Sustainable and affordable supply of clean, safe, and adequate water is one of the most challenging issues facing the world. Membrane separation technology is one of the most cost-effective and widely applied technologies for water purification. Polymeric membranes such as cellulose-based (CA) membranes and thin-film composite (TFC) membranes have dominated the industry since 1980. Although further development of polymeric membranes for better performance is laborious, the research findings and sustained progress in inorganic membrane development have grown fast and solve some remaining problems. In addition to conventional ceramic metal oxide membranes, membranes prepared by graphene oxide (GO), carbon nanotubes (CNTs), and mixed matrix materials (MMMs) have attracted enormous attention due to their desirable properties such as tunable pore structure, excellent chemical, mechanical, and thermal tolerance, good salt rejection and/or high water permeability. This review provides insight into synthesis approaches and structural properties of recent reverse osmosis (RO) and nanofiltration (NF) membranes which are used to retain dissolved species such as heavy metals, electrolytes, and inorganic salts in various aqueous solutions. A specific focus has been placed on introducing and comparing water purification performance of different classes of polymeric and ceramic membranes in related water treatment industries. Furthermore, the development challenges and research opportunities of organic and inorganic membranes are discussed and the further perspectives are analyzed.
In recent years, an increasing popularity of deep learning model for intelligent condition monitoring and diagnosis as well as prognostics used for mechanical systems and structures has been observed. In the previous studies, however, a major assumption accepted by default, is that the training and testing data are taking from same feature distribution. Unfortunately, this assumption is mostly invalid in real application, resulting in a certain lack of applicability for the traditional diagnosis approaches. Inspired by the idea of transfer learning that leverages the knowledge learnt from rich labeled data in source domain to facilitate diagnosing a new but similar target task, a new intelligent fault diagnosis framework, i.e., deep transfer network (DTN), which generalizes deep learning model to domain adaptation scenario, is proposed in this paper. By extending the marginal distribution adaptation (MDA) to joint distribution adaptation (JDA), the proposed framework can exploit the discrimination structures associated with the labeled data in source domain to adapt the conditional distribution of unlabeled target data, and thus guarantee a more accurate distribution matching. Extensive empirical evaluations on three fault datasets validate the applicability and practicability of DTN, while achieving many state-of-the-art transfer results in terms of diverse operating conditions, fault severities and fault types.
Chao-feng Liang, Chao-feng Liang, Bihao Pan
et al.
Abstract In recent years, the CO2 curing technique has been developed to enhance the properties of recycled aggregate (RA) and recycled aggregate concrete (RAC), materials that can absorb the CO2 gas and are more sustainable for the construction industry. A body of literature on the CO2 curing of RA and RAC is currently available, but a systematic review is lacking. Therefore, this paper reviewed the published literatures on the use of CO2 curing to enhance the properties of the RA and prepared RAC. The studies on CO2 curing technology, the properties of carbonated recycled aggregate (CRA), and the micro-properties, workability, mechanical properties and durability performance of concrete with CRA are respectively reviewed. The results showed that the RA properties, CO2 concentration and pressure, relative humidity and curing time all had a significant impact on the properties of CRA. Carbonation treatment improved the pore structure of RA and reduced its porosity, and the workability, mechanical properties and durability performance of prepared RAC were also improved. In addition, an outlook on the CO2 curing of RA and prepared concrete was presented, and we expected that this work may inform further investigation of the use of CO2 curing to enhance the properties of concrete and cement products.
Yajie Zhong, Patrick M. Godwin, Yongcan Jin
et al.
Abstract Recently, the demands for biodegradable and renewable materials for packaging applications have increased tremendously. This rise in demand is connected to the growing environmental concerns over the extensive use of synthetic and non-biodegradable polymeric packaging, polyethylene in particular. The performance of biodegradable polymers is discussed in this review, with a particular focus on the blends of starch and other polymers. Furthermore, in food packaging industry, microbial activities are of great concern. Therefore, incorporation of antimicrobial agents or polymers to produce barrier-enhanced or active packaging materials provides an attractive option for protecting food from microorganism development and spread. Additionally, the barrier, mechanical and other properties of biodegradable polymers are discussed. Lastly, the existing and potential applications for bioactive coatings on antimicrobial packaging materials are also addressed.
Boosted by the success of high‐entropy alloys (HEAs) manufactured by conventional processes in various applications, the development of HEAs for 3D printing has been advancing rapidly in recent years. 3D printing of HEAs gives rise to a great potential for manufacturing geometrically complex HEA products with desirable performances, thereby inspiring their increased appearance in industrial applications. Herein, a comprehensive review of the recent achievements of 3D printing of HEAs is provided, in the aspects of their powder development, printing processes, microstructures, properties, and potential applications. It begins with the introduction of the fundamentals of 3D printing and HEAs, as well as the unique properties of 3D‐printed HEA products. The processes for the development of HEA powders, including atomization and mechanical alloying, and the powder properties, are then presented. Thereafter, typical processes for printing HEA products from powders, namely, directed energy deposition, selective laser melting, and electron beam melting, are discussed with regard to the phases, crystal features, mechanical properties, functionalities, and potential applications of these products (particularly in the aerospace, energy, molding, and tooling industries). Finally, perspectives are outlined to provide guidance for future research.
