Innovative Reviews in Engineering and Science
Aim: Innovative Reviews in Engineering and Science, ISSN - 3048-8745 is a premier open-access journal published by the Society for Communication and Computer Technologies (SCCTS). The journal aims to provide a comprehensive platform for disseminating high-quality review articles that synthesize current knowledge, identify trends, and propose future directions in the vast fields of engineering and science. Our mission is to bridge the gap between cutting-edge research and practical applications, fostering a deeper understanding and facilitating advancements across diverse scientific and engineering disciplines. Subject Covered: Innovative Reviews in Engineering and Science, published by the Society for Communication and Computer Technologies (SCCTS), focuses on publishing high-quality review articles that cover the following areas: Biomedical Engineering: Medical devices, biomechanics, biomaterials, signal processing, tissue engineering, regenerative medicine. Chemical Engineering: Reaction engineering, process systems, sustainable chemistry, nanotechnology in chemical processes. Civil and Environmental Engineering: Structural engineering, geotechnical engineering, water resources, sustainable construction. Electrical and Electronics Engineering: Power systems, renewable energy, signal processing, telecommunications, microelectronics, control systems. Mechanical and Aerospace Engineering: Fluid mechanics, heat transfer, advanced manufacturing, aerospace propulsion, robotics, mechatronics. Materials Science: Composite materials, nanomaterials, materials characterization, functional materials. Computer Science and Engineering: Artificial intelligence, machine learning, data science, cybersecurity, software engineering. Interdisciplinary Science and Engineering: IoT, smart technologies, environmental science, renewable energy, computational methods. Quantitative Methods, Modeling, and Psychometrics in Engineering: Statistical modeling, measurement theory, psychometrics, testing and validation methodologies, reliability analysis, experimental design, computational statistics, data analytics, and quantitative evaluation methods applied to engineering systems, technology assessment, human–machine interaction, and interdisciplinary technological research. Key Features: High-Quality Reviews: Comprehensive and critical analyses in various fields. Open Access: Freely accessible to a global audience. Peer-Reviewed: Maintains rigorous standards for quality and integrity. Interdisciplinary Approach: Encourages research that bridges traditional boundaries. IRES aims to provide significant insights, identify trends, and propose future research directions in engineering and science. Frequency of publication - Bi Annual - It has Two issue per year Language - English Subject - Engineering Year of Starting - 2024 ISSN - 3048-8745 format of publication - Online Only
Society for Communication and Computer Technologies
Engineering Design Principles of Biomass-Derived Porous Carbon for Adsorption–Antibacterial Synergy
Porous carbon obtained by biomass has gained great interest as an eco-friendly highly versatile material due to its renewable source, controllable pore structure, and modifiable surface chemistry. Although BDPC has found extensive application in the adsorption-based removal of organic and inorganic impurities, recent reports suggest that rational structural and chemical engineering can be used to confer intrinsic antibacterial activity to BDPC, thus giving rise to a synergistic adsorption -antibacterial platform. This paper offers an overall engineering design strategy of BDPC that incorporates the biomass precursor choice, regulated carbonization, and activation, optimization of hierarchical pore architecture, and heteroatom-mediated surface functionalization concurrently to amplify the contaminants adsorption and bacterial inactivation. The effect of the micro mesoporous structures on adsorption capacity and mass transfer and how surface defects and heteroatom doping may promote the bacterial membrane disruption and oxidative stress are systemically discussed. Key mechanistic pathways that control the adsorption kinetics, electrical interactions, reactive oxygen species formation, and contact-centred bacterial inactivation are discussed critically to explain the root causes of multifunctional performance. Moreover, uniform measures of adsorption efficiency, antibacterial performance, reusability, and structural stability are defined so that meaningful comparison of their performance can be made. Another issue that is approached practically is the challenge of scalability, environmental safety and regeneration strategies. This work has given concrete rules of designing high-performance BDPC materials with the capability of eliminating chemical and biological isobutyls at the same time by integrating relationship of structure, property, and functional aspects. The suggested architecture contributes to the development of the porous carbon systems based on a circular economy and next-generation water purification, environmental cleanup, and anti-bacterial uses.
Biomass-derived porous carbon, adsorption, antibacterial materials, pore engineering, heteroatom doping, sustainable materials
Explainable Artificial Intelligence (XAI): State-of-the-Art, Challenges, and Research Trends
Since the use of artificial intelligence (AI) is becoming more common across high-stakes areas, including healthcare diagnostics, financial decision-making, autonomous vehicles, and legal analytics, the need to increase transparency, interpretability, and accountability in AI decision-making has become critical. Due to the opaqueness of numerous effective machine learning algorithms commonly termed as black boxes, issues related to fairness, trust, bias, and regulatory conformity have increased. Explainable Artificial Intelligence (XAI) has become a major research area aiming at an attempt to interpret the predictions and routes of AI models and do not degrade interpretable performance. The first section of this paper provides a systematic and end-to-end review of the state of the art of XAI, subdividing the existing methods into post-hoc explanation models (e.g. LIME or SHAP), models whose interpretation is intrinsic (e.g. decision trees or rule-based systems), and those with explainability incorporated into the architecture of deep networks (hybrid methods). All of the essential issues relating to XAI are discussed in-depth and these include the model fidelity and interpretability trade-off, the subjectivity of explanations based on human interaction, the absence of evaluative metrics, and computational complexity involved in providing explanations. Moreover, this paper visits new directions, like causal explanations, counterfactual reasoning, a combination with federated learning, and consistency of XAI techniques with ethical AI theories and governance frameworks, such as GDPR and HIPAA. It relies on a systematic review methodology to review pertinent literature in large databases between 2017 and 2025, taking note of some comparative strengths, application areas, and usability issues regarding XAI techniques. The conclusion of the study determines the main gaps in research and the following directions such as creating benchmark datasets, explainability in reinforcement learning, domain-specific evaluation frameworks could be developed. The given paper may be used as an initial source of information by researchers, developers, and policymakers trying to develop AI systems that possess not only accuracy but also interpretablity, alignment with human values and fairness.
