International Journal of Materials and Product Technology (14 papers in press)

Special Issue on: OA The Application of Advanced Materials for Smart and Sustainable Manufacturing

• Open Access

  Colour fixation process and colour fastness improvement strategies for natural plant dyes in functional clothing fabrics ( Free Full-text Access )

  by Jiaheng Han, Zicheng Zhang, Jiang Chang 
  Abstract: The application of natural plant dyes in functional textiles is limited by poor colour fastness and difficulty in colour fixation. Functional additives can reduce fibre surface polarity, shield active sites, and hinder dye uptake. Traditional metal mordant dyeing methods also carry the risk of chemical interference with functional components, compromising performance stability. This study proposes an optimised colour fixation method. First, plant dyes compatible with functional fabrics are selected, and dyeing parameters are adjusted to ensure uniform dye penetration into the fibres. Then, a customised fixing agent is used to enhance dye-fibre bonding through high-temperature steam and mild chemical crosslinking. Dyeing conditions (such as pH, time, and temperature) are further optimised to improve colour fixation. Results show that after 25 washes, the antibacterial fabric achieves a wash fastness of 2.7, with a dye residue rate of 70.1%. The light fastness remains at 3.9 (initial value: 5) after 120 hours of exposure, and the antibacterial rate remains at 91.6% after washing. This method effectively improves colour durability while preserving the fabrics functional properties.
  Keywords: natural plant dyes; functional clothing fabrics; colour fixation process; colour fixing agent formulation; dyeing process.
  DOI: 10.1504/IJMPT.2026.10078276
   
  

• Open Access

  Preparation of intelligent responsive printing materials and their application in anticounterfeiting and packaging ( Free Full-text Access )

  by Hong Wu, Xiaorong Zhou, Quan Li 
  Abstract: In order to address the challenges of insufficient stability and accuracy in the large-scale application of intelligent responsive printing materials, this paper first designs a dual chamber microcapsule structure with temperature and light dependent response, and applies nano interface crosslinking agents to improve polymer crosslinking density. Secondly, this paper optimises the rheological properties of ultraviolet (UV) ink, adjusts the monomer molecular structure to match surface tension, and makes it suitable for high-speed screen/inkjet printing processes. Finally, this paper constructs a portable detection terminal based on smartphone spectral sensing and support vector machine convolutional neural network (SVM-CNN) algorithm. The results showed that the colour retention rate after five cold chain cycles was 83.33%, the fracture rate after 48 hours of mechanical vibration was only 2.0%, the accuracy of the 5-level high-quality imitation label was 97.5%, and the response threshold drift reached 0.30 C within 96 hours.
  Keywords: intelligent responsive printing materials; anticounterfeiting and packaging; microcapsule structure; environmental tolerance; portable detection.
  DOI: 10.1504/IJMPT.2026.10078783
   
  

• Open Access

  Crack resistance and toughening mechanism of nano-SiO2 reinforced PVA fibre cement matrix composites in steel bridge engineering ( Free Full-text Access )

  by Pingrang Wang, Yue Wang 
  Abstract: This paper aims to study the crack resistance and toughening properties of nano silica reinforced polyvinyl alcohol (PVA) fibre cement-based composites, hoping that these composites can be better applied in steel bridge engineering. This paper designs a cement-based composite material using quartz sand, cement, nano silica, and PVA fibres as raw materials. This paper controls the dosage of nano silica at six levels (0, 0.5, 1, 1.5, 2, and 2.5) and analyses the performance of PVA fibre cement-based composites at these levels. The results showed that compared with cement-based composites containing PVC fibres, cement-based composite materials containing 0.5% nano silica increased their compressive strength, flexural strength, initial fracture toughness, and unstable fracture toughness by 10.3%, 13.7%, 8.3%, and 11.8%, respectively. This indicates that the appropriate addition of nano silica in PVA fibre cement-based composite materials can prevent cracking and toughen the material, giving it sufficient strength for steel bridge engineering.
  Keywords: cement-based composite; crack resistance and toughening mechanism analysis; nano silica; nanometre materials; steel bridge engineering.
  DOI: 10.1504/IJMPT.2026.10078899
   