Polymer 3D printing is an emerging technology with recent research translating towards increased use in industry, particularly in medical fields. Polymer printing is advantageous because it enables printing low-cost functional parts with diverse properties and capabilities. Here, we provide a review of recent research advances for polymer 3D printing by investigating research related to materials, processes, and design strategies for medical applications. Research in materials has led to the development of polymers with advantageous characteristics for mechanics and biocompatibility, with tuning of mechanical properties achieved by altering printing process parameters. Suitable polymer printing processes include extrusion, resin, and powder 3D printing, which enable directed material deposition for the design of advantageous and customized architectures. Design strategies, such as hierarchical distribution of materials, enable balancing of conflicting properties, such as mechanical and biological needs for tissue scaffolds. Further medical applications reviewed include safety equipment, dental implants, and drug delivery systems, with findings suggesting a need for improved design methods to navigate the complex decision space enabled by 3D printing. Further research across these areas will lead to continued improvement of 3D-printed design performance that is essential for advancing frontiers across engineering and medicine.
Abstract Additive manufacturing (AM) is a digital manufacturing technology, rapidly revolutionizing in the medical sectors for printing of distinct body parts having intrinsic shapes and offering customized solutions to every patient. In the past few decades, AM is used as a versatile and cost-effective method for the manufacturing of geometrically complicated shape in the medical industry. In addition, AM technology is used for the development of products from dental implants to heart valves and joint replacements etc. This is the technology that makes a physical model directly from CAD models by adding materials in layer by layer fashion and offers robust mechanical properties. This review paper aims to consolidate the contribution of various researchers in the area of AM especially focusing the applications in the medical field using various technologies of AM, materials and their mechanical properties, so that this review paper could become the torch bearer for the futuristic researchers working in this area.
Native starch is subjected to various forms of modification to improve its structural, mechanical, and thermal properties for wider applications in the food industry. Physical, chemical, and dual modifications have a substantial effect on the gelatinization properties of starch. Consequently, this review explores and compares the different methods of starch modification applicable in the food industry and their effect on the gelatinization properties such as onset temperature (To), peak gelatinization temperature (Tp), end set temperature (Tc), and gelatinization enthalpy (ΔH), studied using differential scanning calorimetry (DSC). Chemical modifications including acetylation and acid hydrolysis decrease the gelatinization temperature of starch whereas cross-linking and oxidation result in increased gelatinization temperatures. Common physical modifications such as heat moisture treatment and annealing also increase the gelatinization temperature. The gelatinization properties of modified starch can be applied for the improvement of food products such as ready-to-eat, easily heated or frozen food, or food products with longer shelf life.
Jakka Mahesh, Chitrartha Dixit, Pavel Vijay Gaurkar
et al.
Active Vehicle Safety Systems (AVSS) play a pivotal role in enhancing road safety by reducing accident-related fatalities, particularly in Heavy Commercial Road Vehicles (HCRVs), which predominantly employ pneumatic braking systems. The effective performance of these systems hinges on the availability of fast-acting actuators capable of delivering precise pressure control. This study presents a framework for optimization of an existing actuator valve to improve its responsiveness and fidelity for AVSS applications, with adherence to the automotive braking standard IS 11852. A physics-based model of the actuator valve was developed to identify critical design parameters that influence its dynamic performance. Subsequently, an extensive Design of Experiments (DoE) methodology was employed to determine the optimal valve geometry. Evaluation of the optimized valve on a Hardware-in-the-Loop (HiL) setup demonstrated a significant improvement in performance, with reductions of 35.8% and 45.6% in brake apply and exhaust times, respectively, relative to the baseline valve achieved without compromising adherence to the IS 11852 standard. These enhancements in valve response translated into notable improvements in Antilock Brake System (ABS) performance, yielding a 9.3% reduction in stable braking distance and an 8.2% increase in Mean Fully Developed Deceleration (MFDD). Furthermore, these performance gains were validated through on-vehicle testing on a single-unit 4 × 2 19-tonne vehicle. Upon evaluation in an unladen vehicle on high-friction surfaces, a commonly encountered critical braking condition, the optimized valve achieved a 6.8% reduction in stable braking distance and a 3.7% increase in MFDD. These results affirm the practical viability and performance advantages of the optimized valve design for AVSS integration in HCRVs.
Cyber-Physical Systems (CPS) play a critical role in modern industrial domains, including manufacturing, energy, transportation, and healthcare, where they enable automation, optimization, and real-time decision-making. Ensuring the robustness of these systems is paramount, as failures can have significant economic, operational, and safety consequences. This paper present findings from an industrial survey conducted in Wallonia, covering a wide range of sectors, to assess the current state of practice in CPS robustness. It investigates robustness from how it is understood and applied in relationship with requirements engineering, system design, test execution, failure modes, and available tools. It identifies key challenges and gaps between industry practices and state-of-the-art methodologies. Additionally, it compares our findings with similar industrial surveys from the literature.
Flavien Armangeon, Thibaud Ehret, Enric Meinhardt-Llopis
et al.
Aligning functional schematics with 2D and 3D scene acquisitions is crucial for building digital twins, especially for old industrial facilities that lack native digital models. Current manual alignment using images and LiDAR data does not scale due to tediousness and complexity of industrial sites. Inconsistencies between schematics and reality, and the scarcity of public industrial datasets, make the problem both challenging and underexplored. This paper introduces IRIS-v2, a comprehensive dataset to support further research. It includes images, point clouds, 2D annotated boxes and segmentation masks, a CAD model, 3D pipe routing information, and the P&ID (Piping and Instrumentation Diagram). The alignment is experimented on a practical case study, aiming at reducing the time required for this task by combining segmentation and graph matching.