Explainable AI, Interpretable Models, Black-box Models, Post-hoc Explanation, Trustworthy AI, Causal Inference, Human-Centric AI, Model Transparency
Explainable Artificial Intelligence (XAI) in Healthcare: A Systematic Review of Algorithms, Interpretability Techniques, and Clinical Integration Strategies
The fact that Artificial Intelligence (AI) is increasingly finding its ways into healthcare has greatly contributed to the diagnostic, prognostic, and forecasting propositions as well as clinical decision-making. Nonetheless, black box in deep learning results and deep learning algorithms in general pose significant challenges to both clinical acceptability as well as regulatory acceptance and patient confidence. Explainable Artificial intelligence (XAI) has come to curb such shortcomings by envisioning interpretability and humanistic comprehension of model decisions. This systematic review intends to relatively or comprehensively examine XAI in healthcare, and its analysis focuses on two dimensions: types of algorithms and interpretability methods, as well as strategies of clinical integration. A total of 112 articles were reviewed consisting of peer-reviewed articles published since 2018 and ending by 2025 which continued to be peer-reviewed till 2025 and then considered in the following databases; PubMed, Scopus, IEEE Xplore, and Web of Science. Papers were grouped by the domain of application (radiology, pathology, genomics, etc.), the type of AI model (decision trees, deep neural networks, etc.), and explanation technique (SHAP, LIME, attentions, etc.). The results indicate that SHAP and attention-based models are common and widely applicable to their compromise between fidelity and usability. Among the key challenges have been mentioned such as accuracy interpretability tradeoff, data bias, absence of standardized evaluation metrics and an insufficient clinical workflow. The conclusion to the review presents a proposed unfolding maturity model of using human-in-the-loop XAI and future research recommendations to include the presence of domain-specific interpretability benchmarks and the regulatory-compliant XAI systems. The presented work will serve as an apt guide to the development of trusted and transparent AI in healthcare.
Explainable Artificial Intelligence (XAI); Clinical Decision Support Systems (CDSS); Interpretability Techniques; Healthcare AI; SHAP; LIME; Attention Mechanisms; Deep Learning; Medical Imaging; Human-in-the-Loop AI
Bioengineered Scaffolds and Smart Biomaterials for Tissue Regeneration: Trends and Future Directions
Regeneration of tissues is as well a revolutionary front in regenerative medicines, and the development in bioengineered scaffold and intelligent biomaterials that replicate the intricate architectural, biochemical, and mechanical properties of the natural extracellular neighbor (ECM) have contributed to this. Such scaffolds serve both supporting structures as well as cell behavior regulation, tissue formation, and controlled release of bioactive molecules. The past few years have experienced great advancement in biomimetic scaffold construction, which poses high precision levels to replicate the microenvironment in a given tissue. Parallel to this, the introduction of smart biomaterials, whose properties are dynamic and responsive to a physiological cue, e.g. pH, temperature, enzymatic activity or mechanistic load gave rise to new opportunities in real-time responsiveness and adaptive wound healing. Other strategies that have improved scaffold design include 3D bioprinting, electrospinning, and self-assembling peptide systems which allow perfecting of porosity, architecture, and mechanical characteristics of the scaffold to constitute a variety of tissue such as bone, cartilage, skin, neural, and cardiac tissues. Nanotechnology has also allowed incorporation of nanoscale signals and functions into the scaffolds thus promoting improved interactions between cells and matrix and therapeutic delivery. Whereas spectacular laboratory and preclinical success have been achieved, clinical translation of these technologies has numerous challenges such as immune compatibility, vascularization, mechanical mismatch, biodegradation control, and scalability. The regulatory environment of scaffold-based implants is still convoluted and requires a unified assessment criteria of long term efficacy and safety. In this review, the recent advances in fabrication methods of scaffold materials and the functionalization methods of biomaterials have been synthesized and their critical analysis is discussed in terms of their therapeutic potential related to different tissue systems and the interdisciplinary frontier in terms of artificial intelligence, bioelectronics, and intelligent monitoring systems. In addition, it indicates major research lacunae and suggests future directions with the intention to transcend the translational pitfalls and achieve patient-specific and clinically viable solutions to regenerate tissues. Given this thorough evaluation, the paper will foreseeably lead to orienting researchers, biomedical engineers and clinicians in the rational design and use of next-generation regenerative therapies through sophisticated scaffolding systems and smart biomaterials.
Bioengineered scaffolds, smart biomaterials, tissue engineering, regenerative medicine, stimuli-responsive materials, 3D bioprinting, extracellular matrix, nanomaterials, clinical translation.
A Holistic Framework for IoT-Driven Smart Agriculture: Intelligent Sensing, AI-Based Analytics, and Environmental Sustainability
The recent need to achieve high agricultural production, internalization of resources and sustainability on the global scale has triggered the adoption of new digital technologies on contemporary farming. A holistic framework of the use of IoT to realize smart agriculture is unveiled in this paper with a focus on synergy between intelligent sensing technologies, AI-based analytics and sustainability objectives. The proposed architecture combines a wide variety of IoT sensors to observe real-time soil parameters, environmental conditions, and crop health with no issues handing them over to the cloud-edge infrastructure and providing low latency and energy-efficient data operations. Machine learning algorithms and artificial intelligence are used to derive meaningful information that can be used to carry out precision irrigation, forecast pests and diseases, and allocate resources in the best possible ways. The framework also assesses other communication protocols, which can be deployed reasonably on farms, including LoRa, ZigBee, and NB-IoT, on the reliability and scalability to heterogeneous farm conditions. In order to support the effectiveness and viability of the proposed implementation, a case study deployment on a test bed farm is discussed in the accuracy of data collected, amount of energy used, and sustainability parameters, which include how much water is saved and carbon emission reducing. The findings indicate an effective increase in the rates of efficiency of operations, accuracy of decision-making and optimization of resources. In addition, this research paper outlines the areas of crucial difficulty in system interoperability, data privacy, and rural connectivity, and provides the potential future research orientations such as blockchain-based system security and agri-intelligence through 6G. Filling the gap in the technological and the ecological level, this work further helps to develop the concept of sustainable smart farming ecosystems and provides a scalable plan on how to turn the existing agriculture into a resilient and data-driven paradigm.
