Summary

Eng (ISSN 2673-4117) is an international, peer-reviewed open access journal which publishes original papers, critical reviews, rapid communications, technical notes, and discussions on all areas of engineering. Eng's aim is to encourage scientists to publish their experimental and theoretical research relating to engineering science and technology in as much detail as possible. There is no restriction on the maximum length of the papers. Launched in 2020, Eng was indexed in Scopus in 2023. The journal was subsequently included in the Emerging Sources Citation Index (ESCI, Web of Science) in March 2024 and Ei Compendex in April 2025. It holds a 2025 Impact Factor of 3.5 and is ranked JCR Q1 in the “ENGINEERING, MULTIDISCIPLINARY” category. Its 2025 CiteScore is 4.1, and it currently ranks Q2 in Scopus’ “Engineering (miscellaneous)” category.

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Topic Review
Intelligent Construction
Intelligent construction refers to the integration of digital technologies, data-driven methods, artificial intelligence, and automated systems throughout the building life cycle to improve the planning, design, construction, and operation of built assets. It encompasses building information modeling (BIM), Internet of Things (IoT), digital twins, artificial intelligence (AI), machine learning, robotics, and construction automation, which can be combined to support information integration, monitoring, analysis, decision-making, and automated or semi-automated construction processes [1][2]. Rather than referring to a single technology, intelligent construction represents an integrated approach in which digital information and computational technologies are used to improve construction processes, productivity, safety, quality, and decision-making across the project life cycle [1]. BIM provides structured digital information about building components and project processes, while IoT devices, sensors, reality-capture technologies, and other data sources can provide information about the physical construction environment. These data can be integrated into digital twins to establish connections between physical assets and their digital representations, supporting applications such as construction progress monitoring, quality control, safety management, resource and logistics management, and predictive analysis [2][3]. AI and machine learning can be applied to tasks such as cost and schedule prediction, risk assessment, image-based quality inspection, safety monitoring, and decision support [4]. Robotics and automated construction systems further extend intelligent construction from digital analysis to physical execution, including automated material handling, robotic assembly, autonomous construction equipment, inspection, and human–robot collaboration [5]. The implementation of intelligent construction faces technical, organizational, and workforce-related challenges. Data quality, interoperability, and data integration can affect the reliability and scalability of systems that combine BIM, IoT, digital twins, AI, and robotic technologies [2][3]. Differences in data structures and software platforms may hinder information exchange across project participants, while insufficient data quality can reduce the reliability of AI-based analysis and digital-twin applications [2][3]. Implementation may also require substantial investment in digital infrastructure, changes to established workflows, and personnel with appropriate digital, analytical, and technical skills [1][3]. Therefore, intelligent construction depends not only on the adoption of individual technologies but also on their effective integration with project processes, information management, and human expertise throughout the building life cycle.
  • 25
  • 29 Sep 2026
Topic Review
Stretchable Electronic
Stretchable electronics is a class of electronic devices fabricated on elastomeric or flexible substrates that can sustain large tensile strain, bending, twisting, and out-of-plane deformation without loss of electrical functionality, in contrast to conventional rigid silicon-wafer electronics that fracture under even modest mechanical strain [1]. The devices are commonly constructed using inorganic semiconductor nanomaterials—such as silicon nanoribbons, ultrathin membranes, or wavy and serpentine interconnect structures—bonded to pre-strained elastomeric substrates so that buckling and out-of-plane wrinkling accommodate the applied strain while the active material itself remains well within its elastic deformation limit [2]. Alternatively, organic field-effect transistors embedded in soft elastomeric matrices and metallic nanowire networks are used to build large-area, conformable pressure and thermal sensor arrays and electronic-skin systems that can be stretched, twisted, bent, and conformally wrapped over arbitrary three-dimensional curvilinear surfaces while maintaining stable electrical conductivity and consistent electronic device performance under repeated mechanical cycling and deformation [3].
