Results in Engineering最新文献

{"title":"Quasi-static compressive mechanical behaviours of two-phase hybrid lattices based on asymmetric design and bionic strategy","authors":"Xinlong Guang ,&nbsp;Huilan Huang ,&nbsp;Quanping Fu ,&nbsp;Shen Xu ,&nbsp;Xiaolin Deng","doi":"10.1016/j.rineng.2025.107291","DOIUrl":"10.1016/j.rineng.2025.107291","url":null,"abstract":"<div><div>Lattice structures have attracted considerable attention in the fields of aerospace, construction, and marine engineering due to their unique properties and enhanced mechanical performance. Nonetheless, conventional single-configuration lattice structures are constrained by limitations in diversity, versatility, and adaptability across multiple scenarios. To mitigate these constraints, a two-phase hybrid lattice structure with modular assembly capability has been developed. This design allows for reconfiguration based on load conditions and functional requirements. We conduct experimental investigations to characterize the mechanical properties of three novel configurations: the asymmetric re-entrant lattice, the bionic lattice, and their hybrid structure. The results indicate that the hybrid lattice demonstrates improved specific energy absorption and exhibits more diversified and flexible properties compared to the conventional single lattice structure. The specific energy absorption and effective Young's modulus of the double asymmetric re-entrant lattice are improved by 32.8 % and 128.36 %, respectively, when compared to benchmark re-entrant lattice. This approach presents a viable solution for the diversification of engineering structures.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107291"},"PeriodicalIF":7.9,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid energy platforms: A review of perovskite solar cells coupled with graphene supercapacitors","authors":"Mzoun M. Almutairi ,&nbsp;Mariam H. Alalwan ,&nbsp;Hawraa K. Algharash ,&nbsp;Raghad A. Aldossary ,&nbsp;Nouf K. Al-Saleem ,&nbsp;Yahya A. Alzahrani ,&nbsp;Masfar Alkahtani","doi":"10.1016/j.rineng.2025.107200","DOIUrl":"10.1016/j.rineng.2025.107200","url":null,"abstract":"<div><div>The integration of photovoltaic and energy storage components has garnered significant scientific and technological interest, driven by the growing demand for green energy and the trend toward miniaturization and multi-functionalization in the electronics industry. This study explores the novel integration of perovskite solar cells (PSCs) with solid-state supercapacitors to create efficient power packs for solar energy harvesting and storage. The hybrid system achieves simultaneous photoelectric conversion and energy storage by combining PSCs with high-energy-density graphene-based supercapacitors using common carbon electrodes. This review provides a comprehensive analysis of the fundamental principles, recent advancements, and key challenges in developing these integrated systems. It critically evaluates material properties, device architectures, and performance metrics, highlighting the potential of such hybrid systems for sustainable energy solutions. Additionally, the study outlines future research directions aimed at improving efficiency, scalability, and practical applications of perovskite-supercapacitor power packs. This work contributes to the ongoing efforts to advance renewable energy technologies and meet the increasing demand for compact, multifunctional energy systems.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107200"},"PeriodicalIF":7.9,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication of microfluidic devices by 3D printing: technology, materials, applications and prospects","authors":"Jinhao Zheng ,&nbsp;Shaohua Ju ,&nbsp;Xian Zhou ,&nbsp;Shihong Tian","doi":"10.1016/j.rineng.2025.107270","DOIUrl":"10.1016/j.rineng.2025.107270","url":null,"abstract":"<div><div>Microfluidic devices have emerged as a cornerstone of chemical process intensification, owing to their exceptional mass and heat transfer efficiencies, precise fluid manipulation, and inherent safety. However, their traditional manufacturing technology is limited by high cost, long cycle and insufficient structural design freedom. Leveraging layer-by-layer additive manufacturing, 3D printing offers a revolutionary approach to fabricating microfluidic devices, characterized by sub-micron resolution, unparalleled design flexibility, and rapid prototyping capabilities. This paper systematically reviews the technical system of 3D printing microfluidic devices for the chemical industry. Starting from the forming mechanism and applicable scenarios of mainstream printing technologies (photocuring, melt extrusion, powder bed melting), the interface characteristics and chemical compatibility of photosensitive resin, thermoplastic wire, metal/ceramic powder and other materials are compared and analyzed. The innovative applications of 3D printed microreactors in chemical scenarios such as catalytic reaction, nanomaterial synthesis, continuous flow separation and multi-functional integration are mainly discussed. Finally, aiming at the key technical bottlenecks such as multi-material co-printing, surface roughness control and high-throughput production, the development direction of high-throughput design-manufacturing-testing platform driven by digital twin is proposed, which provides theoretical support for the industrial application of microfluidic devices and the low-carbon transformation of the chemical industry.