Smart Agriculture, Internet of Things (IoT), Precision Farming, Artificial Intelligence (AI), Environmental Sustainability, Wireless Sensor Networks (WSNs), Cloud-Edge Computing, Sustainable Agriculture, Machine Learning, Real-Time Crop Monitoring
Advances in Functional Nanomaterials for Energy Storage and Conversion: A Comprehensive Review of Mechanisms, Materials, and Applications
Moving towards durable and efficient energy regimes requires new materials that will offer high performance energy storage and conversion. The review highlights the latest developments in functional nanomaterials and elaborates on their structural composition, synthesis methodologies as well as their potential applications in the area of batteries, supercapacitors, fuel cells and photocatalytic/electrocatalytic systems. The key task is to investigate the role of nanomaterials (i.e. metal oxides, carbon-based materials (e.g. graphene, CNTs), metalorganic frameworks (MOFs), perovskites, and transition metal dichalcogenides (TMDs)) in the improvement of the device performance due to its morphology engineering, quantum confinement effects, and interfacial design. The approaches to the synthesis (e.g., sol-gel, hydrothermal, CVD, electrospinning) are evaluated comparatively to note the possibilities of scaling it and its cost and environmental impact. Critical discussion on key performance indices such as energy density, power density, cyclic stability and charge transport dynamics are discussed. Limits to modern technologies which are structural degradation, poor cycle life, and interfacial charge recombination are also identified in the review and addressed by heterostructure engineering and hybrid nanocomposites. Combining the knowledge of the recent experimental and theoretical works aimed at smart hybrid nanostructures and green synthesis, the article proposes the future perspectives of green synthesis, smart hybrid systems, and materials discovery with the guidance of AI. This review was created with the intention of forming the basis on which other researchers and engineers work on new generations of multifunctional nanom.
Functional nanomaterials, energy storage, energy conversion, batteries, supercapacitors, electrocatalysts, photocatalysis, MOFs, perovskites, nanotechnology
Recent Advances in Wearable Biomedical Sensors: Materials, Signal Processing, and Healthcare Applications
The use of biomedical wearable sensors has become a disruptive technology that has found application in the healthcare sector that allows continuous real-time observation of physiological and biochemical responses in a non-invasive and user-friendly manner. The paper carries out a critical review of the recent developments of the area and examines it under the major axes: new materials for the development of new sensors, new signal processing methods, and practical healthcare applications. Due to a rapid advancement in materials science, there is the emergence of flexible, stretchable (flexible, stretchable), and biocompatible substrates of polydimethylsiloxane (PDMS), thermo plastic polyurethanes (TPUs), hydrogels, and nanomaterial-optimizing composites like graphene carbon nanotubes (CNTs) and MXenes. These materials provide better electrical aspects, mechanical compliance and conform-ability to skin, hence applicable on long term wearables. The latest developments in the signal processing domain are adaptive filtering, a wavelet transformation, deep learning-based models like convolutional neural networks (CNN) and long short-term memory (LSTM) networks, which allow noise to be reduced, feature extracted, and diseases to be classified in real-time sufficiently well. Additionally, wearable devices were being supported by privacy-preserving analytics through the dissolving of the edge computing and federated learning. Other various healthcare applications covered in the review are continuous ECG monitoring, glucose sensing, stress/ fatigue monitoring by EEG, multimodal system to manage and rehabilitate patients with chronic conditions. The trade-offs involved in terms of accuracy, power efficiency, cost of material and computational complexity are shown in comparative analyses. These advances aside, limitations are presented by long-term biocompatibility, energy independence and data security and clinical verification. Such future directions of smart healthcare systems identified within this paper are the development of biodegradable and self-healing sensors, integrating with digital twins and IoT ecosystems and using 6G-enabled communication to share data in real-time. Through the integration of recent literature and technological trends, the paper intends to become a foundational source of information regarding researchers, engineers, or medical practitioners dealing with the design and implementation of the next-generation wearable biomedical sensing systems.
Wearable Biomedical Sensors, Flexible Electronics, Biocompatible Materials, Signal Processing, Edge AI, Chronic Disease Monitoring, IoT Healthcare, Real-Time Analytics, Biosignal Acquisition, Personalized Medicine
Multifunctional Electronics Enabled by 2D Materials: From Scalable Synthesis to Device-Level Characterization and Challenges
Two-dimensional (2D) materials like graphene, transition metal dichalcogenides (TMDs), hexagonal boron nitride (h-BN), and MXenes have gained attention as promising materials to develop multifunctional electronics because of their outstanding electrical, optical, and thermal, and mechanical properties. They have high surface-to-volume ratio and atomically thin structure with tunable bandgaps which make them ideal candidates to use in flexible, wearable, transparent, and high-performance electronic systems. This paper gives a detailed overview of current knowledge of scalable synthesis approaches to graphene, such as chemical vapor deposition, liquid-phase exfoliation and bottom-up approaches, as well as state-of-the-art characterization methods that are essential to the study of the structural relationship between property. Moreover, methods of incorporating 2D materials in different device structures including field-effect based transistors, photo-detection devices, memory units and neuromorphic model are also discussed critically. Important issues of uniformity control, contact resistance, interface stability and CMOS compatibility are identified and explained. Lastly, we conclude with future areas of research, such as the design of materials with the assistance of artificial intelligence, large-area production, and the engineering of 2D heterostructures, which will be necessary before 2D materials-based multifunctional electronics can be achieved on a large scale.
2D materials, multifunctional electronics, scalable synthesis, device-level characterization, graphene, TMDs, flexible electronics, integration challenges
AI-Enabled Battery Management Systems for Electric Vehicles: Recent Trends in Control, Safety, and Energy Efficiency
Increasing electrification and the swift growth of electric vehicles (EVs) have escalated the pressure on the development of sophisticated Battery Management Systems (BMS) that could bring superior performance and safety of the lithium batteries in highly dynamic operation conditions. This paper is a detailed survey of the latest development of Artificial Intelligence (AI)-enabled BMS architectures with focus on state estimation enhancement, fault detection, thermal control, as well as energy efficiency. In this particular context, it examines how artificial neural networks (ANNs), support vector machines (SVMs), deep learning (DL), and reinforcement learning (RL) has been applied to predict state-of-charge (SoC), state-of-health (SoH), and battery degradation behavior. The review is synthesis of the results of more than 40 peer-reviewed publications, which compare the AI-based solutions with the traditional model-driven estimating approaches. The findings indicate that the prediction chances are drastically enhanced (±1.5% SoC), faults are detected almost in real-time (>95% prediction accuracy) and the energy consumption is kept at an optimized level (up to 12% energy savings). Another challenge of implementation discussed in the paper is computational complexity, real-time constraints as well as availability of data. Summing up, AI-based BMS models can serve as a disruptive course and empower smart, forecasting, and energy-conscious battery management in EVs. Hybridization of data-centric learning models and embedded control platforms promises to release the next era of secure, efficient, and driverless electric mobility.