  • 12
  • 25 Sep 2026
Topic Review
Antibiotic Biodegradation
Antibiotic biodegradation is the microbially mediated transformation and mineralization of antibiotic compounds—such as sulfonamides, tetracyclines, fluoroquinolones, and macrolides—into less toxic or innocuous metabolites, carbon dioxide, water, and inorganic nitrogen or sulfur under aerobic or anaerobic conditions [1]. The process is carried out by specialized bacterial strains and mixed microbial communities, including ammonia-oxidizing bacteria and heterotrophic degraders, that express enzymes such as flavin-dependent monooxygenases and reductases which initiate attack on specific molecular substructures—for example, ipso-hydroxylation of the sulfonamide aromatic ring followed by cleavage of the sulfonamide bond to release the aniline fragment and the isoxazole side chain [2]. Biodegradation kinetics depend on antibiotic concentration, temperature, pH, nutrient availability, redox conditions, and whether the antibiotic serves as a primary carbon and energy source or is co-metabolized with another substrate; incomplete degradation can produce transformation products that retain antimicrobial activity and contribute to the spread of antibiotic resistance genes in the environment [3].
  • 11
  • 25 Sep 2026
Topic Review
Rail Transit Optimization
Rail transit optimization comprises the mathematical modeling and solution of operational planning problems in railway and urban metro systems, including line planning, train timetabling, rolling stock circulation, crew scheduling, and stop-skipping patterns [1]. The train timetabling problem determines the scheduled departure and arrival times of each train at each station, subject to safety constraints such as minimum headways, station track capacities, block-section occupancy rules, and speed restrictions, and it is typically formulated as a mixed-integer or multi-commodity flow model on a time-space network that represents each train path as a flow of units through nodes [2]. The objective function commonly balances long-term operational cost against service quality, minimizing fleet size, net energy consumption, or passenger waiting and in-vehicle travel time while satisfying time-dependent origin-destination travel demand; integrated approaches simultaneously optimize timetables, stop plans, and rolling stock assignments to account for the tight coupling between these interrelated operational planning decisions [3].
  • 12
  • 25 Sep 2026
Topic Review
Human-Automation Interaction
Human-automation interaction is the study of how human operators and automated systems divide functions and exchange control authority in complex sociotechnical systems, addressing how the allocation of tasks between human and machine affects performance, situation awareness, trust, mental workload, and operational safety [1]. A central conceptual framework decomposes automation into four classes of information-processing functions—information acquisition, information analysis, decision and action selection, and action implementation—and assigns to each function a graduated level of automation ranging from full manual control at one extreme to fully autonomous machine action with no human notification at the other [2]. The design problem is to select the appropriate level of automation for each function rather than automating maximally, because excessive automation can lead to loss of manual skills, overreliance, mode confusion, and reduced ability of the human operator to detect and recover from failures of the automated system, particularly when that automation is unreliable [3].
  • 57
  • 28 Sep 2026
Topic Review
Lean Manufacturing
Lean manufacturing is a production philosophy centered on the systematic identification and elimination of waste—defined as any activity that consumes resources but creates no value from the customer's perspective—while simultaneously shortening production lead times and improving the continuous, uninterrupted flow of material [1]. The approach is built on two foundational pillars: just-in-time production, in which only the necessary units are produced in the necessary quantities at the necessary time through a pull system signaled by kanban cards, and autonomation, or jidoka, in which equipment and workers automatically stop production when abnormalities or defects occur, preventing the propagation of defects downstream [2]. Value is specified from the customer's standpoint, the entire value stream for each product family is mapped to identify non-value-added steps, and value is made to flow continuously without interruptions, waiting, or overproduction, with the customer pulling demand and the organization pursuing continuous incremental improvement, or kaizen, through the participation of all workers [3].
