Machine Learning-Assisted Sustainable Mix Design of Waste Glass Powder Concrete with Strength–Cost–CO₂ Emissions Trade-Offs by Yuzhuo Zhang, Jiale Peng, Zi Wang, Meng Xi, Jinlong Liu, Lei Xu

“…A robust database of 1154 experimental records was developed, focusing on five key predictors: cement content, water-to-binder ratio, aggregate composition, glass powder content, and curing age. Seven ML models were optimized via Bayesian tuning, with the Ensemble Tree model achieving superior accuracy (R² = 0.959 on test data). …”
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Spatio-temporal evolution of habitat quality and its influencing factors in karst areas based on the InVEST model. by Chao Ma, Huituo Yang, Zhi Yan

“…Such measures contribute to the scientific underpinning for decision-making regarding the optimization of regional landscape composition and enhance land spatial planning strategies.…”
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Performance of a Batch Operation Microbial Fuel Cell (MFC) with Cobalt Micronutrient Addition Based on Kinetic Models by Sri Rachmania Juliastuti, Fitria Nur Laily, Raden Darmawan

“…The maximum power density was attained at a substrate concentration of 4:1 (w/v) exceeding 25,000 mW/m². The presented model facilitated the enhancement and optimization of MFC performance. …”
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Adsorption of Rhodamine B dye from solution using 3-((1-(4-((1H-benzo[d]imidazol-2-yl)amino)phenyl)ethylidene)amino)phenol (BIAPEHB)/ P(AA-co-AM) composite by Hayder O. Jamel, Maryam H. Jasim, Makarim A. Mahdi, Safaa H. Ganduh, Maryam Batool, Layth S. Jasim, Muhammad Nouman Haider

“…Optimized parameters include contact time of 120 min at pH 10 using 0.12 g of BIAPEHB loading to prepare composite. …”
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Plasma-Induced Abatement of Tar from Syngas Produced in Municipal Waste Gasification: Thermodynamic Modeling with Experimental Validation by Mobish A. Shaji, Francis Eboh, Alexander Rabinovich, Liran Dor, Alexander Fridman

“…Determining thermodynamic energy requirements and the equilibrium composition of products during tar reformation can aid with the proper optimization of the treatment process. …”
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Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning by Muhammad Salman Khan, Tianbo Peng, Tianbo Peng, Muhammad Adeel Khan, Asad Khan, Mahmood Ahmad, Mahmood Ahmad, Kamran Aziz, Mohanad Muayad Sabri Sabri, N. S. Abd EL-Gawaad

“…Accurately predicting key engineering properties, such as compressive and tensile strength, remains a significant challenge in high-performance concrete (HPC) due to its complex and heterogeneous composition. Early selection of optimal components and the development of reliable machine learning (ML) models can significantly reduce the time and cost associated with extensive experimentation. …”
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Debiased Learning via Composed Conceptual Sensitivity Regularization by Sunghwan Joo, Taesup Moon

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Revealing effect of oxide scale on decarburization behaviour of 55Cr3 spring steel: Experimental and modelling research by Zhaoqi Song, Haitao Zhao, Kaixun Wang, Junheng Gao, Chengming Wang, Xiaoqian Yang, Honghui Wu, Yuhe Huang, Chaolei Zhang, Jun Lu, Shuize Wang, Xinping Mao

“…This explains the discrepancies between the phase diagram calculated and the observed decarburization ferrite occurrence temperature range. A modified numerical model incorporating the scale/substrate interfacial equilibrium carbon content determined by multiple oxides successfully predicts the decarburization ferrite thickness of the experimental in 55Cr3 steel, offering direct guidance for heat treatment parameter optimization to minimize surface decarburization. …”
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Artificial neural network and response surface method-based optimization of unsteady natural convective heat transfer of Fe3O4-Engine Oil nanofluid in a trapezoidal enclosure by Umme Salma, Md. Shariful Alam, S. M. Chapal Hossain, Md. Nurul Huda, Tarikul Islam

“…The optimization process employs response surface methodology (RSM), and artificial neural networks (ANN) based on a one-component thermally equilibrium mathematical model. …”
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Sensitivity analysis and optimization of heat transfer in the time-reliant magnetohydrodynamic bioconvective flow of radiative couple-stress hybrid nanofluid through a squeezing ch... by Seetalsmita Samal, Surender Ontela

“…The current numerical study stands out because it optimizes heat transmission rate using a face-centered central composite design framework with RSM (Response Surface Methodology) and analyses its sensitivity toward effective parameters. …”
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AMMap tool for additive manufacturing design, alloy discovery, and path planning by Alexander M Richter, Adam M Krajewski, Zhening Yang, Allison M Beese, Zi-Kui Liu