Battery Management System (BMS), Electric Vehicles, Artificial Intelligence, State of Charge (SoC), Fault Diagnosis, Energy Efficiency, Thermal Management, Neural Networks, Deep Learning
Advances in Nanomaterials for Catalysis: Design Strategies, Reaction Mechanisms, and Emerging Industrial Applications
Nanomaterials have transformed the way catalysis can be done giving an exceptional property to control over such catalytic activity, selectivity and also stability thanks to their extraordinary physicochemical nanoscale properties. This is a general overview of all of the recent progress in the design approaches of nanomaterials with specific focus to catalytic application through approaches of size, shape, composition and surface functionalization. We discussed and investigated essential reaction dynamics that went through the bubble of catalyst performance, a dynamics of active sites, electron and adsorption dynamics. Moreover, the article has discussed some of the new industrial uses of nanocatalysts in a broad range of industries like energy conversion, environmental cure, and production of chemical products. Although scale up has been achieved, other challenges that exist are associated with how to scale up the synthesis modes, improve the durability of catalysts, and how to integrate nanomaterials with the ongoing industrial processes. Last but not least, we mentioned about future outlooks which has potential of giving sustainable and efficient catalytic technologies by advance nanomaterial engineering.
Nanomaterials, Catalysis, Catalyst Design, Reaction Mechanisms, Industrial Applications, Nanocatalysts, Surface Functionalization, Energy Conversion, Environmental Catalysis, Chemical Synthesis
Green Construction Technologies: A Comprehensive Review of Sustainable Building Materials, Energy-Efficient Design Strategies, and Lifecycle Assessment Frameworks
Green construction technologies have turned out to be a strategic reaction to the global call of low-emission and green infrastructure. This review attempt will give a general overview of the green building concepts that focus on three dimensions that are matters of concern: the sustainable material used in construction, energy-efficient design process, and lifecycle assessment (LCA) approaches. The main task is to digest the existing improvements and discover new possibilities of sustainable building. Due to the direction of the study and the description above, a thematic review methodology is adopted in the definition and screening of peer-reviewed literature, industrial reports, and international standards on low-carbon materials including geopolymer concrete (up to 70% of embodied carbon reduction), recycled aggregates (30-40% resource saving), bamboo (tensile strength equal to mild steel), and phase-change materials (3-5 induction temperature flux capacity). Passive cooling, daylighting (creating natural lighting up to 50 percent more), thermal insulation (preventing energy loss by 2535 percent), and intelligent HVAC systems (lowering operational energy by 2030 percent) count among the design methods that have been critically re-evaluated. Further, the review assesses LCA tools including SimaPro and OpenLCA and discusses their use in measuring embodied energy, carbon footprint and a wider scope of environmental impact within a building life course. The results demonstrate that, although the possibility of green materials and energy-efficient designs is growing, the combination problems, data standardization and economic trade-offs problems are still preventing a full-scale implementation. Lifecycle assessment, albeit promising, needs wider alignment of interested parties and formulation of regionframe works to meet variability in environmental information. In this review, it is concluded that the argument about the multidisciplinary approach through an integration of material innovation, intelligent energy systems and a robust LCA modeling are critical towards the mainstreaming of green construction and realization of measurable outputs of sustainability. The paper provides practical guidance on how engineers, architects and policy makers can proceed in having their built environment work with climate objectives and the regulatory system.
Green Construction, Sustainable Materials, Energy-Efficient Design, Lifecycle Assessment, Passive Cooling, Smart Buildings, Embodied Energy, Eco-Friendly Architecture, Net-Zero Buildings
Soft Robotics: Materials, Actuation Mechanisms, and Emerging Biomedical Applications
Soft robotics has come up as a disruptive technology that is redefining the functionality of robotic systems through the confluence of compliant materials and nature-based actuation methods. Compared to the conventional rigid-bodied robots, soft robots possess superior adaptability, flexibility, and are safe to interact with the non-linear environment that benefits them being utilized in the biomedical field, particularly. Over the past years, great advancement has been made with regard to soft robot construction to aid in the tasks involving delicate manipulation, including endoscopic navigation, targeted drug delivery, tissue engineering and minimally invasive surgical procedures. The present paper features an extended exploration of the multidisciplinary science of soft robotics through the lenses of the three major domains; that of materials, actuation and biomedical exploitation. We discuss different soft materials: silicone elastomers, hydrogels, shape-memory polymers and liquid crystal elastomers, with some emphasis on their mechanical properties, biocompatibility, and responsiveness mechanically to external stimuli, such as temperature, pH, light, and electric fields. Prominent actuation methods, such as pneumatic, dielectric elastomer, shape-memory alloy and magneto/electroactive polymers are also categorized in the paper and their operating principles, performance parameters and use in physiological situation analysed. Special weight is given to the assimilation of such technologies into biomedical tools like soft endoscopes, artificial muscles, implantable drug-release systems, and wearable rehabilitation exosuits. We can evaluate the efficiency of the soft robots to improve patient outcomes, minimize surgical trauma and support personalized therapeutic roles through experimental analysis and synthesizing the literature. Along with these developments, difficulties continue to be faced relating to long-term material robustness, energy consumption, scaling to smaller sizes, and concurrent sensing-feedback in real time. We single out the new trends of multifunctional materials, hybrid actuation, and control systems based on artificial intelligence which will remove these shortcomings. The study ends with an avenue of future research that may expand scalable intelligent and biocompatible soft robotic platforms thus initiating the next generation of robots designed specifically toward real world complex environments, as it may relate to biomedical machines.
