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Green Energy & Environment 2024年第10期9卷 1627-1640页

作者： Junaid Saleem Moghal Zubair Khalid Baig Usman Bin Shahid Rafael Luque Gordon McKay Division of sustainable development College of Science and EngineeringHamad Bin Khalifa University Center for Advanced Materials Qatar University department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Universidad ECOTEC

Plastic waste is an underutilized resource that has the potential to be transformed into value-added ***,its chemical diversity leads to cost-intensive sorting techniques,limiting recycling and upcycling ***,we report an open-loop recycling method to produce graded feedstock from mixed polyolefins waste,which makes up 60%of total plastic *** method uses heat flow scanning to quantify the composition of plastic waste and resolves its compatibility through controlled *** resulting feedstock is then used to synthesize blended pellets,porous sorbents,and superhydrophobic coatings via thermally induced phase separation and *** hybrid approach broadens the opportunities for reusing plastic waste,which is a step towards creating a more circular economy and better waste management practices.

关键词： Plastic waste Valorization Superhydrophobic coatings Blended pellets Porous materials Sorbents

Directly predicting N_(2) electroreduction reaction free energy using interpretable machine learning with non-DFT calculated features

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Journal of Energy Chemistry 2024年第10期97卷 139-148,I0004页

作者： Yaqin Zhang Yuhang Wang Ninggui Ma Jun Fan department of Materials Science and Engineering City University of Hong KongHong Kong 999077China Center for Advanced Nuclear Safety and sustainable development City University of Hong KongHong Kong 9077China department of Mechanical Engineering City University of Hong KongHong Kong 999077China

Electrocatalytic nitrogen reduction to ammonia has garnered significant attention with the blooming of single-atom catalysts(SACs),showcasing their potential for sustainable and energy-efficient ammonia ***,cost-effectively designing and screening efficient electrocatalysts remains a *** this study,we have successfully established interpretable machine learning(ML)models to evaluate the catalytic activity of SACs by directly and accurately predicting reaction Gibbs free *** models were trained using non-density functional theory(DFT)calculated features from a dataset comprising 90 graphene-supported *** results underscore the superior prediction accuracy of the gradient boosting regression(GBR)model for bothΔg(N_(2)→NNH)andΔG(NH_(2)→NH_(3)),boasting coefficient of determination(R^(2))score of 0.972 and 0.984,along with root mean square error(RMSE)of 0.051 and 0.085 eV,***,feature importance analysis elucidates that the high accuracy of GBR model stems from its adept capture of characteristics pertinent to the active center and coordination environment,unveilling the significance of elementary descriptors,with the colvalent radius playing a dominant ***,Shapley additive explanations(SHAP)analysis provides global and local interpretation of the working mechanism of the GBR *** analysis identifies that a pyrrole-type coordination(flag=0),d-orbitals with a moderate occupation(N_(d)=5),and a moderate difference in covalent radius(r_(TM-ave)near 140 pm)are conducive to achieving high ***,we extend the prediction of activity to more catalysts without additional DFT calculations,validating the reliability of our feature engineering,model training,and design *** findings not only highlight new opportunity for accelerating catalyst design using non-DFT calculated features,but also shed light on the working mechanism of"black box"ML ***,the model provides valuable g

关键词： Nitrogen reduction Single-atom catalyst Interpretable machine learning Graphene Non-DFT features

A CAD-BEM geometry transformation method for face-based primary geometric input based on closed contour recognition

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Building Simulation 2024年第2期17卷 335-354页

作者： Jun Xiao Hao Zhou Shiji Yang Deyin Zhang Borong Lin department of Building Science School of ArchitectureTsinghua UniversityBeijing100084China Key Laboratory of Eco Planning&Green Building Ministry of EducationTsinghua UniversityBeijing100084China Institute for Urban Governance and sustainable development Tsinghua UniversityBeijing100084China

