Engineering Development Research Articles

Advanced parametrization for the production of high-energy solid-state lithium pouch cells containing polymer electrolytes

Lithium batteries with solid-state electrolytes are an appealing alternative to state-of-the-art non-aqueous lithium-ion batteries with liquid electrolytes because of safety and energy aspects. However, engineering development at the cell level for lithium batteries with solid-state electrolytes is limited. Here, to advance this aspect and produce high-energy lithium cells, we introduce a cell design based on advanced parametrization of microstructural and architectural parameters of electrode and electrolyte components. To validate the cell design proposed, we assemble and test (applying a stack pressure of 3.74 MPa at 45 °C) 10-layer and 4-layer solid-state lithium pouch cells with a solid polymer electrolyte, resulting in an initial specific energy of 280 Wh kg−1 (corresponding to an energy density of 600 Wh L−1) and 310 Wh kg−1 (corresponding to an energy density of 650 Wh L−1) respectively.

NRIMD, a Web Server for Analyzing Protein Allosteric Interactions Based on Molecular Dynamics Simulation.

Long-range allosteric communication between distant sites and active sites in proteins is central to biological regulation but still poorly characterized, limiting the development of protein engineering and drug design. Addressing this gap, NRIMD is an open-access web server for analyzing long-range interactions in proteins from molecular dynamics (MD) simulations, such as the effect of mutations at distal sites or allosteric ligand binding at allosteric sites on the active center. Based on our recent works on neural relational inference using graph neural networks, this cloud-based web server accepts MD simulation data on any length of residues in the alpha-carbon skeleton format from mainstream MD software. The input trajectory data are validated at the frontend deployed on the cloud and then processed on the backend deployed on a high-performance computer system with a collection of complementary tools. The web server provides a one-stop-shop MD analysis platform to predict long-range interactions and their paths between distant sites and active sites. It provides a user-friendly interface for detailed analysis and visualization. To the best of our knowledge, NRIMD is the first-of-its-kind online service to provide comprehensive long-range interaction analysis on MD simulations, which significantly lowers the barrier of predictions on protein long-range interactions using deep learning. The NRIMD web server is publicly available at https://nrimd.luddy.indianapolis.iu.edu/.

The Rise of Molecular Image-Guided Robotic Surgery.

Following early acceptance by urologists, the use of surgical robotic platforms is rapidly spreading to other surgical fields. This empowerment of surgical perception via robotic advances occurs in parallel to developments in intraoperative molecular imaging. Convergence of these efforts creates a logical incentive to advance the decades-old image-guided robotics paradigm. This yields new radioguided surgery strategies set to optimally exploit the symbiosis between the growing clinical translation of robotics and molecular imaging. These strategies intend to advance surgical precision by increasing dexterity and optimizing surgical decision-making. In this state-of-the-art review, topic-related developments in chemistry (tracer development) and engineering (medical device development) are discussed, and future scientific robotic growth markets for molecular imaging are presented.

Phase transitions limit lithium adsorption in titanium-based ion sieves

Hydrogen titanium oxide (HTO) is a promising material in extracting lithium ions from dilute sources such as geothermal or oil/gas brines. However, experiments show limited Li adsorption in HTO compared to its theoretical maximum capacity, where all H atoms in HTO are replaced by Li that forms lithium titanium oxide (LTO). Here, ab initio molecular dynamics (AIMD) simulations show clear evidence of phase transitions at specific Li adsorption in pure or doped HTO/LTO, which directly predict their experimental maximum capacity. Analysis of thermodynamic properties as well as layered crystal structures show distinct Li-poor to Li-rich phase transitions in the pure, Mo-doped, and Fe-doped HTO/LTO. In addition, it is observed a second phase transition in the Fe-doped HTO/LTO in the Li-poor phases that further constrains Li adsorption. To the best of my knowledge, this is the first study that accurately predict the experimental capacities in ion sieves from first principle. More importantly, this study puts spotlights on phase transitions as an important consideration in molecular engineering developments of functional separation materials, such as the high-performance lithium-ion sieves presented herein.