Soft robotics, biocompatible materials, dielectric elastomers, hydrogel actuators, biomedical devices, artificial muscles, minimally invasive surgery, stimuli-responsive polymers, soft sensors, wearable robotics.
Photonic Integrated Circuits in Next-Generation Optical Communication Systems: A Comprehensive Review of Design, Fabrication, and Emerging Applications
Photonic integrated circuits (PICs) are transforming the next-generation optical communications systems due to their ability to provide ultra-high data rates, compact systems, and extremely low power consumption. PICs can solve this problem because they will support the ever-increasing amount of data traffic caused by cloud computing, 5G/6G networks, and AI workloads in a simple, clean, and energy-efficient way. In this review, the author provides an in-depth review of the PIC landscape in terms of main design methodologies, mature and advanced fabrication processes as well as diverse integration strategies on the main material platforms, silicon photonics, III-V semiconductors, and lithium niobate among others. We discuss critical state-of-the-art components such as the modulators, photodetectors, multiplexers and the coherent transceivers, their applications in data center interconnects, long-haul transmission and reconfigurable optical networks. The next wave in quantum technologiesThe emergence of quantum technologies, quantum LiDAR, quantum biomedical diagnostics, quantum neural networks and their applications are also discussed. Other important aspects of key design and manufacturing issues, including the relationship of thermal stability, coupling losses, yield scalability and heterogeneous integration, are also said in details. The paper ends with future analysis of research on the fields of reconfigurable architecture, AI-assisted photonic design, and monolithic photonic-electronic co-integration, in which PICs play a pivotal role as a foundation piece of technology to the high-performance, broadband communication and beyond.
Photonic Integrated Circuits (PICs); Optical Communication Systems; Silicon Photonics; Coherent Transceivers; Optical Interconnects; Hybrid Integration; Electro-Optic Modulators; Photodetectors; Quantum Photonics; LiDAR; Biomedical Sensing; Photonic Neural Networks; High-Speed Data Transmission; Heterogeneous Integration; Energy-Efficient Photonics
Recent Advances in Soft Robotics: Smart Materials, Novel Actuation Technologies, and Emerging Applications in Biomedical and Industrial Systems
The new challenge of soft robotics is changing the arena of adaptive and smart systems with compliant materials by focusing on nonconventional actuation approaches to achieve their functioning characteristics to biological systems. Herein, the most recent advances in soft robotics are described focusing on three major areas: (i) incorporation of new smart materials-like hydrogel-based tissue-mimicking compliances, liquid crystal elastomers-based anisotropic responsiveness, and shape-memory polymers-based programmable actuation; (ii) novel types of actuation like pneumatic inflation, electroactive polymers-based electrically driven deformation, and magnetic field-responsive actuation; and (iii) real-life applications in biomedical engineering (examples including soft prosthet The review is a summary of the existing methodologies, experimental standards, and design code, with their mechanical efficiency, biocompatibility, and energy requirements being assessed. Such critical challenges as reaching the ideal of real-time closed-loop control, enhancing actuator robustness, the miniaturization of devices and effective electrical energy transduypion are examined. The paper ends with future research directions such as combinations of soft robotics with artificial intelligence, embedded sensing and multifunctional materials in order to facilitate intelligence based and autonomous systems of soft robots. All these are to applicable to scholars who are trying to develop and implement the next generation robotic systems both in clinical and in industrial sectors.
Soft Robotics, Smart Materials, Shape-Memory Polymers, Electroactive Polymers, Pneumatic Actuation, Liquid Crystal Elastomers, Biomedical Devices, Soft Grippers, Embedded Sensing, Artificial Intelligence in Robotics, Compliant Actuation, Human–Robot Interaction, Wireless Soft Actuation.
2D Materials for Next-Generation Electronics and Optoelectronics: Trends and Challenges
Flat, two-dimensional (2D) materials have also become a breakthrough type of nanomaterials, which exhibit outstanding electrical, optical, thermal, and mechanical performances because of the properties inherent in their ultrathin structuring (of atomic dimensions) and their well-engineered properties. Since graphene was isolated, there has been a broad number of 2D materials eagerly pursued as possible next-generation materials in electronics and optoelectronics, including, but not limited to the transition metal dichalcogenides (TMDs), black phosphorous (BP), hexagonal boron nitride (h-BN), and the MXenes. This review concisely summarizes the current development in Design, synthesis, characterization and use of 2D materials refractory to work into their incorporation as FETs, photodetectors, conformable electronic circuits, quantum devices and energy-harvesting platforms. Each of the synthesis methods that have been proposed, such as mechanical exfoliation, chemical vapor deposition (CVD), molecular beam epitaxy (MBE), and liquid-phase exfoliation, are critically assessed and a trade-off in material quality, scalability, or feasibility of integration is highlighted. There is particular focus on new developments in van der Waals Heterostructures, bandgap engineering tactics and strain-driven modulation, which allow previously unattainable manipulation of electronic and optoelectronic characteristics. Although 2D materials have shown excellent potential in lab-scale devices, other drawbacks in terms of the ambient instability (particularly in BP), interface traps, unfavorable contact resistance, and limited ability to grow large AREA uniformly, have prevented a successful application in practice. The limitations are discussed at length in this review, as well as the newer developments to address them: passivation layers, low-temperature processing and AI-aided material discovery. Added to this, we provide the tendencies in device performance characteristics, including its carrier mobility, responsivity, switching speed, and power efficiency, and compare 2D materials with conventional semiconductors. This article will give a sense of integrated research efforts among researchers and engineers who take a multidisciplinary approach toward the development of materials science, nanoelectronics, and photonics with the view of creating a coherent outline of the road toward practical, high-performance and scalable systems that rely on 2D materials.
2D materials; Transition Metal Dichalcogenides (TMDs); Graphene; Black Phosphorus; Hexagonal Boron Nitride (h-BN); MXenes; Field-Effect Transistors (FETs); Optoelectronics; Photodetectors; Flexible electronics; Van der Waals heterostructures; Chemical Vapor Deposition (CVD); Bandgap engineering; Quantum devices; Synthesis techniques; Material integration; Electronic mobility; Nanomaterials.
