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Bridging the microstructural evolutions from slurry to porous electrode of a lithium-ion battery

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Journal of Energy Chemistry 2023年第9期84卷 329-334页

作者： Hamid Hamed Zoleikha Mirzaie Alamooti Ashutosh Agrawal Jan D'Haen An Hardy Mohammadhosein Safari Institute for Materials Research(imo-imomec) UHasseltMartelarenlaan 42B-3500 HasseltBelgium Energyville Thor Park 8320B-3600 GenkBelgium IMEC Division imomec BE-3590Belgium

1. Introduction The porous electrodes are the crucial components of the modern electrochemical devices including lithium-ion batteries. The detailed configuration of the lithium-insertion, carbon black, and PVDF binder particles in a typical electrode of a lithium-ion cell has a significant impact on its energy and power density. A thinner electrode is desired to decrease the battery volume particularly for portable electronics and mobility applications.

关键词： density. lithium electrode

Analysis of Secured Cloud Data Storage Model for Information

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Journal of Software Engineering and Applications 2024年第5期17卷 297-320页

作者： Emmanuel Nwabueze Ekwonwune Udo Chukwuebuka Chigozie Duroha Austin Ekekwe Georgina Chekwube Nwankwo Department of Computer Science Imo State University Owerri Nigeria Department of Computer Science Gregory University Abia Nigeria Department of Computer Science Anambra State University Awka Nigeria

This paper was motivated by the existing problems of Cloud Data storage in imo State University, Nigeria such as outsourced data causing the loss of data and misuse of customer information by unauthorized users or hackers, thereby making customer/client data visible and unprotected. Also, this led to enormous risk of the clients/customers due to defective equipment, bugs, faulty servers, and specious actions. The aim if this paper therefore is to analyze a secure model using Unicode Transformation Format (UTF) base 64 algorithms for storage of data in cloud securely. The methodology used was Object Orientated Hypermedia Analysis and Design Methodology (OOHADM) was adopted. Python was used to develop the security model;the role-based access control (RBAC) and multi-factor authentication (MFA) to enhance security Algorithm were integrated into the Information System developed with HTML 5, JavaScript, Cascading Style Sheet (CSS) version 3 and PHP7. This paper also discussed some of the following concepts;Development of Computing in Cloud, Characteristics of computing, Cloud deployment Model, Cloud Service Models, etc. The results showed that the proposed enhanced security model for information systems of cooperate platform handled multiple authorization and authentication menace, that only one login page will direct all login requests of the different modules to one Single Sign On Server (SSOS). This will in turn redirect users to their requested resources/module when authenticated, leveraging on the Geo-location integration for physical location validation. The emergence of this newly developed system will solve the shortcomings of the existing systems and reduce time and resources incurred while using the existing system.

关键词： Cloud Data Information Model Data Storage Cloud Computing Security System Data Encryption

Dynamic Signature Verification Using Pattern Recognition

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Journal of Software Engineering and Applications 2024年第5期17卷 214-227页

作者： Emmanuel Nwabueze Ekwonwune Duroha Austin Ekekwe Chinyere Iheakachi Ubochi Henry Chinedu Oleribe Department of Computer Science Imo State University Owerri Nigeria Department of Computer Science Gregory University Abia Nigeria ICT Department Alvan Ikoku University of Education Owerri Nigeria

Dynamic signature is a biometric modality that recognizes an individual’s anatomic and behavioural characteristics when signing their name. The rampant case of signature falsification (Identity Theft) was the key motivating factor for embarking on this study. This study was necessitated by the damages and dangers posed by signature forgery coupled with the intractable nature of the problem. The aim and objectives of this study is to design a proactive and responsive system that could compare two signature samples and detect the correct signature against the forged one. Dynamic Signature verification is an important biometric technique that aims to detect whether a given signature is genuine or forged. In this research work, Convolutional Neural Networks (CNNsor ConvNet) which is a class of deep, feed forward artificial neural networks that has successfully been applied to analysing visual imagery was used to train the model. The signature images are stored in a file directory structure which the Keras Python library can work with. Then the CNN was implemented in python using the Keras with the TensorFlow backend to learn the patterns associated with the signature. The result showed that for the same CNNs-based network experimental result of average accuracy, the larger the training dataset, the higher the test accuracy. However, when the training dataset are insufficient, better results can be obtained. The paper concluded that by training datasets using CNNs network, 98% accuracy in the result was recorded, in the experimental part, the model achieved a high degree of accuracy in the classification of the biometric parameters used.