Modern Features of Radioactive Substance Content Dynamics Simulation in Multi-walled Stores

The world’s sustainable development of nuclear power engineering during last decades resulted in large number of radioactive wastes. Currently, each state having nuclear power engineering systems in possession, utilizes the concept of geological disposal as a long-term strategy of radioactive wastes treatment that requires continuous advancements in methods and means due to wastes and standards of radiation monitoring stringency. The article considers the features of radioactive substance content dynamics simulation for single- and multi-walled solid radioactive waste stores, being the product of uranium production, represented by one-dimensional equations and the second and first order sets of equations. The potentials of the existing models, that take into account complex interactions between radionuclides and environment along with possible sources of pollution and mechanisms of radioactive substance transfer, were reviewed. The data availability of temporary radionuclide content evolution inside the store to assess possible effect on environment and people based on the results of mathematical modelling of the considered numerical expressions was emphasized. It was shown, that current models allow analysing and predicting transfer of radionuclide solutions and other substances due to finding solution to contemporary scientific engineering and environmental problems. It was noted, that nowadays there is no model providing forecast of radionuclide content spatial and temporal variations within various store layers to study the accumulated radioactive wastes revealing the mechanisms of their formation, to analyse the features of their distribution, to determine the areas of their active concentration and to define the radionuclide migration activity during storage.

FEA of Bajaj Discover 100 cc Connecting Rod for Aluminum Material

The connecting rod is a vital component of internal combustion engines, responsible for converting the piston's linear motion into rotational motion. Its design involves careful consideration of material selection, geometry, and load distribution to ensure it can withstand the dynamic forces and stresses encountered during engine operation. Finite element analysis plays a crucial role in evaluating the structural performance of the connecting rod, allowing engineers to optimize its design for maximum efficiency and reliability. By understanding the complexities of connecting rod design and the forces acting upon it, engineers can develop robust and high-performing engines that meet the demands of modern automotive applications. The paper describes a case study that was crucial to the engine development program's evaluation of the connecting rod's strength and fatigue analysis for Bajaj Discover 100 cc engine. The basic model was prepared using appropriate modeling software and then it was analyzed in Ansys for strength and fatigue analysis. The compressive and tensile loading was applied on the both ends of the connecting rod and the results were found. The location of the maximum stress was found.

Modifying Injection Equipment Components for Their Adaptation to Work with Greener Hydrogen-Containing Fuels for Non-Road Vehicle Engines

This article presents the authors’ considerations regarding the possibilities of developing fuel equipment for modern compression ignition engines used in special and non-road vehicles. The paper discusses the process of fuel combustion and atomization in the chamber of a piston combustion engine. The paper then presents the concept of modifying the atomizer of a modern fuel injector for operation using hydrogen-containing fuels of plant origin. The authors present a review of tests performed using an engine dynamometer on a modern engine with a Common Rail system running on biofuel. The CI engine operated with standard and modified fuel injectors. During the tests, the external ecological characteristics of the engine were analyzed as a function of rotational speed; the values of injection doses at individual rotational speeds and their effects on the characteristics were read from the current parameters, and the pressure and temperature in the engine’s combustion chamber were measured. The research results show that implementing the changes proposed by the authors of this work is a good direction for the development of compression ignition engines.

Expanding chemistry through in vitro and in vivo biocatalysis.

Living systems contain a vast network of metabolic reactions, providing a wealth of enzymes and cells as potential biocatalysts for chemical processes. The properties of protein and cell biocatalysts-high selectivity, the ability to control reaction sequence and operation in environmentally benign conditions-offer approaches to produce molecules at high efficiency while lowering the cost and environmental impact of industrial chemistry. Furthermore, biocatalysis offers the opportunity to generate chemical structures and functions that may be inaccessible to chemical synthesis. Here we consider developments in enzymes, biosynthetic pathways and cellular engineering that enable their use in catalysis for new chemistry and beyond.

Racial/Ethnic Disparities and Immunotherapeutic Advances in the Treatment of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) remains one of the leading causes of death among many associated liver diseases. Various conventional strategies have been utilized for treatment, ranging from invasive surgeries and liver transplants to radiation therapy, but fail due to advanced disease progression, late screening/staging, and the various etiologies of HCC. This is especially evident within racially distinct populations, where incidence rates are higher and treatment outcomes are worse for racial/ethnic minorities than their Caucasian counterparts. However, with the rapid development of genetic engineering and molecular and synthetic biology, many novel strategies have presented promising results and have provided potential treatment options. In this review, we summarize past treatments, how they have shaped current treatments, and potential treatment strategies for HCC that may prove more effective in the future.

Mass Spectrometry of Collagen-Containing Allogeneic Human Bone Tissue Material.