  

• Open Access

  Parametric design in ceramic product form generation and manufacturing optimisation ( Free Full-text Access )

  by Liwen Yu, Yao Chen 
  Abstract: Traditional methods of design for ceramics are inefficient due to a lack of innovative solutions in addition to precision issues with manufacturing. This paper provides a modelling approach that utilises NURBS, parameter-based design and the NSGA-II multi-objective optimisation process to mitigate some of these challenges. The morphological characteristics of the design are transformed into a parameterised controllable design space and used in conjunction with process parameters (which include shrinkage rates and sintering temperatures) and performance metrics (such as structural strength) for the purposes of determining objective measures. The iterative process carried out by the NSGA-II algorithm determines Pareto-optimal solutions, each demonstrating a balance between aesthetics and manufacturability. The following statistics were generated reflecting improvements over the initial population: average structural stiffness had an increase from approximately 55 N/mm to approximately 75 N/mm; average material usage decreased from approximately 81,000 to approximately 65,000 units; median maximum geometric deviation decreased from 1.62 mm to approximately 0.57 mm. The method enables efficient generation of complex free-form ceramic designs with enhanced strength, reduced material consumption and superior dimensional accuracy.
  Keywords: parametric design; multi-objective optimisation; ceramic product; form generation; manufacturing process modelling.
  DOI: 10.1504/IJMPT.2026.10078932
   
  

• Open Access

  Design of a GUI framework for digital home appliance products based on artificial intelligence ( Free Full-text Access )

  by Weijian Zeng, Lijie Zhou, Jongki Kim 
  Abstract: With the continuous breakthrough and popularisation of computer technology, network communication, and multimedia applications, people have put forward higher requirements for the design of smart home appliances. As an indispensable part of home decoration, digital home appliances have also emerged to adapt to it. This article used artificial intelligence technology to design a graphical user interface (GUI) framework for digital home appliance products, and introduced the structural model of embedded GUI. The functional requirements of the digital home appliance product GUI framework and the application of artificial intelligence within it have been analysed, and the GUI frameworks structural design and main functions have been explained. Starting from design theory and specific practice, this paper explores how to achieve better user interaction and solutions based on the artificial intelligence GUI framework.
  Keywords: GUI framework; digital appliances; home appliance products; artificial intelligence.
  DOI: 10.1504/IJMPT.2026.10079053
   
  

• Open Access

  Preparation and performance of supramolecular polymer-based piezoresistive damping composites ( Free Full-text Access )

  by Xuan Wang, Xue Yang, Yu Li, Xincan Lu, Songlin Chen, Zilin Geng 
  Abstract: This paper proposes a collaborative construction strategy based on molecular design and multi-scale structure tuning to address the main conflict between high damping efficiency and sustainable piezoresistive response in supramolecular polymer based piezoresistive damping composites. Firstly, this paper constructs a dynamically reversible thermoplastic polyurethane matrix by introducing a quadruple hydrogen bond UPy (2-ureido-4 [1H] pyrimidinone) unit, and controls the hydrogen bond density to optimise the internal friction ability. Secondly, this paper proposes a heterogeneous mixed filler composed of aminated SiO2 (silicon dioxide) and carboxylated multi walled carbon nanotubes. Finally, this paper prepares a series of composite materials through solution mixing hot pressing process, and predicts the synergistic window of electromechanical properties using an improved percolation Maxwell model. The results showed that the prepared composite material had a mixed filler content of 5 wt%, a peak damping loss factor of 0.83, and a piezoresistive sensitivity of 12.4.
  Keywords: supramolecular polymer; piezoresistive damping; hybrid filler; dynamic hydrogen bonding; multifunctional composite.
  DOI: 10.1504/IJMPT.2026.10079054
   