关键词： Verification Security Biometrics Signature Authentication Model Pattern Recognition Dynamic

Photocatalytic and Electrocatalytic Generation of Hydrogen Peroxide: Principles, Catalyst Design and Performance

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Nano-Micro Letters 2023年第6期15卷 24-72页

作者： Yan Guo Xili Tong Nianjun Yang State Key Laboratory of Coal Conversion Institute of Coal ChemistryChinese Academy of SciencesTaiyuan 030001People’s Republic of China University of Chinese Academy of Sciences Beijing 100049People’s Republic of China Institute of Materials Engineering University of Siegen57076 SiegenGermany Department of Chemistry Hasselt University3590 DiepenbeekBelgium imo‑imomec Hasselt University3590 DiepenbeekBelgium

Hydrogen peroxide(H_(2)O_(2)) is a high-demand organic chemical reagent and has been widely used in various modern industrial applications. Currently,the prominent method for the preparation of H_(2)O_(2) is the anthraquinone oxidation.Unfortunately, it is not conducive to economic and sustainable development since it is a complex process and involves unfriendly environment and potential hazards. In this context, numerous approaches have been developed to synthesize H_(2)O_(2). Among them, photo/electro-catalytic ones are considered as two of the most promising manners for on-site synthesis of H_(2)O_(2). These alternatives are sustainable in that only water or O_(2) is required. Namely, water oxidation(WOR) or oxygen reduction(ORR)reactions can be further coupled with clean and sustainable energy. For photo/electro-catalytic reactions for H_(2)O_(2) generation, the design of the catalysts is extremely important and has been extensively conducted with an aim to obtain ultimate catalytic performance. This article overviews the basic principles of WOR and ORR,followed by the summary of recent progresses and achievements on the design and performance of various photo/electro-catalysts for H_(2)O_(2) generation. The related mechanisms for these approaches are highlighted from theoretical and experimental aspects. Scientific challenges and opportunities of engineering photo/electro-catalysts for H_(2)O_(2) generation are also outlined and discussed.

关键词： H_(2)O_(2)generation Photocatalysts Electrocatalysts Reaction mechanisms

A rare combination of late-onset post-LASIK keratectasia after early-onset central toxic keratopathy

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International Journal of Ophthalmology(English edition) 2022年第11期15卷 1873-1877页

作者： Mehrdad Mohammadpour Masoud Khorrami-Nejad Mohsen Heirani Joseph Oleribe Translational Ophthalmology Research Center Farabi Eye HospitalTehran University of Medical SciencesTehran ***Iran Department of Optometry Imo State UniversityOwerriImo 2000Nigeria

Dear Editor,We have presented the clinical findings of a case with bilateral early-onset central toxic keratopathy(CTK) followed by bilateral late-onset post-LASIK keratectasia. Laser in situ keratomileusis(LASIK) is a safe procedure to treat a broad spectrum of refractive errors;however, unexpected and rarely encountered post-LASIK complications could be a challenge for patient and surgeon.

关键词： rare refractive finding

Physics-based electrical modelling of CIGS thin-film photovoltaic modules for system-level energy yield simulations

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npj Flexible Electronics 2022年第1期6卷 854-862页

作者： Santhosh Ramesh Arttu Tuomiranta Ali Hajjiah Marc Meuris Bart Vermang Jef Poortmans Imec imo-imomecThor Park 83203600 GenkBelgium EnergyVille imo-imomecThor Park 83203600 GenkBelgium KU Leuven Dept.of Electrical Engineering(ESAT)LeuvenBelgium Hasselt University imo-imomecMartelarenlaan 423500 HasseltBelgium Kuwait University Dept.of Electrical EngineeringCollege of Engineering and PetroleumKuwaitKuwait

Copper indium gallium selenide(CIGS)is a commercialized,high-efficiency thin-film photovoltaic(PV)technology.The state-of-theart energy yield models for this technology have a significant normalized root mean square error(nRMSE)on power estimation:De Soto model—26.7%;PVsyst model—12%.In this work,we propose a physics-based electrical model for CIGS technology which can be used for system-level energy yield simulations by people across the PV value chain.The model was developed by considering models of significant electrical current pathways from literature and adapting it for the system-level simulation.We improved it further by incorporating temperature and irradiance dependence of parameters through characterisation at various operating conditions.We also devised a module level,non-destructive characterization strategy based on readily available measurement equipment to obtain the model parameters.The model was validated using the measurements from multiple commercial modules and has a significantly lower power estimation nRMSE of 1.2%.

