, 2023

Phthalate esters (PAEs) are known as of phthalic acid, which commonly used plasticizers in the plastic industry. Due to lack chemical bonding with polymer matrix, these compounds easily separated from products and enter environment. To investigate growth concentration PAEs like DBP (Dibutyl phthalate), DEP (Diethyl DMP (Dimethyl DIBP (Diisobutyl TPMBP (tris(2-methylbutyl) phosphate) different water sources, a study January 01, 1976, April 30, 2021, was implemented via global systematic review plus meta-analysis which, 109 articles comprising 4061 samples, 4 types, 27 countries were included. Between various types river lake most contaminated resources PAEs. Among all studies PAEs, values >15,573 mg L−1 have highest average value 0.002885 has lowest sources. The sources Nigeria least China. Besides, Monte-Carlo simulation indicated that for minimum lower than acceptable limit generated. However, population (>75 %) is at risk both adults child cases. For situation much worse, simulations not providing one case where R index 1E-06.

Language: Английский

Citations

133
Bacillus thuringiensis Based Ruthenium/Nickel Co-Doped Zinc as a Green Nanocatalyst: Enhanced Photocatalytic Activity, Mechanism, and Efficient H2 Production from Sodium Borohydride Methanolysis DOI
Akbar Hojjati‐Najafabadi, Ayşenur Aygün, Rima Nour Elhouda Tiri

et al.

Industrial & Engineering Chemistry Research, Journal Year: 2023, Volume and Issue: 62(11), P. 4655 - 4664

Published: Jan. 11, 2023

Today, the development of green nanocatalysts is among popular topics due to need for energy production and cleaning organic pollutants. In this approach, Bacillus thuringiensis, a bacterium, was used as biosupport ruthenium/nickel co-doped zinc nanoparticles (btRNZn NPs) release hydrogen from methanolysis sodium borohydride (NaBH4). addition, their photocatalytic activity reported against Methyl Orange (MO) dye. This study focused on preparation, characterization, catalytic btRNZn biocatalyst NaBH4 removal MO According TEM analysis, average size NPs found be 11.78 nm; in showed photodegradation effect 68.2% dye at 90 min, its mechanism discussed. The effects catalyst, substrate, temperature reaction presence catalyst were investigated extensively. kinetics calculated, TOF, activation energy, enthalpy measured 2497.14 h–1, 14.89 kJ/mol, 12.35 respectively. It observed that process first-order based amount substrate. aimed synthesize nanobiocatalyst by biological method, it will great photocatalyst prevent wastewater pollution; also, can an excellent produce methanolysis. application solar photocatalysis pollution research through creation are both made clear these studies.

Language: Английский

Citations

56
An enhanced Dendritic Neural Algorithm to predict the wear behavior of alumina coated silver reinforced copper nanocomposites DOI Creative Commons
A.M. Sadoun, I.M.R. Najjar,

A. Fathy

et al.

Alexandria Engineering Journal, Journal Year: 2022, Volume and Issue: 65, P. 809 - 823

Published: Oct. 4, 2022

Due to the lack of analytical solutions for wear rates prediction nanocomposites, we present a modified machine learning method named Dendritic Neural (DN) predict performance copper-alumina (Cu-Al 2 O 3 ) nanocomposites that have large applicability in electronics. This modification aims at determining optimal weights DN since they largest influence on its performance. To achieve this improvement new meta-heuristic technique Artificial Hummingbird Algorithm (AHA) was used. The model applied and coefficient friction Cu-Al developed study. Electroless coating Al nanoparticles with silver (Ag) performed improve wettability followed by ball milling compaction consolidate composites. microstructural, mechanical properties produced composites different content were characterized. evaluated using sliding test load speeds. AHA algorithm showed excellent predictability rate reinforcement up 10%.

Language: Английский

Citations

63
Facile synthesis of biogenic palladium nanoparticles using biomass strategy and application as photocatalyst degradation for textile dye pollutants and their in-vitro antimicrobial activity DOI

Yunyi Liang,

Halit Demir, Yingji Wu

et al.

Chemosphere, Journal Year: 2022, Volume and Issue: 306, P. 135518 - 135518

Published: June 30, 2022

Language: Английский

Citations

53
Hydrogen production and photocatalytic activities from NaBH4 using trimetallic biogenic PdPtCo nanoparticles: Development of machine learning model DOI
Elif Esra Altuner, Rima Nour Elhouda Tiri, Ayşenur Aygün

et al.