The current paper highlights the active development of tissue engineering in the field of the biofabrication of living tissue analogues through 3D-bioprinting technology. The implementation of the latter is impossible without important products such as bioinks and their basic components, namely, hydrogels. In this regard, tissue engineers are searching for biomaterials to produce hydrogels with specified properties both in terms of their physical, mechanical and chemical properties and in terms of local biological effects following implantation into an organism. One of such effects is the provision of the optimal conditions for physiological reparative regeneration by the structural components that form the basis of the biomaterial. Therefore, qualitative assessment of the composition of the protein component of a biomaterial is a significant task in tissue engineering and bioprinting. It is important for predicting the behaviour of printed constructs in terms of their gradual resorption followed by tissue regeneration due to the formation of a new extracellular matrix. One of the most promising natural biomaterials with significant potential in the production of hydrogels and the bioinks based on them is the polymer collagen of allogeneic origin, which plays an important role in maintaining the structural and biological integrity of the extracellular matrix, as well as in the morphogenesis and cellular metabolism of tissues, giving them the required mechanical and biochemical properties. In tissue engineering, collagen is widely used as a basic biomaterial because of its availability, biocompatibility and facile combination with other materials. This manuscript presents the main results of a mass spectrometry analysis (proteomic assay) of the lyophilized hydrogel produced from the registered Lyoplast® bioimplant (allogeneic human bone tissue), which is promising in the field of biotechnology. Proteomic assays of the investigated lyophilized hydrogel sample showed the presence of structural proteins (six major collagen fibers of types I, II, IV, IX, XXVII, XXVIII were identified), extracellular matrix proteins, and mRNA-stabilizing proteins, which participate in the regulation of transcription, as well as inducer proteins that mediate the activation of regeneration, including the level of circadian rhythm. The research results offer a new perspective and indicate the significant potential of the lyophilized hydrogels as an effective alternative to synthetic and xenogeneic materials in regenerative medicine, particularly in the field of biotechnology, acting as a matrix and cell-containing component of bioinks for 3D bioprinting.

Preface

The 4th International Conference on Materials Chemistry and Environmental Engineering (CONF-MCEE 2024) is an annual conference focusing on research areas including materials science and engineering, chemical science and technology, and environmental engineering. It aims to establish a broad and interdisciplinary platform for experts, researchers, and students worldwide to present, exchange, and discuss the latest advance and development in materials, chemistry, and environmental engineering. This volume contains the papers of the 4th International Conference on Materials Chemistry and Environmental Engineering (CONF-MCEE 2024). Each of these papers has gained a comprehensive review by the editorial team and professional reviewers. Each paper has been examined and evaluated for its theme, structure, method, content, language, and format. Cooperating with prestigious universities, CONF-MCEE 2024 organized four workshops in London, Tampa, Eskişehir, and Wuhan. Dr. Seyed Ghaffar chaired the workshop “The Influence of Nano-Additives in Low-Carbon 3D Printable Cementitious Materials”, which was held at the University of Birmingham. Dr. Ioannis Spanopoulos chaired the workshop “Perovskite Solar Cells Challenges and Promises” at University of South Florida. And Dr. Ömer Burak İSTANBULLU chaired the workshop “Preserving Clarity: Enhancing Image and Signal Quality for Computer-Aided Diagnosis and Treatment in Biomedical Engineering” at Eskişehir Osmangazi University. Besides these workshops, CONF-MCEE 2024 also held an online session. Eminent professors from top universities worldwide were invited to deliver keynote speeches in this online session, including Dr. Ioannis Spanopoulos from University of South Florida and Dr. Ömer Burak İSTANBULLU from Eskişehir Osmangazi University. They have given keynote speeches on related topics of materials, chemistry, and environmental engineering. On behalf of the committee, we would like to give sincere gratitude to all authors and speakers who have made their contributions to CONF-MCEE 2024, editors and reviewers who have guaranteed the quality of papers with their expertise, and the committee members who have devoted themselves to the success of CONF-MCEE 2024. List of Committee Members are available in this Pdf.

Identification and prediction method for acoustic emission and electromagnetic radiation signals of rock burst based on deep learning

With the deep development of underground rock engineering, the threat of rock burst disasters is increasing. At present, the identification and prediction of rock burst mostly rely on the experience of field staff to determine the critical value and development trend, and there is a lack of efficient and intelligent methods for the utilization of massive data. Therefore, this paper constructs a rock burst signal recognition and prediction model based on deep learning methods to solve the above problems. In this paper, the acoustic emission (AE) and electromagnetic radiation (EMR) data of the site are first marked and input into the long-short-term memory-fully connected neural network model to realize the identification of rock burst danger signals. Then, the graph data of the AE and EMR sensor monitoring networks are constructed and input into the spatiotemporal graph convolutional network signal prediction model to predict future monitoring data. Finally, this paper uses the same dataset to compare and analyze several other commonly used deep learning models. The results show that the model constructed in this paper has the best performance in the identification and prediction of AE and EMR signals with rockburst risk. This study can provide theoretical reference for intelligent monitoring and early warning of rock burst in underground rock engineering.