Performance analysis during the early design stage can significantly reduce building energy ***,it is difficult to transform computer-aided design(CAD)models into building energy models(BEM)to optimize building *** model structures for CAD and BEM are *** this study,geometry transformation methods was implemented in BES tools for the early design stage,including auto space generation(ASG)method based on closed contour recognition(CCR)and space boundary topology calculation *** program is developed based on modeling tools SketchUp to support the CAD format(like*.stl,*.dwg,*.ifc,etc.).It transforms face-based geometric information into a zone-based tree structure model that meets the geometric requirements of a single-zone BES combined with the other thermal parameter inputs of the *** addition,this study provided a space topology calculation method based on a single-zone BEM *** program was developed based on the SketchUp modeling tool to support additional CAD formats(such as*.stl,*.dwg,*.ifc),which can then be imported and transformed into*.*** to current methods mostly focused on BIM-BEM transformation,this method can ensure more modeling *** method was integrated into a performance analysis tool termed MOOSAS and compared with the current version of the transformation *** were tested on a dataset comprising 36 conceptual models without partitions and six real cases with detailed *** ensures a transformation rate of two times in any bad model condition and costs only 1/5 of the time required to calculate each room compared to the previous version.

关键词： geometry transformation building energy model computer aid design closed contour recognition

Proposed numerical and machine learning models for fiber-reinforced polymer concrete-steel hollow and solid elliptical columns

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Frontiers of Structural and Civil Engineering 2024年第8期18卷 1169-1194页

作者： Tang QIONG Ishan JHA Alireza BAHRAMI Haytham F.ISLEEM Rakesh KUMAR Pijush SAMUI School of Applied Technologies Qujing Normal UniversityQujing 655011China department of Civil Engineering Indian Institute of Technology-BHUVaranasi 221005India department of Building Engineering Energy Systems and Sustainability ScienceFaculty of Engineering and Sustainable DevelopmentUniversity of GävleGävle 80176Sweden department of Civil Engineering National Institute of Technology-PatnaPatna 800005India

This study employs a hybrid approach,integrating finite element method(FEM)simulations with machine learning(ML)techniques to investigate the structural performance of double-skin tubular columns(DSTCs)reinforced with glass fiber-reinforced polymer(GFRP).The investigation involves a comprehensive examination of critical parameters,including aspect ratio,concrete strength,number of GFRP confinement layers,and dimensions of steel tubes used in DSTCs,through comparative analyses and parametric *** ensure the credibility of the findings,the results are rigorously validated against experimental data,establishing the precision and trustworthiness of the *** present research work examines the use of the columns with elliptical cross-sections and contributes valuable insights into the application of FEM and ML in the design and evaluation of structural systems within the field of structural engineering.

关键词： elliptical column fiber-reinforced polymer machine learning finite element method ABAQUS

Techno-economic and environmental impact analysis of electric two-wheeler batteries in India

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Clean Energy 2024年第3期8卷 147-156页

作者： Aman Gupta Ditipriya Bose Sandeep Tiwari Vikrant Sharma Jai Prakash department of Green Energy and sustainable development Zakir Husain College of Engineering and Technology Aligarh Muslim UniversityUttar Pradesh-202002India Battery Testing Facility National Institute of Solar EnergyGurugram-Faridabad RoadGwal PahariGurugram-122003HaryanaIndia

This paper presents a comprehensive techno-economic and environmental impact analysis of electric two-wheeler batteries in *** technical comparison reveals that sodium-ion(Na-ion)and lithium-ion(Li-ion)batteries outperform lead-acid batteries in various parameters,with Na-ion and Li-ion batteries exhibiting higher energy densities,higher power densities,longer cycle lives,faster charge rates,better compactness,lighter weight and lower self-discharge *** economic comparison,Na-ion batteries were found to be~12-14%more expensive than Li-ion ***,the longer lifespans and higher energy densities of Na-ion and Li-ion batteries can offset their higher costs through improved performance and long-term ***-acid batteries have the highest environmental impact,while Li-ion batteries demonstrate better environmental performance and potential for ***-ion batteries offer promising environmental advantages with their abundance,lower cost and lower toxic and hazardous material *** recycling processes can further enhance the environmental benefits of Na-ion ***,this research examines the potential of Na-ion batteries as a cheaper alternative to Li-ion batteries,considering India’s abundant sodium resources in regions such as Rajasthan,Chhattisgarh,Jharkhand and others.