The recent trend of wearable biomedical sensors poses a very significant transformation to the current healthcare system; they could monitor the physiological parameters of people in real-time, continuously, providing an early warning of diseases and the ability to treat patients remotely. Based on it the recent developments in the field are thoroughly discussed keeping in view three important areas such as new materials, new signal processing techniques and various healthcare applications. The growth of clinically useful flexible, stretchable and non-toxic materials has contributed greatly to the convenience, life span and skin friendliness of sensors. At the same time, advanced signal acquisition and artificial intelligence processing has enhanced the quality and trustworthiness of biosignal analysis even on the low-resource wearable systems. The paper also examines an extensive variety of clinical, wellness applications, such as chronic disease, rehabilitation, neurological assessment, and pandemic-driven telemedicine. Such challenges as power consumption, data security, interoperability, and long-term biocompatibility are critically discussed. Lastly, concluding remarks on the future research directions will be presented, where the future of intelligent wearable healthcare systems will be determined by developing new technologies such as 2D materials, edge-AI, and next-generation wireless networks.
Wearable Biomedical Sensors, Flexible Electronics, Biocompatible Materials, Biosignal Processing, Machine Learning in Healthcare, Edge AI, Continuous Health Monitoring, Remote Patient Monitoring, Physiological Signal Analysis, Healthcare Applications
Next-Generation Biomedical Implants: A Comprehensive Review of Smart Biomaterials and 4D Bioprinting Technologies for Personalized and Responsive Medicine
Smart biomaterials and 4D bioprinting bring the paradigm shift in the field of biomedical implants. Such innovations allow creating the next generation of implants that have an ability to react to physiological factors dynamically and thus make the therapeutic process more efficient and more individualized. This paper seeks to examine in detail the role of the modern development related to the use of smart biomaterialsssuch as shape-memory polymers, stimuli-responsive hydrogels, and multifunctional nanocompositesin implantable medical devices. Here, we also discuss the concepts and advancements of 4D bio-printing, with regard to their intelligent-bios me-inks, programmable structures and time-varying morphological changes. In our methodology, we conducted a proper literature review regarding peer reviewing identified research in significant databases (e.g., Scopus, Web of Science) conducted during the past 10 years. We review and critically analyse the study on the fabrication process, responsiveness to materials, biocompatibility and clinical relevance. The review identifies three main clinical use-cases which are orthopedic scaffolds, cardiovascular stents, neural interfaces, and sensors and actuators in wound healing. Although spectacular advances have been witnessed, limitations to long term biocompatibility, mechanical stability, regulatory acceptability and scalability exist at a clinical translation level. The present review finalizes that the synthesis of smart biomaterials and 4D bioprinting has the tremendous potential of disruptive innovation in customized and responsive medicine. Further interdisciplinary studies, based on advances in biofabrication, modeling and harmonization of regulations, would be necessary to complete the gap between the development and use of biomedical products in the laboratory to biomedical practice.
Smart Biomaterials; 4D Bioprinting; Personalized Medicine; Biomedical Implants; Stimuli-Responsive Materials; Bio-Inks; Tissue Engineering; Regenerative Medicine.
Recent Developments in Wearable Biosensors for Real-Time Health Monitoring: A Comprehensive Review
Instantaneous health monitoring through wearable biosensors has become an enhancement platform in healthcare management that provides a non-invasive individual continuous health monitoring solution making it compatible with the transformation towards proactive healthcare. With the incorporation of stretchable substrates, enhanced nanomaterials, miniaturized electronics, and wireless connectivity standards, the precise smart systems can measure an array of physiological and biochemicalrelated parameters such as heart rate, oxygen saturation, glucose levels, hydration, temperature, and metabolic biomarkers in mediums such as sweat, saliva, interstitial, and interdigital skin allergies. Innovation has in the recent past been laying stress on enhancing sensitivity, stretch capacity and long-run stability of these sensors and maintaining comfort and sturdiness in the end user. At the same time, the approach to energy harvesting, including triboelectric, thermoelectric, piezoelectric generators, has solved the issue of power autonomy, allowing to use battery-free, long-lasting power. At the same time, more and more frequently we are also to see AI-derived data processing methods that would allow us to increase signal accuracy, give out predictive information, and ensure smooth integration with mobile health (mHealth) technologies and Internet of Medical Things (IoMT), frameworks. Such innovations have enhanced the usage of wearable biosensors in various settings, such as chronic disease management (e.g., diabetes, cardiovascular diseases), sports activities, and fitness tracking, postsurgical care, aging, and pandemic surveillance. Nevertheless, the popularity of these systems is also associated with the issues of biocompatibility, skin irritability, and sensor wear, data protection, ethical standards, and regulatory licensing. Besides, the problem of artifacts or motion, calibration drift, and interoperability with some other devices are obstacles to stable clinical quality work. The broad review of wearable biosensor research gives a detailed overview of the latest innovation in wearable biosensor technology classified by sensor types, materials, fabrication processes, signal transmission pathways, power solutions and data acquisition methods. It also addresses real-life deployment, restrictions, and what trends and technologies have been introduced into the field including digital twins, self-healing smart sensors, and edge AI for decentralized healthcare. This review attempts to support future research and development by systematizing the existing efforts and establishing the remaining gaps in the goal of developing wearable healthcare systems that are scalable,secure and smart
Wearable biosensors; real-time health monitoring; flexible electronics; nanomaterials; chronic disease management; physiological sensing;
Future of Tissue Engineering in Regenerative Medicine: Challenges and Opportunities
However, these innovations, which include work in the field of tissue engineering, opens unprecedented possibilities for healing and regeneration. In the journey into the intricate world of cellular scaffolds, biomaterials and regenerative therapies, there is a landscape promising but fraught with difficulty. In this article, we explore the state of the art, persistent hurdles, and promising directions laying out the path into the future tissue engineering and its central place in the field of regenerative medicine. Tissue engineering doesn't stop with lab grown organs either; the horizons of the field continue to expand, with the potential for transformative solutions to a number of medical conditions through personalized cellular therapies. While we transit this dynamically expanding sphere, we explore some of the most recent advances, highlight the barriers experienced by researchers and practicing clinicians, and speculate how this will potentially change the trajectories of healthcare and patient outcomes. On this journey into the intriguing territory of tissue engineering, where science fiction hits reality, and where edges of what's doable in medicine keeps moving.