  

• Open Access

  Algorithm for visual communication design: generating textures of composite materials using artificial intelligence ( Free Full-text Access )

  by Dong Chen, Qing Li 
  Abstract: In response to the lack of authenticity and quality in composite material texture generation in the field of visual communication design, this article adopts a self-attention generative adversarial network (GAN) algorithm to study it. This article enhances the texture dataset for composite materials, thereby expanding the available datasets. The self-attention mechanism is applied to the generator and discriminator of generative adversarial networks, and the networks are jointly optimised. Then, the perceptual loss function and an adaptive adversarial loss function are applied to improve the similarity and authenticity between the generated and real images and a progressive fine-tuning strategy is adopted to train the model. The evaluation results of the self-attention generative adversarial network show excellent performance in three indicators, SSIM, PSNR, and Perceptual Loss, with mean values of 0.82, 23.22, and 0.012, respectively, and the score of the model is 67. Overall, the improved network described in this article offers significant advantages for composite material texture generation, providing a more reliable solution for the field of visual communication design.
  Keywords: generative adversarial network; GAN; self-attention mechanism; composite texture generation; visual communication design; image quality evaluation.
  DOI: 10.1504/IJMPT.2026.10079055
   
  

• Open Access

  Composite material surface texture generation and cultural and creative design application based on generative adversarial networks ( Free Full-text Access )

  by Yuandong Jiang, Shuyi Wang 
  Abstract: This paper proposes a composite material texture generation and cultural and creative design method based on generative adversarial networks (GANs). A multi-scale convolutional generator and self-attention mechanism are constructed to capture microscopic fibre structures and macroscopic texture layouts. Physical constraint encodings of fibre orientation, interlayer interfaces, and micro-defects are embedded in the generator. A structure discriminator evaluates the microscopic realism of the material, while a design style discriminator, combined with a style encoder, applies multi-dimensional latent style vectors to control colour, texture density, geometric feel, and visual contrast. Latent space interpolation and a texture fusion module are used to achieve a smooth combination of different material textures and styles. A design adaptation module performs multi-scale splicing and visual evaluation to output usable texture images for cultural and creative designs.
  Keywords: generative adversarial network; GAN; composite material texture; multi-scale convolution; style control; visual diversity.
  DOI: 10.1504/IJMPT.2026.10079186
   
  

• Open Access

  Adaptability of welding process parameters and defect control in ship cabin based on low-carbon steel-based materials ( Free Full-text Access )

  by Zhifeng Zhao, Shan Zhou 
  Abstract: Due to the mismatch between current welding process parameters for ship compartments and the metallurgical response of low-carbon steel-based materials, defects such as hot cracking and porosity are easily generated, leading to insufficient joint reliability. To address this issue, this paper first uses Gleeble thermal simulation software to calibrate the phase transformation kinetics and critical strain threshold for hot cracking of the material. Second, the aforementioned metallurgical response characteristics are embedded as constraints into a thermo-mechanical coupled finite element model to extract local thermal cycles and strain rate fields. Then, a Gaussian process surrogate model is constructed with the dual objectives of minimising the HTI (hot cracking tendency index) and maximising the equivalent strength. Finally, the optimal combination of process parameters is searched sequentially using the expected improvement criteria in Bayesian optimisation. Experimental verification shows that this method can achieve a median HTI of 0.18 for the weld, a tensile strength of 512 MPa at the weld centre, and effectively suppress inherent defects.
  Keywords: low-carbon steel; ship cabin welding; adaptive parameter optimisation; thermo-metallurgical-mechanical coupling; welding defect control.
  DOI: 10.1504/IJMPT.2026.10079471
   
  