Characterisation Techniques for Bituminous Binder

Bituminous binders, often referred to as asphalt, play a pivotal role in the construction and maintenance of flexible pavements. As the demand for durable and sustainable infrastructure continues to rise, a thorough understanding of the physical and rheological properties of bituminous binders becomes imperative. This manuscript presents a comprehensive review of various mechanical tests used to assess bituminous binder properties, including penetration (Pen), softening point (SP), penetration ratio (PR), penetration index (PI), ductility tests and absolute and kinematic viscosities. These mechanical tests serve as fundamental tools for evaluating binder consistency, hardness, ductility and flow behaviour. SP and Pen measurements are employed to grade bituminous binders based on their response to temperature. Additionally, PR and PI provide valuable insights into binder performance under varying environmental conditions. Ductility tests offer critical information about a binder’s ability to elongate without breaking, a crucial factor in withstanding the stresses imposed by traffic. In parallel, the manuscript underscores the significance of understanding the rheological properties of bituminous binders. Dynamic shear rheometry (DSR) is introduced as a method for characterising complex modulus (G*), fail temperature and phase angle (δ) behaviour under different temperature and loading conditions. These tests are well established in the USA based on Strategic Highway Research Program (SHRP) specifications. Their relevance in the Indian context is discussed, with recent inclusion of rheological parameters in the Bureau of Indian Standards (BIS) specification. The manuscript highlights the role of instrumental analysis techniques, including Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR) and scanning electron microscopy (SEM), in uncovering the molecular and microstructural aspects of bituminous binders. FTIR aids in identifying functional groups within the binder, elucidating chemical composition and aging effects, while NMR provides insights into molecular mobility and heterogeneity. SEM is instrumental in revealing the binder’s microstructure and its interaction with aggregates. In conclusion, this manuscript offers a comprehensive analysis of both mechanical and rheological testing, emphasising their significance in evaluating bituminous binder properties. It also stresses the growing importance of instrumental analysis techniques, particularly for chemically modified bitumen. The primary aim is to provide a valuable resource for researchers, engineers and practitioners in the field of civil engineering and infrastructure development.

Implementasi Machine Learning Untuk Prediksi Harga Laptop Menggunakan Algoritma Regresi Linear Berganda

This article discusses the implementation of machine learning using multiple linear regression algorithms to predict laptop prices. The main objective of this research is to design an appropriate predictive model based on various features such as technical specifications and laptop brands. The research stages include literature study, collection of relevant datasets, pre-processing or data cleaning, Exploratory Data Analysis, Feature Engineering, data splitting, model building, and website development. The results show that the proposed model is able to provide price predictions with a high level of accuracy, measured using evaluation metrics such as Mean Absolute Error (MAE) which produces a value of 0.18 and R-squared (R²) which has a value of 0.68. Implementation was done by integrating Jupyter Notebook, Visual Studio Code (VS Code) and Streamlit for interactive web application development. The conclusion of this research is that the multiple linear regression algorithm is effective in predicting laptop prices, and can be used as a tool in making business decisions and pricing strategies.

Applied Ideation Methodology Selector Tool

AbstractIn engineering and product development, it is challenging to identify the most promising opportunities to work on, translate those opportunities into well‐defined problem statements, generate many alternative concepts, and select/implement the most promising concepts. Many well‐known tools aim to put structured processes around the ideation or concept generation phase, including, but not limited to, Theory of Inventive Problem Solving (TRIZ), Yilmaz et al. 77 Design Heuristics, Biomimicry, and Brainwriting. Herein, the authors identify thirteen methods specific to concept generation, clearly define and differentiate what these methods excel at, and provide structured reasoning as to why some methods are preferred in various situations over others. Following this reasoning the authors propose a Microsoft Excel‐based tool built off a modified version of Analytic Hierarchy Process (AHP) that with user input will recommend the best set of ideation methodologies for the users' scenario. Seven criteria definitions were established to differentiate and rank each ideation methodology. Multiple test cases demonstrate the results of the selection tool to be predictable and rational. Possible future work includes adding additional ideation methodologies to the Excel based tool, further validation by more users, and expanding it to include tools for both problem definition and concept selection/implementation methodologies. The authors feel that doing great systems engineering must begin with a great architecture/concept, and this tool can facilitate routine development of highly innovative, high‐valued solutions that, when well executed via a rigorous systems engineering process, will create exceptional enterprise value.