关键词： electric two-wheelers environmental impact assessment lead-acid batteries lithium-ion batteries sodium-ion batteries techno-economic analysis

Deep learning to develop zero-equation based turbulence model for CFD simulations of the built environment

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Building Simulation 2024年第3期17卷 399-414页

作者： Giovanni Calzolari Wei Liu Division of sustainable Buildings Department of Civil and Architectural EngineeringKTH Royal Institute of TechnologyBrinnelvägen 23Stockholm11428Sweden

This study aims to improve the accuracy and speed of predictions for thermal comfort and air quality in built environments by creating a coupled framework between computational fluid dynamics(CFD)simulations and deep learning *** coupling approach is showcased by the development of a data-driven turbulence *** new turbulence model is built using a deep learning neural network,whose mapping structure is based on a zero-equation turbulence model for built environment simulations,and is coupled with the CFD software OpenFOAM to create a hybrid *** neural network is a standard shallow multi-layer *** number of hidden layers and nodes per layer was optimized using Bayesan optimization *** framework is trained on an indoor environment case study,as well as tested on an indoor office simulation and an outdoor building array *** show that the deep learning based turbulence model is more robust and faster than traditional two-equation Reynolds average Navier-Stokes(RANS)turbulence models,while maintaining a similar level of *** model also outperforms the standard algebraic zero-equation model due to its superior ability to generalize to various flow *** some challenges,namely the mapping constraint,the limited training dataset size and the source of generation of training data,the hybrid framework demonstrates the viability of the coupling technique and serves as a starting point for future development of more reliable and advanced models.

关键词： neural networks computational fluid dynamics(CFD) turbulence model OpenFOAM

Height and body mass index trajectories from 1975 to 2015 and prevalence of stunting,underweight and obesity in 2016 among children in Chinese cities:findings from five rounds of a national survey

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World Journal of Pediatrics 2024年第4期20卷 404-412页

作者： Xin‑Nan Zong Hui Li Ya‑Qin Zhang department of Growth and development Capital Institute of PediatricsBeijing 100020China

Background A more comprehensive assessment of growth and nutrition in children is required in China due to rapid socioeconomic *** aimed to investigate height and body mass index(BMI)trajectories from 1975 to 2015 and the prevalence of stunting and obesity in 2016 among children in Chinese *** A total of 904,263 children from birth to 6.9 years were collected from a series of nationally representative surveys in *** and BMI trajectories and prevalence of stunting,underweight,overweight and obesity were *** The average height level of Chinese urban children under 7 years presented a positive secular trend from 1975 to 2015;however,a slowing tendency occurred in 2005‒*** apparent increase was observed at the 5th,50th and 95th percentiles of BMI in urban children aged 3 years and older,with a more prominent increase at the 95th *** total prevalence of stunting and underweight under 7 years was 1.4%and 2.0%,*** total prevalence of overweight and obesity under 7 years was 12.6%and 4.3%,respectively,with 12.7%and 4.9%for boys,12.6%and 3.6%for girls,12.1%and 4.0%in urban areas and 13.1%and 4.5%in suburban rural *** The average height level of Chinese urban children has reached World Health Organization child growth standards since 2005 and presented a slowing tendency in secular trend in 2005‒*** attention and efforts and public health interventions should be urgently made to combat overweight and obesity among preschool children.