Tissue Engineering; Regenerative Medicine; Stem Cells; Biomaterials; Cellular Therapy
Smart Construction Materials for Sustainable and Resilient Infrastructure Innovations
We are in a precarious moment, at a turning point, for the construction industry: unprecedented challenges in sustainability and resilience. In fact, as global urbanization rapidly proceeds and climate change increases, creating innovative building materials and technologies has never been more important. A fast emerging category of smart construction materials stands as the keystone for sustainable and resilient infrastructure, delivering the solutions needed to mitigate environmental impact while enhancing the resilience and performance of built environments. In this article, cutting edge smart construction materials are explored as these cutting edge advancements are changing how the world views sustainable and resilient infrastructure. We’ll look at technologies ranging from self healing concrete to energy harvesting surfaces that are helping push the industry in a more sustainable direction. During this traverse through this exploration, it emerges that smart construction materials are not a passing fancy, but a fundamental progress of how we build out the world. They are the convergence of material science, environmental stewardship and technological innovation, and which will change what it means to build our cities and structures. Together, we dive into how these revolutionary materials can transform the built environment into a future that is shaped by 21st century challenges and sustainability.
Smart Materials; Sustainable Infrastructure; Resilient Construction; Green Building Materials; Energy-Efficient Design; Advanced Construction Technologies
Robotics and Mechatronics in Advanced Manufacturing
Rigorous advancements in robotics and mechatronics are driving a profound change to the manufacturing landscape. Intelligent automation systems are method of production reshaping the way we produce, enhance efficiency and open new possibilities as industries embrace the fourth industrial revolution. This detailed review examines conjoining robotics, mechatronics, and sophisticated manufacturing that is on the leading edge, highlighting coming up trends that would drastically change the sector. It’s an era of unprecedented productivity brought about by smart technologies, from collaborative robots working alongside humans to the use of AI for product quality control. In this post, we review how these technologies are being utilized in different industries, the hurdles that accompany utilizing them, and how they pave the way for the future of manufacturing. Let’s discover this exciting frontier between mechanical engineering and artificial intelligence, opening the greenway to the smarter, more adaptable, more energy efficient production environments.
Industrial Robotics; Mechatronic Systems; Automation Technology; Smart Manufacturing; Precision Robotics; Manufacturing Optimization
Fluid Mechanics for Aerospace Propulsion Systems in Recent Trends
Fluid mechanics is still a central theme of aerospace technology as industry strives to exceed the technology barriers. And the principles of fluid dynamics govern aerospace vehicles from aircraft engines to spacecraft thrusters. In this article, we explore the state of the art of fluid mechanics in the field of aerospace propulsion and showcase some of the most important recent developments in the field. When we start to explore aerospace fluid mechanics, we start to explore how researchers and engineers are utilizing advanced computational methods, novel materials and novel design approaches to make better, more powerful and less environmentally devastating propulsion systems. Fluid mechanics finds applications from hypersonic flight to electric propulsion for spacecraft, and the list is as vast and growing. Let’s embark together on this exploration of the hottest trends in the field of aerospace propulsion systems fluid mechanics technologies and concepts driving us towards the next wave in aviation and space exploration.
Fluid Dynamics; Aerospace Propulsion; Computational Fluid Dynamics (CFD); Jet Engine Technology; Propulsion Efficiency
Nanotechnology Recent Developments in Sustainable Chemical Processes
Nanotechnology represents a rapid advancement of scientific and industrial innovation covers of many disciplines. This integration of nanomaterials and nanotechnology has made a breakthrough in the field of chemical engineering and resulted in providing nanotechnology enabled processes. This article reviews the most recent developments in the employ of nanotechnology for more sustainable and efficient chemical processes focusing on significant progress and current and future directions. However, the synergy of nanotechnology and chemical engineering has great promise in applying novel solutions to address key energy, environmental remediation and resource use hurdles. The power of this technique lies in a process of manipulation of matter on a very small scale, enabling researchers and engineers to unlock new material properties and improve process efficiency in ways never previously possible. Nanomaterials are transforming how we do chemistry—focusing on advanced catalysts, smart sensors and other tasks involved in chemical reactions, separations, and analysis. In this article, we explore the opportunities for greener synthesis routes, more selective catalysis, improved separation techniques and innovative pollution control and environmental monitoring that nanotechnology will provide. We will also detail emerging applications of nanomaterials in energy storage, conversion and conservation. We will highlight how these advancements help to make chemical processes and industries more sustainable, throughout.
Nanomaterials; Green Chemistry; Sustainable Processes; Catalysis; Environmental Impact; Nanostructures
Thabo Sipho, Nomsa Lindiwe, Tsholofelo Ngidi
Optimizing Renewable Energy Integration for Power Grid Challenges to Navigating
With the global movement towards sustainable energy, the power generation has leap forward to renewable energy systems. Ped Cricket's focus is on countries across the globe striving to reduce their carbon emissions and combat climate change, and the integration of renewable energy sources into existing power grids has never been more important. While essential for a greener future this transition is a complex set of challenges that need innovative solutions and strategic planning. Originally, power grids were the backbone of our modern energy infrastructure, the foundation of which were designed for a more centralized, more predictable energy landscape. However, given the variable and distributed nature of renewable energy sources such as solar and wind power, these systems now need to change in order to operate. It requires a major transformation of how grid operations occur: from long-term stability planning and connection through to real time management. Integrating renewable energy, as we dive into the intricate art of optimizing renewable energy integration, you’ll learn about the buried challenges faced by grid operators and the coolest solutions invented to solve them. This article will give you a thorough background on the strategies that will define the future of our energy systems through advanced grid technologies and flexibility services, innovative planning models, to stakeholder cooperation. Welcome as we embark on an exploration of power sector evolution in an effort to build a stronger, more sustainable, reliable and efficient grid for the coming generations.