  • 9
  • 25 Sep 2026
Topic Review
Rotating Machinery Diagnostics
Rotating machinery diagnostics is the process of identifying the mechanical condition and incipient faults of rotating equipment such as motors, pumps, compressors, turbines, and gearboxes by analyzing vibration, acoustic emission, and process signals acquired from accelerometers, velocity transducers, and proximity probes mounted on the machine bearing housings or shafts [1]. The diagnostic procedure relies on the fact that different mechanical faults—including rotor imbalance, shaft misalignment, rolling-element bearing defects, gear tooth damage, blade-passage phenomena, and mechanical rubs—produce characteristic vibration signatures at specific rotational frequencies, harmonics, sidebands, and high-frequency resonance frequencies that can be extracted through fast-Fourier-transform spectral analysis, high-frequency envelope demodulation, and time-synchronous averaging [2]. Advanced signal-processing methods such as spectral kurtosis and cyclostationary analysis are used to detect weak, impulsive, and non-stationary fault features buried in background noise, and the diagnosed mechanical condition is used to determine whether scheduled corrective maintenance, component replacement, or continued safe operation is warranted [3].
  • 13
  • 25 Sep 2026
Topic Review
Coagulation-Flocculation
Coagulation-flocculation is a physicochemical water treatment process in which charged colloidal particles that remain stably dispersed because of electrostatic repulsion are destabilized and then aggregated into larger settleable flocs [1]. In the coagulation stage, coagulants such as aluminum sulfate, ferric chloride, or cationic polymers are rapidly mixed into the water to neutralize the surface charge of the colloids, compress the electric double layer, and form microflocs; in the flocculation stage, gentle slow mixing promotes perikinetic and orthokinetic collisions among the destabilized particles so that they grow into dense, macroscopic flocs that can be removed by subsequent sedimentation and granular-media filtration [2]. The process is evaluated using standardized jar-test procedures that determine the optimal coagulant dose, pH, and mixing intensity, and its performance is governed by the surface chemistry of the suspended particles, the hydrolysis speciation of the added metal salts, and the mean velocity gradient generated by flocculation basin mixers [3].
  • 14
  • 28 Sep 2026
Topic Review
Bifunctional Electrocatalysis
Bifunctional electrocatalysis refers to the catalytic behavior of a single electrode material that promotes two distinct electrochemical reactions at different electrode potentials, most commonly the oxygen reduction reaction at the cathode and the oxygen evolution reaction at the anode in rechargeable metal-air batteries and unitized regenerative fuel cells [1]. A bifunctional oxygen catalyst must simultaneously exhibit high activity and low overpotential for both the four-electron reduction of oxygen to water and the reverse oxidation of water to oxygen, while remaining stable over the wide potential window that alternates between reducing and oxidizing conditions during discharge and charge cycles [2]. The activity of such materials is governed by the electronic structure of the catalytically active sites—particularly the occupancy of transition-metal d-orbitals, the covalency between metal and oxygen, and the adsorption energetics of reaction intermediates such as hydroxyl, oxide, and peroxide species on the surface [3]. Non-precious-metal candidates including manganese oxides, perovskite oxides, and transition-metal-nitrogen-carbon composites are evaluated by the potential gap between the oxygen evolution and reduction polarization curves.
  • 5
  • 24 Sep 2026
Topic Review
Activated Sludge
Activated sludge is a biological wastewater treatment process in which a suspended culture of aerobic microorganisms is mixed with wastewater in an aeration tank and supplied with oxygen, so that the microorganisms metabolize dissolved and particulate organic matter into carbon dioxide, water, and new cell mass [1]. The mixed liquor then flows to a secondary sedimentation tank where the microbial flocs settle by gravity; a portion of the settled biomass is returned to the aeration tank as return activated sludge to maintain the desired mixed-liquor suspended-solids concentration, while the excess biomass is wasted as waste activated sludge [2]. The process is characterized by operational parameters including the sludge age, or mean cell residence time, the food-to-microorganism ratio, and the oxygen uptake rate, and its kinetics are described by structured mathematical models that relate substrate removal, biomass growth, and nutrient transformations to the hydraulic and solids retention times [3]. Flocculation of the microbial biomass is essential for efficient solid-liquid separation in the secondary clarifier.
  • 10
  • 24 Sep 2026
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