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107270"},"PeriodicalIF":7.9,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clean energy demand in industry 4.0: Trends, challenges, and opportunities","authors":"Sololo Kebede Nemomsa,&nbsp;Naol Dessalegn Dejene,&nbsp;Dame Alemayehu Efa,&nbsp;Dinkisa Tamiru Negari,&nbsp;Dejene Alemayehu Ifa,&nbsp;Devarakonda Harish Kumar","doi":"10.1016/j.rineng.2025.107260","DOIUrl":"10.1016/j.rineng.2025.107260","url":null,"abstract":"<div><div>The combination of Industry 4.0 technologies with clean energy systems presents a strategy that offers a pathway towards high efficiency, resilient, and sustainable industrial operations. This review examined progress in six key enablers, namely the Internet of Things (IoT), Artificial Intelligence (AI), Cyber-Physical Systems (CPS), digital twins, blockchain, and additive manufacturing, focusing on energy optimization, renewable energy integration, and transparent, secure, and adaptive energy management. By carrying out a systematic literature review of peer-reviewed articles and conferences in primary databases, we identified trends, sectoral applications, and barriers to implementation. This analysis provides a foundation for advocacy of the Digital-Clean Synergy Framework (DCSF), a four-layer interoperable architecture comprising sensing, analytics, control, and governance to fully integrate digital and clean energy systems. The reviewed literature suggests that combining multiple enablers can reduce industrial energy consumption, increase renewable energy penetration by 8 - 52 % [<span><span>1</span></span>], decrease downtime, and enhance carbon accounting and traceability through blockchain. However, DCSF is only theoretical; it lacks large-scale empirical validation, agreed interoperability standards, appropriate cybersecurity practices, or hybrid workforce skills. Further research should include cross-sector pilot deployments, lifecycle assessment, and integration across diverse regulatory and infrastructure contexts to demonstrate scalability and economic viability. DCSF offers a pathway to bridge the policy-technology divide and could serve as a scalable model to accelerate industrial decarbonization in line with SDG 7, SDG 9, and SDG 13.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107260"},"PeriodicalIF":7.9,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward resource-intelligent greenhouses: A prospective vision for drylands","authors":"Amrit Kumar Thakur ,&nbsp;Aidan Ferguson ,&nbsp;Md Shamim Ahamed ,&nbsp;Zheng Miao ,&nbsp;Mahmoud E. Attia ,&nbsp;Tien-Chieh Hung ,&nbsp;Hasan Fath ,&nbsp;Abdelwahab S. Kassem ,&nbsp;Ahmed Torky Jailany ,&nbsp;Abdalla Zain Eldin","doi":"10.1016/j.rineng.2025.107035","DOIUrl":"10.1016/j.rineng.2025.107035","url":null,"abstract":"<div><div>Greenhouse agriculture offers a promising alternative to open-field cultivation in dryland regions, where extreme temperatures, drought, and poor soil quality restrict conventional food production. However, existing greenhouse systems, often designed for temperate climates, struggle to cope with the thermal and hydric stresses that characterize dryland environments, including arid, semi-arid, and Mediterranean zones. This prospective review presents a systems-level framework for climate-resilient greenhouse design, emphasizing the integration of structural optimization, passive and hybrid cooling strategies, advanced glazing materials, desalination-enabled water reuse, and aquaponics-based biological cycling. Key leverage points include orientation-driven thermal mitigation, membrane-based desalination powered by renewable energy, and decoupled aquaponics systems enabling a precise and climate-smart approach to environmental control. Emerging innovations in evaporative and desiccant hybrid cooling, spectral selective and radiative films, and nutrient-selective electrodialysis further enhance the potential of integrated solutions. The paper highlights how materials science, thermofluid dynamics, and engineering can be harmonized to improve crop productivity, resource efficiency, and climate adaptability in greenhouse production for dryland settings. Rather than viewing cooling, irrigation, and biological production as discrete challenges, the review advocates for interdependent subsystem designs that close thermal, hydric, and nutrient loops within a unified bioclimatic envelope. A circular conceptual framework illustrates these synergies and guides future greenhouse development in water and energy-stressed drylands. By reframing the greenhouse as a regenerative infrastructure, this study outlines a blueprint for an integrated food–water–energy nexus able to operate efficiently and sustainably in the world's most vulnerable agricultural zones.