关键词： Body mass index Children Height Obesity Stunting

Thermo-Physical Potential of Recycled Banana Fibers for Improving the Thermal and Mechanical Properties of Biosourced Gypsum-Based Materials

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Journal of Renewable Materials 2024年第4期12卷 843-867页

作者： Youssef Maaloufa Soumia Mounir Sara Ibnelhaj Fatima Zohra El Wardi Asma Souidi Yakubu Aminu Dodo Malika Atigui Mina Amazal Abelhamid Khabbazi Hassan Demrati Ahmed Aharoune National School of Architecture Agadir New ComplexIbn Zohr UniversityAgadirMorocco Energy Materials and Sustainable Development(EMDD)Center for WaterNatural ResourcesEnvironment and Sustainable Development(CERNE2D)Mohammed V UniversityRabatMorocco Thermodynamics and Energetics Laboratory Faculty of ScienceIbn Zohr UniversityAgadirMorocco Architectural Engineering department Najran UniversityNajranSaudi Arabia The Centre of Scientific and Engineering Research Najran UniversityNajranSaudi Arabia Physics department LPMAT LaboratoryFaculty of Sciences Ain ChockHassan II UniversityCasablancaMorocco

The development of bio-sourced materials is essential to ensuring sustainable construction;it is considered a locomotive of the green ***,it is an abundant material in our country,to which very little attention is being *** work aims to valorize the waste of the trunks of banana trees to be used in ***,the physicochemical properties of the fiber,such as the percentage of crystallization and its morphology,have been determined by X-ray diffraction tests and scanning electron microscopy to confirm the potential and the impact of the mode of drying on the quality of the banana fibers,with the purpose to promote the use of this material in ***,the results obtained with the gypsum matrix allowed us to note a preponderant improvement in the composite’s thermal properties thanks to the variation of the banana fiber ***,the impact of the nature of the banana fiber distribution(either fiber mixed in matrix or fiber series model)on the flexural and compressive strengths of the composites was *** results obtained indicate that the insulation gain reaches up to 40%.It depends on the volume fraction and type of distribution of the banana ***,the thermal inertia of the composites developed,represented by thermal diffusivity and thermal effusivity,was *** indicate a gain of 40%and 25%,respectively,in terms of thermal diffusivity and thermal effusivity of the developed composites compared to plaster *** the mechanical properties,the flexural strength depends on the percentage of the volume fraction of banana fibers used,and it can reach 20%more than the flexural strength of plaster;nevertheless,there is a significant loss in terms of the compressive strength of the studied *** results obtained are confirmed by the microstructure of the fiber *** fact,the morphology of the banana fibers was improved by the drying *** reduces the amorphous area an

关键词： Biosourced materials fiber banana flexural strength mechanical properties open-air drying plaster thermal properties waste management

Dual PPAR delta/gamma agonist offer therapeutic potential for Alzheimer's disease

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Neural Regeneration Research 2024年第6期19卷 1175-1176页

作者： Ian Steinke Meenakshi Singh Rajesh Amin department of Drug Discovery and development Auburn UniversityAuburn AlabamaALUSA

The increasing incidence of Alzheimer's disease(AD)in the aging population,indicates the critical need for the development of novel targeted molecular therapies for ameliorating AD ***,clinical and preclinical evidence demonstrates that peroxisomal proliferator activating receptors(PPAR)agonists regulate energy and lipid homeostasis in models of diabetes,as well as improve spatial memory in animal models of AD(Khan et al.,2019).

关键词： Alzheimer clinical homeostasis

Growth and development of children in China:achievements,problems and prospects

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World Journal of Pediatrics 2024年第2期20卷 97-104页

作者： Xin-Nan Zong Hui Li department of Growth and development Capital Institute of PediatricsBeijing 100020China

Growth reflects the general condition of society,and is a measure of the nutritional and hygienic status of a population[1,2].Nutrition is one of the most important components of children’s well-being[3].The Chinese government attaches great importance to children’s health and development,with a clear statement and consistent practice for“Children are the future and hope of the motherland”.

关键词： mother statement children