Extending SysML Model Federation to Support Systems of Systems Multilevel Security Development

AbstractPractitioners of modern systems engineering within the defense industry and intelligence community often find themselves being pulled in diametrically opposed directions. On the one hand, systems engineering is quickly evolving into a digital practice, strategically connecting heterogeneous sets of models to form digital threads and digital twins capable of providing insights more valuable than the sum of their parts. On the other hand, the inherent nature of working within the national security space necessitates information be held a multiple levels of classification, safeguarded from release, and compartmentalized. This paper focuses on Model Based Systems Engineering (MBSE) development to introduce methods and tools to aid in overcoming these challenges. The work presented here builds on previously published works in SysML Model Federation for Systems of Systems (SoS) Architecting, the experience of applying this methodology on real world programs. Furthermore, it leverages freely available MBSE tools, processes, and methods in the construction of System Architecture Models (SAMs). This paper culminates in a call to action for additional published research and development to address residual challenges and gaps with respect to executing MBSE for Multilevel Security (MLS) development.

Biogenic construction: The new era of civil engineering

With the increasing demand for buildings and infrastructures and the mounting challenges associated with the current construction technologies such as high emission, high pollution, and high energy consumption, the civil engineering profession is at the crossroad for a transformation or upgrading before it can be put into tasks for these challenges. Inspired by the concept of harmonious coexistence between humans and nature, a new concept, biogenic construction, for civil engineering is proposed in this paper. The definition of biogenic construction is given. The framework and four components of biogenic construction are established. These include microbial construction, plant construction, animal construction, and bioinspired construction. Examples of each component are given. A new construction system for creating a more eco-friendly, healthier, and more sustainable environment for future civil engineering developments is also proposed.

A Evolution and Impact of Web Search Engines: A Comprehensive Review

Web search engines have become indispensable tools in our daily lives, revolutionizing the way we access and navigate the vast expanse of information available on the internet. This research paper provides an in-depth analysis of the evolution, functioning, and impact of web search engines. Beginning with a historical overview, it traces the development of search engines from their inception to the present day. The paper explores the underlying technologies that power search engines, including crawling, indexing, and ranking algorithms. Furthermore, it examines the socio-economic implications of search engines, discussing their influence on information retrieval, online advertising, user behavior, and societal dynamics. Finally, the paper discusses current trends and future prospects in the field of web search engines.

Subject and Object of Forensic Electrical Engineering in Proceedings Electricity Theft

The purpose of this article is to summarize the results of electrical engineering expert research (in particular, performed at National Scientific Center «Hon. Prof. M. S. Bokarius Forensic Science Institute» of the Ministry of Justice of Ukraine) and a complex of general scientific and special methods (in particular, formal-logical, comparison, analysis and synthesis) to determine the place of examination on the facts of theft of electricity in the forensic electrical examination, to formulate the concept of the subject and object of such examination, to compile a list of its types .Prospects for the development of forensic electrotechnical expertise are outlined. The results of forensic electrotechnical researches in proceedings on the theft of electricity are summarized. Continuity of the general tasks of the forensic electrotechnical examination has been proven by these studies. On the basis of the considered separate trends of species genesis in forensic examination, an opinion is expressed about the further development of forensic electrical engineering. The structure of areas of forensic research on unaccounted electricity use was considered and their place in the system of forensic electrical technical examinations was determined. The principles of formation of typical lists of questions in forensic electrotechnical examination on the facts of electricity in accordance with the method of committing a criminal offense are laid down. According to provisions of the general theory of forensic examinations, the subject and object of the forensic electrical engineering on the facts of electricity theft are defined. Typical questions to forensic expert in proceedings about electricity theft due to the influence of electromagnetic radiation on the metering device are formulated. On the example of this list, the principles of forming typical lists of questions for other areas of re-search into the facts of electricity theft, depending on the method of committing the criminal offense, are considered.

A Comprehensive Review on an Advanced Machine Learning Approach for Enhancing Phishing Website Detection

Abstract: Phishing attacks continue to pose a significant threat to online security, exploiting user trust to steal sensitive information. This paper presents a comprehensive review of advanced machine learning techniques for enhancing phishing website detection. We analyze recent developments in feature engineering, focusing on content-based, URL-based, and networkbased attributes. Various machine learning algorithms, including supervised and unsupervised learning, are examined, highlighting their strengths and limitations in this domain. Furthermore, we investigate the potential of ensemble methods and deep learning models to improve detection accuracy. Additionally, we address challenges such as concept drift and adversarial attacks, discussing potential mitigation strategies. Finally, we outline future research directions, emphasizing the need for adaptable and real-time detection systems to counter evolving phishing tactics. This review serves as a valuable resource for researchers and practitioners seeking to develop more robust and effective phishing website detection solutions.