Process Safety and Environmental Protection, Journal Year: 2022, Volume and Issue: 184, P. 180 - 190

Published: May 23, 2022

Language: Английский

Citations

35
Hydrogen Generation by Methanolysis of NaBH4 via Efficient CuFe2O4 Nanoparticle Catalyst: A Kinetic Study and DNN Model DOI

Muhammad Ali Yousif Al Janabi,

Rima Nour Elhouda Tiri, Ali Chérif

et al.

Topics in Catalysis, Journal Year: 2024, Volume and Issue: 67(9-12), P. 843 - 852

Published: Feb. 20, 2024

Language: Английский

Citations

6
Nickel-iron catalyst for decomposition of methane to hydrogen and filamentous carbon: Effect of calcination and reaction temperatures DOI Creative Commons
Abdulrahman I. Alharthi

Alexandria Engineering Journal, Journal Year: 2022, Volume and Issue: 67, P. 129 - 141

Published: Dec. 29, 2022

Nickel-ferrite Ni-Fe (molar ratio 1:2) were synthesised and calcined at different temperatures. The catalytic performances of for methane decomposition production hydrogen carbon nanostructures evaluated various calcination (350–800 °C) reaction temperatures (700–800 °C). Fresh spent catalysts characterized using scanning electron microscopy (SEM), BET surface area, X-ray diffraction (XRD), TGA Raman spectroscopy. XRD results revealed the formation highly crystalline NiFe2O4 in samples, while alloys observed catalysts. catalyst has a mesoporous structure with monomodal pore distribution. area decreased from 107.0 to 3.8 m2/g increasing temperature 350 800 °C. Methane conversion, 48.50%, rate, 97.70 × 10-5 mol H2 g−1 min−1 was obtained activity slightly improved by temperature. SEM images some filamentous over all except that operated 700 studies deposited increased increase achieved 42.50 59.32 wt%, respectively. graphitization decreases as increased.

Language: Английский

Citations

25
Predicting physical properties of oxygenated gasoline and diesel range fuels using machine learning DOI Creative Commons

Hussain A. AlNazr,

Nabeel Ahmad, Usama Ahmed

et al.

Alexandria Engineering Journal, Journal Year: 2023, Volume and Issue: 76, P. 193 - 219

Published: June 19, 2023

Understanding the physical properties of distillate petroleum fuels like gasoline and diesel is very critical to ensure normal operation internal combustion (IC) engines with regards processes spray atomization, heating, evaporation etc. Two most important are density viscosity. Many factors such as molecular structure, weight, temperature effect fuel. The present work deals development a machine learning model for predicting viscosity containing oxygenated chemical classes alcohols, esters, ketones aldehydes. was developed using structure compounds expressed in form functional groups inputs. 164 pure spanning various families 14 blends known compositions collected from literature. An artificial neural network (ANN) tool Matlab. Each ANN tested against 15% data results show that models were able successfully predict unseen points good accuracy. A regression coefficient 0.99 (for density) 0.98 viscosity) obtained test set. can be used screen real drop bio-fuels.

Language: Английский

Citations

15
Fish processing discards: A plausible resource for valorization to renewable fuels production, optimization, byproducts and challenges DOI
A. Saravanan,

D. Yuvaraj,

P. Senthil Kumar

et al.

Fuel, Journal Year: 2022, Volume and Issue: 335, P. 127081 - 127081

Published: Dec. 13, 2022

Language: Английский

Citations

21
Machine vision based damage detection for conveyor belt safety using Fusion knowledge distillation DOI Creative Commons
Xiaoqiang Guo, Xinhua Liu, Paolo Gardoni

et al.

Alexandria Engineering Journal, Journal Year: 2023, Volume and Issue: 71, P. 161 - 172

Published: March 25, 2023

A belt conveyor system is one of the essential equipment in coal mining. The damages to belts are hazardous because they would affect stable operation a whilst impairing mining efficiency. To address these problems, novel damage detection method based on CenterNet proposed this paper. fusion feature-wise and response-wise knowledge distillation proposed, which balances performance size deep neural network. Fused Channel-Spatial Attention compress latent feature maps efficiently, Kullback-Leibler divergence introduced minimize distribution distance between student teacher networks. Experimental results show that lightweight object model reaches 92.53% mAP 65.8 FPS. can detect efficiently accurately, indicates its high potential deploy end devices.

Language: Английский

Citations

13