Renewable Energy; Power Grid Optimization; Energy Storage; Smart Grids; Grid Stability; Demand Response
Nanomaterials for Water Purification Towards Global Water Crisis Sustainable Solutions
Providing the world's increasingly growing population with clean, affordable water is an unprecedented challenge for the 21st century. In the face of climate change and failing water quality, nanotechnology has become the center piece in innovation in this global crisis. This article discusses the ways in which nanomaterials are leading the way in the revolution of the water purification techniques and are providing sustainable means to increase access to safe drinking water around the world. Water scarcity and pollution threaten human health, economic development and environmental sustainability. Traditional water treatment methods do not generally achieve effective removal of emerging pollutants and pathogen. Thus, the properties of nanomaterials at the molecular scale make it unique, and open new possibilities for development of more efficient, cost effective and environmentally friendly water purification. Nanotechnology is changing the way we clean and reuse water resources from nano adsorbents that remove toxic metals selectively and nanomembranes that filter out the slightest contaminants. In this article we will look at the advances in nanomaterials for water purification looking at how they work, what they are good for, and they could help enlighten us about the global water crisis. Through these innovations we’ll explore ways these are redefining the future of water management for anyone and everyone, not just industries and communities, but all across the globe.
Nanomaterials; Water Purification; Sustainable Solutions; Environmental Remediation; Filtration Technology
Machine Learning in Chemical Engineering for Future Trends and Recent Applications
Machine learning (ML) integration into chemical engineering has become the latest innovation and efficiency. It is transforming how chemical engineers conceive of, tackle and solve the most sophisticated problems, improve processes and take major decisions during manufacture. We’ll take a look at how this synergy is transforming the industry and driving leaps in innovation, as we explore current and forthcoming uses of machine learning in this arena. There is nothing new to the convergence of artificial intelligence and chemical engineering. But in the last few years, the resurgence of interest has resulted in tremendous breakthroughs as more and more data become available and as computational power gets cheaper. Machine learning is becoming an indispensable tool for the chemical engineer from process optimization to predictive maintenance. In this review we seek to provide a high level overview of the current status of machine learning in chemical engineering (wide application across multiple areas), its application in various domains, and its surging potential.
Machine Learning; Chemical Engineering; Process Optimization; Predictive Modeling; Data Analytics
Quantification of Carbon Nanotube Fiber reinforcement for Composites in Revolutionizing Aerospace
The advent of composite materials has brought a new generation in aerospace engineering, conferring in it unmatched strength, weight reduction and performance. In the face of efforts to improve aviation’s efficiency while increasing capability, composites play an increasingly important role in the design and construction of aircraft. In this comprehensive exploration of composite structures, the design principles, analysis techniques, and key applications that are transforming flight are covered. Composite materials have found a powerful position in the area of structural engineering as a result of the aerospace sector's relentless quest for innovation. Combined in the form of these engineered materials, these disparate components harness the synergistic properties that form a paradigm shift in how we design and fabricate airframes, propulsion systems and space craft. I find it quite interesting the journey from traditional metallic structures to becoming advanced composites describes a fascinating scientific progress and engineering ingenuity. In this in depth analysis, each will unravel the conceptuals underpinning composite design and manufacturing, and find out about new ways this is being brought to reality, and how these fabrics are responding across various aerospace industry applications. Commercial airliners to next generation spacecraft, composites are rewriting the rulebook in the world of flight.
Carbon Nanotubes; Fiber Reinforcement; Aerospace Composites; Material Strengthening; Nanomaterials
Leveraging Data Science for Predictive Maintenance in Industrial Settings
In recent years the industrial landscape has been dramatically changing due to technological advances and the increased importance on operational efficiency. In industries where essential machinery and equipment are very complex, integration of data science with maintaining practice has been quite transformative. This technological revolution is benefitting manufacturers plants, energy facilities, transportation networks among others. Keeping an eye on how equipment health and performance metrics are year to year evolving allows companies to make data driven decisions regarding when to do maintenance activities and how to do them. With that, the applications of data science in predictive maintenance become more and more obvious and it’s obvious that we are not talking about a fleeting trend here, but a completely new approach to industrial operations based on predictive maintenance. The ability to predict and prevent equipment failures has widespread impact on productivity, safety, profitability within various industries.
Data Science; Predictive Maintenance; Industrial Automation; Machine Learning; Operational Efficiency
Maximilian Mia, Alexander Emma, Paul Hannah
Comprehensive Review of Cybersecurity Challenges in the Age of IoT
The Internet of Things (IoT) has ushered in a new era of connected devices that is so rapid that traditional networks cannot keep up. But the potential for this connected landscape results in unprecedented cybersecurity risk and businesses and people alike must navigate it. It’s imperative that we leverage our understanding and solutions to these challenges to protect sensitive data and our critical infrastructure as a smart planet continues to become more and more digitized. In a comprehensive review, we explore the dynamics of the growing field of cybersecurity and IoT, while exploring its complex relationship; discussing the uniqueness of cybersecurity vulnerabilities and emerging threats, as well as the avenues of solution. Through examining the industry specific impacts, regulatory considerations, and best practices we intend to educate our readers as we give them the tools to armor their defenses in an IoT world.
Cybersecurity; Internet of Things (IoT); Network Security; Data Privacy; Vulnerability Management
Artificial Intelligence Techniques in Biomedical Signal Processing
It is a new health care innovation, the integration of artificial intelligence (AI) to biomedical signal processing. This non-traditional, rapidly evolving field infuses AI algorithms technology and advanced signal processing techniques to disclose the hidden meaningful insights from complex biological data. AI driven biomedical signal processing is revolutionizing patient care in all medical specialties from providing diagnostic accuracy to enabling personalized treatment strategies. Today, researchers and clinicians are pursuing the potential of AI as it is applied to healthcare reaching milestones in fetal monitoring, bone health assessment, cardiovascular diagnostics, and neurological evaluations. They not only gentrify medical procedures more effective and accurate; they even lay the path to cheaper, less expensive healthcare. In this comprehensive study, we will review developments in biomedical signal processing that make use of current state of the art in AI applications, identify emerging trends, and discuss future developments that will have a huge impact on the future of modern medicine. If you can see the limits and the capabilities of these technologies in a way that allows you to confidently prepare for a future where AI is a key member of the clinical tool kit then you have a chance of preparing for a future where AI is crucial to what makes it special.
Artificial Intelligence, Biomedical Signal Processing, Machine Learning, Medical Imaging, Healthcare Automation