关键词： CIGS electrical PVsyst

Synergistic interactions between the charge‐transport and mechanical properties of the ionic‐liquid‐based solid polymer electrolytes for solid‐state lithium batteries

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Carbon Energy 2023年第11期5卷 44-53页

作者： Ashutosh Agrawal Saeed Yari Hamid Hamed Tom Gouveia Rongying Lin Mohammadhosein Safari Institute for Materials Research(imoimomec) UHasseltHasseltBelgium Energyville GenkBelgium Solvionic ToulouseFrance IMEC Division imomec DiepenbeekBelgium

The performance sensitivity of the solid‐state lithium cells to the synergistic interactions of the charge‐transport and mechanical properties of the electrolyte is well acknowledged in the literature,but the quantitative insights therein are very limited.Here,the charge‐transport and mechanical properties of a polymerized ionic‐liquid‐based solid electrolyte are reported.The transference number and diffusion coefficient of lithium in the concentrated solid electrolyte are measured as a function of concentration and stack pressure.The elastoplastic behavior of the electrolyte is quantified under compression,within a home‐made setup,to substantiate the impact of stack pressure on the stability of the Li/electrolyte interface in the symmetric lithium cells.The results spotlight the interaction between the concentration and thickness of the solid electrolyte and the stack pressure in determining the polarization and stability of the solid‐state lithium batteries during extended cycling.

关键词： battery diffusion pressure solid state transference

An artificial neural network visible mathematical model for real-time prediction of multiphase flowing bottom-hole pressure in wellbores

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Petroleum Research 2023年第3期8卷 370-385页

作者： Chibuzo Cosmas Nwanwe Ugochukwu Ilozurike Duru Charley Anyadiegwu Azunna I.B.Ekejuba Department of Minerals and Petroleum Resources Engineering Technology Federal Polytechnic NekedeOwerriP.M.B.1036OwerriImo StateNigeria Department of Petroleum Engineering Federal University of TechnologyOwerriP.M.B.1526OwerriImo StateNigeria

Accurate prediction of multiphase flowing bottom-hole pressure(FBHP)in wellbores is an important factor required for optimal tubing design and production optimization.Existing empirical correlations and mechanistic models provide inaccurate FBHP predictions when applied to real-time field datasets because they were developed with laboratory-dependent parameters.Most machine learning(ML)models for FBHP prediction are developed with real-time field data but presented as black-box models.In addition,these ML models cannot be reproduced by other users because the dataset used for training the machine learning algorithm is not open source.These make using the ML models on new datasets difficult.This study presents an artificial neural network(ANN)visible mathematical model for real-time multiphase FBHP prediction in wellbores.A total of 1001 normalized real-time field data points were first used in developing an ANN black-box model.The data points were randomly divided into three different sets;70%for training,15%for validation,and the remaining 15%for testing.Statistical analysis showed that using the Levenberg-Marquardt training optimization algorithm(trainlm),hyperbolic tangent activation function(tansig),and three hidden layers with 20,15 and 15 neurons in the first,second and third hidden layers respectively achieved the best performance.The trained ANN model was then translated into an ANN visible mathematical model by extracting the tuned weights and biases.Trend analysis shows that the new model produced the expected effects of physical attributes on FBHP.Furthermore,statistical and graphical error analysis results show that the new model outperformed existing empirical correlations,mechanistic models,and an ANN white-box model.Training of the ANN on a larger dataset containing new data points covering a wider range of each input parameter can broaden the applicability domain of the proposed ANN visible mathematical model.

关键词： Flowing bottom-hole pressure Real-time prediction Artificial neural network Visible mathematical model Levenberg-marquardt optimization algorithm Hyperbolic tangent activation function Empirical correlations Mechanistic models

Mitigating the Prevalence of Diabetic Retinopathy in the United States: Utilization of the Chronic Care Model as a Public Health Framework

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Open Journal of Ophthalmology 2024年第2期14卷 103-116页

作者： Anthony Obiyom Kamalu Austin Ebhodaghe Ekeoba Emeka Canice Uzor Christian Chukwuka Duru Obinna Princewill Anyatonwu Ogemdi Emmanuel Adiele Chibuike Reginald Amuzie Chima Lawrence Odoemenam Public Health Department Louisiana State University Shreveport Shreveport USA College of Optometry State University of New York New York USA Faculty of Medicine and Health Sciences Department of Optometry Imo State University Owerri Nigeria Epidemiology and Global Health Unit Department of Public Health and Clinical Medicine Umea University Umea Sweden College of Medicine Georgetown University Washington DC USA Public Health Department School of Allied Health Professionals Louisiana State University Health Shreveport Shreveport USA

As the prevalence of diabetic retinopathy continues to be on the rise, the Chronic Care Model (CCM) offers a transformative, patient-focused approach for efficient diabetic retinopathy care, emphasizing the need for urgent and innovative strategies in the United States. The model integrates community resources, healthcare organizations, self-management support, delivery system design, decision support, and clinical information systems. Addressing challenges and solutions, the model emphasizes proactive and preventive measures, collaborative multidisciplinary care, technological integration, and overcoming resistance to change. This paper proposes the utilization of the Chronic Care Model (CCM) as a possible public health framework for comprehensive management of diabetic retinopathy in the United States. Implementing the CCM offers a comprehensive approach to diabetic retinopathy care, addressing both individual and systemic factors, essential for improving public health outcomes.

关键词： Chronic Care Model Diabetes Diabetic Retinopathy Model Implementation Vision Care