“…Equilibrium thermodynamic calculations and solidification simulations, such as Scheil–Gulliver, can be used to predict feasible compositions or compositional paths, acting as constraints before empirical or machine learning models are applied to predict properties of interest. …”
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Fully‐Printed Ion Sensor Arrays for Measuring Agricultural Nitrogen and Potassium Concentrations Using Nernstian and AI Models by Payton Goodrich, Nithila Poongovan, Elliot Strand, Carolyn Schwendeman, Lucas Lahann, Sophia Koh, Yuting Cai, Carol Baumbauer, Anju Toor, Gregory Whiting, Ana Claudia Arias

“…By enabling more precise and efficient fertilizer application, these sensor arrays coupled to computational models can help increase crop yields, optimize resource use, and reduce environmental impact.…”
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Advanced generalized machine learning models for predicting hydrogen–brine interfacial tension in underground hydrogen storage systems by Ahmed Farid Ibrahim

“…Sensitivity analysis and SHAP (Shapley Additive Explanations) analysis revealed temperature as the dominant factor influencing IFT, followed by CO2 concentration and pressure, while divalent salts (CaCl2, MgCl2) exhibited a stronger impact than monovalent salts (NaCl, KCl). This study optimizes hydrogen storage by offering a generalized, high-accuracy ML model that captures nonlinear fluid interactions in H2–brine systems. …”
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On the Nonlinear Forced Vibration of the Magnetostrictive Laminated Beam in a Complex Environment by Nicolae Herisanu, Bogdan Marinca, Vasile Marinca

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Development of a mathematical model of an autonomous power supply source with a free piston motor on the basis of a synchronous electric returning machine with a permanent magnets by A. R. Safin, I. V. Ivshin, E. I. Gracheva, T. I. Petrov

“…Using a synchronous electric reciprocating machine with permanent magnets in power plants of a modular type makes it possible to rationally design an autonomous power supply source, to obtain the most optimal design. The development of methodological design decisions and the optimization of engine design parameters as part of generating and drive complexes is an important scientific task. …”
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Effect of fitting tolerance on mechanical performance of CFRP/Al double-lap blind riveted joints by Hanli Zhang, Bingbing Wang, Yucan Qin, Zhengqiang Tang

“…Abstract Blind rivets are widely used in connecting composite materials. However, due to the anisotropic properties, as well as the complex failure modes of the composite materials, it is difficult to optimize the joint design of the riveted joint. …”
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TetraRNA, a tetra-class machine learning model for deciphering the coding potential derivation of RNA world by Hanrui Bai, Jie Wang, Xiaoke Jiang, Zhen Guo, Wenjing Yang, Zitian Yang, Jing Li, Changning Liu

“…Therefore, in this study, we devised a novel tetra-class RNA classification model that is systematically optimized for RNA feature extraction. …”
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Achieving Ultra-Low-Sulfur Model Diesel Through Defective <i>Keggin</i>-Type Heteropolyoxometalate Catalysts by Natali de la Fuente, Jin An Wang, Lifang Chen, Miguel A. Valenzuela, Luis E. Noreña, Elizabeth Rojas, Julio González, Mu He, Jiang Peng, Xiaolong Zhou

“…In the oxidation of dibenzothiophene (DBT) in a model diesel within a biphasic system, DBT conversion exceeded 99% under the optimal reaction conditions (reaction temperature 70 °C, reaction time 60 min, H₂O₂/sulfur molar ratio 8, H₂O₂/formic acid molar ratio 1.5, catalyst concentration 2 mg/mL). …”
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Effects of different vegetation restoration models on soil nutrients in the water level fluctuation zone of a large reservoir by Bai Qinfei, Bao Yuhai, Yu Yantong, Yang Jie, Wang Yanqi, Wei Jie

“…Assessing the influence of diverse vegetation restoration strategies on soil nutrient content in the WLFZ is essential for optimizing restoration models. To evaluate the effects of different restoration approaches on soil nutrients in the WLFZ of Heilongtan Reservoir, the integrated levels of soil nutrients in similar topographical environments but with varying vegetation restoration strategies were quantitatively assessed using the entropy weight method. …”
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Microstructural characterization and hardness prediction of AlCuCrFeNi high entropy alloys using Transformer-based Physics-Informed Neural Networks (T-PINN) by Mohamed Yasin Abdul Salam, Enoch Nifise Ogunmuyiwa, Victor Kitso Manisa, Abid Yahya, Irfan Anjum Badruddin

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