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107035"},"PeriodicalIF":7.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maximum power point tracking strategies for solar PV systems: A review of current methods and future innovations","authors":"Lyu Guanghua ,&nbsp;Arsalan Muhammad Soomar ,&nbsp;Syed Hadi Hussain Shah ,&nbsp;Shoaib Shaikh ,&nbsp;Piotr Musznicki","doi":"10.1016/j.rineng.2025.107227","DOIUrl":"10.1016/j.rineng.2025.107227","url":null,"abstract":"<div><div>Photovoltaic (PV) systems are critical for solar energy conversion but face performance degradation due to dynamic environmental conditions. Maximum power point tracking (MPPT) algorithms optimize PV operation to ensure maximum power extraction under such variability. This review comprehensively classifies and analyzes MPPT techniques into three categories: classical, adaptive, and hybrid methods. Classical approaches including Perturb and Observe (P&amp;O) and Incremental Conductance (IncCond) remain widely adopted for their simplicity and low-cost implementation yet exhibit limitations under rapid environmental transients. Adaptive methods (e.g., Fuzzy Logic Controllers and Artificial Neural Networks) enhance accuracy and adaptability at the cost of computational resources. Hybrid techniques synergize classical and adaptive strategies to balance stability with responsiveness. The study further examines how temperature, irradiance fluctuations, and partial shading impact PV performance and MPPT efficacy. Critical evaluation reveals strengths and limitations of current methods, highlighting opportunities for reliability and efficiency improvements.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107227"},"PeriodicalIF":7.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AndroMD: An Android malware detection framework based on source code analysis and permission scanning","authors":"Arvind Prasad ,&nbsp;Shalini Chandra ,&nbsp;Wael Mohammad Alenazy ,&nbsp;Gauhar Ali ,&nbsp;Sajid Shah ,&nbsp;Mohammed ElAffendi","doi":"10.1016/j.rineng.2025.107050","DOIUrl":"10.1016/j.rineng.2025.107050","url":null,"abstract":"<div><div>The rapid growth of Android-based mobile and IoT applications has significantly increased the attack surface for malicious actors. These adversaries often exploit apps and social engineering to deliver malware that compromises device security and user privacy. To address this ongoing threat, we present AndroMD, an intelligent and scalable Android malware detection framework that combines automated dataset construction, optimal feature selection, and ensemble-based classification. The proposed framework is built on three core components. First, an automated pipeline processes over 600,000 APKs to extract static features from more than 140 million Java files and 600,000 manifest files, resulting in three distinct datasets: KeyCount, ZeroOne, and MNF. These datasets are constructed using keys and patterns derived from a detailed analysis of real decompiled malware code, ensuring semantic relevance. Second, we introduce the AndroMD Optimal Feature Selection (AOFS) method, which selects compact, high-performing feature subsets using iterative evaluation based on ensemble feedback. Third, an ensemble detection model combines Random Forest, Decision Tree, and Bagging classifiers, with a threshold-based aggregation mechanism that allows fine-grained control over detection sensitivity. Extensive evaluation demonstrates AndroMD's strong performance, achieving up to 99.88% accuracy on internal datasets and 91.66% accuracy in live testing, including detection of custom and zero-day malware samples. AndroMD also identifies threats overlooked by VirusTotal, showcasing its real-world applicability. The framework, along with sample datasets and code, is made publicly available to support reproducibility and further research on Android security.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107050"},"PeriodicalIF":7.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medical waste management in the modern healthcare era: A comprehensive review of technologies, environmental impact, and sustainable practices","authors":"Hossein Nematollahi ,&nbsp;Maryam Tuysserkani ,&nbsp;Ali Nematollahi","doi":"10.1016/j.rineng.2025.107210","DOIUrl":"10.1016/j.rineng.2025.107210","url":null,"abstract":"<div><div>This comprehensive review addresses critical challenges in modern medical waste management, a concern significantly heightened by the COVID-19 pandemic. Our work uniquely synthesizes and critically assesses emerging technologies, their economic feasibility, and sustainability frameworks within a post-COVID-19 context. The analysis reveals that while conventional incineration remains a dominant practice (60–75 % of global medical waste), it carries considerable environmental risks. In contrast, emerging solutions like plasma gasification and advanced pyrolysis are promising, but face significant implementation barriers. While plasma systems achieve a 90–97 % waste volume reduction and over 99.99 % pathogen elimination, and pyrolysis efficiently converts plastic waste into valuable fuels (35–50 wt% liquid oil), their high capital costs and operational complexities require careful consideration. The COVID-19 pandemic exacerbated waste pressures, increasing global medical waste production by an estimated 3.4 kg per bed per day, with surges up to 425 % in developing nations. We identify significant disparities in management, as many low-income countries face substantial infrastructure and resource challenges that hinder the adoption of these advanced technologies. This work concludes with a critical roadmap for future research and policy, emphasizing the need for robust technical innovations and harmonized international standards to foster more sustainable and pragmatic practices.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107210"},"PeriodicalIF":7.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145057299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Q-GRID SMART: A blockchain-enabled smart home energy management and analytics system","authors":"Ameni Boumaiza","doi":"10.1016/j.rineng.2025.107093","DOIUrl":"10.1016/j.rineng.2025.107093","url":null,"abstract":"<div><div>This study presents Q-GRID SMART, a decentralized, blockchain-enabled residential energy management platform integrating IoT-based monitoring, predictive analytics, and an interactive user dashboard. In a one-month pilot across 4,196 households in Doha, Qatar, machine learning models (GRU, Bi-LSTM) forecasted energy consumption, cost, and CO₂ emissions with RMSE = 160.9 kWh and MAE = 120.3 kWh. Post-deployment surveys (n = 312) indicated a Net Promoter Score of +42 and 87% reported improved energy awareness. The platform achieved an average 16.8% electricity reduction and 145.4 kg CO₂ savings per household per month. We further analyze how blockchain latency and confirmation times affect real-time control and user experience, proposing mitigation via edge control loops, batching, and Layer-2 solutions (state channels, rollups). These results demonstrate Q-GRID SMART's potential to deliver scalable, secure, and user-centric energy management solutions for utilities and households.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107093"},"PeriodicalIF":7.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced biomolecule sensing: Simulation and sensitivity analysis of a dielectric-modulated bilayer electrode in DGOTFT","authors":"Chandaboina Pavan Kumar,&nbsp;Manish Kumar Singh","doi":"10.1016/j.rineng.2025.107039","DOIUrl":"10.1016/j.rineng.2025.107039","url":null,"abstract":"<div><div>A dielectric-modulated bilayer electrode double-gate organic thin-film transistor (DMBE-DGOTFT), employing Dinaphtho[2,3-b:2',3'-f]thieno[3,2-b]thiophene (DNTT) as the active layer, is designed for selective and label-free biomolecule detection. The DMBE-DGOTFT biosensor leverages a biocavity integrated within the gate dielectric region, where the variations in dielectric constant and biomolecular charge density significantly influence the device electrical response. The key parameters, including Drain current variation, DNTT thickness, electric field distribution, charge polarity, and electrostatic potential—are systematically analyzed under diverse biosensing conditions using SILVACO ATLAS TCAD simulations. The DMBE-DGOTFT biosensor exhibits a maximum sensitivity of <span><math><mn>4.5</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>2</mn></mrow></msup></math></span> for a charged biomolecule (<span><math><msub><mrow><mi>Q</mi></mrow><mrow><mi>f</mi></mrow></msub><mo>=</mo><mn>1</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>12</mn></mrow></msup><mspace></mspace><msup><mrow><mtext>cm</mtext></mrow><mrow><mo>−</mo><mn>2</mn></mrow></msup></math></span>) at a dielectric constant of 12, it demonstrates superior performance compared to conventional dielectric-modulated double-gate biosensors, with a sensitivity of 38.1. The dual-gate control and bilayer electrode configuration enhance charge transport and gate coupling, resulting in improved drain current modulation and detection accuracy. With its high sensitivity, real-time detection capability, biocompatibility, and suitability for scalable, low-cost fabrication, the DMBE-DGOTFT platform offers significant promise for next-generation applications in medical diagnostics, environmental monitoring, and point-of-care healthcare systems.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107039"},"PeriodicalIF":7.9,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}