• Open Access

  Intelligent prediction of geometric morphology of missing parts in Clarke ceramic tile based on 3D-GAE image autoencoder and precise completion in 3D printing ( Free Full-text Access )

  by Yibing Yang, Qiang Zhao 
  Abstract: In the restoration of Clark porcelain, in order to solve the problem of insufficient completion accuracy caused by incomplete geometric information and highly complex fragment shapes, this paper adopts an intelligent prediction method based on 3D graphic autoencoder (3D-GAE). This paper first constructs a point cloud structure of Clark porcelain fragments, integrating local adjacency and global symmetry constraints; then, designs a three-layer graph convolutional encoder to extract 128 dimensional latent vectors; and adopts a mask guided training strategy, combined with L2 loss and chamfer distance, to optimise the reconstruction of missing areas; finally, generates a watertight mesh model suitable for FDM printing through Poisson reconstruction, curvature smoothing, and wall thickness detection. The experiment showed that the proposed method achieved a CD of only 0.62 millimetres and an HD of only 2.87 millimetres in areas with high missed detection rates (70%), demonstrating high geometric fidelity.
  Keywords: Clark ceramics; 3D graph autoencoder; 3D-GAE; intelligent prediction; geometric completion; 3D printing; symmetry constraints.
  DOI: 10.1504/IJMPT.2026.10079715
   
  

• Open Access

  Visual communication morphology generation and algorithm control of photosensitive resins in UV curing process ( Free Full-text Access )

  by Boying Qie 
  Abstract: This paper proposes a temporal UV exposure path generation algorithm driven by visual semantic parameterised mapping for photosensitive resin curing. Structural rhythm, spatial hierarchy, and morphological tension are encoded into a continuous semantic parameter field and jointly modelled with UV exposure intensity, density coefficients, and priority factors, then converted into machine-executable exposure trajectories, establishing a direct pathway from visual semantics to physical curing instructions. Experimental results show that the proposed method achieves significantly higher morphological tension intensity (0.87) and rhythmic change rate (0.83) than static exposure strategies (0.42 and 0.35). Curing analysis further verifies effective characterisation of nonlinear resin curing behaviour, demonstrating a controllable and expressive morphology generation framework for digital cultural and visual communication applications.
  Keywords: visual semantic parameterisation; time-series UV exposure path generation; photosensitive resin curing; visual communication; closed-loop coupling mechanism.
  DOI: 10.1504/IJMPT.2026.10079716
   
  

• Open Access

  An algorithm for ranking environmentally friendly material floor plan design schemes integrating life cycle assessment ( Free Full-text Access )

  by Shuqin Zhang, Hongying Yan, Yanchi Fan, Yangyang Ma, Xizhan Tu 
  Abstract: Current evaluation of environmentally friendly material floor plan designs in exhibition design lacks a life cycle perspective considering design contexts such as service life and disassembly frequency, and subjective design preferences are difficult to effectively integrate with objective environmental data. To address this, this paper constructs a ranking algorithm framework for environmentally friendly material floor plan design schemes that integrates life cycle assessment (LCA) within the exhibition design context. This framework first constructs an LCA model covering the entire process of raw material acquisition, manufacturing, transportation, installation and dismantling, use and maintenance, and decommissioning, using each square metre/single exhibition period as a functional unit. The model explicitly incorporates assumptions about material lifespan and dismantling frequency to address the issue of traditional evaluations neglecting differences in usage stages. This method can provide a quantifiable, interpretable, and context- and uncertainty-tested decision support tool for selecting environmentally friendly materials in exhibition design.
  Keywords: environmentally friendly materials; scheme ranking; life cycle assessment; LCA; relative proximity; exhibition design; multi-criteria decision making; service life.
  DOI: 10.1504/IJMPT.2026.10079717
   
  

• Open Access

  Optimisation design of clothing 3D printing materials by combining machine learning and computer graphics ( Free Full-text Access )

  by Pei Wen, Yingqi Fu 
  Abstract: This paper addresses the challenges of poor forming accuracy, low design efficiency, and comfort in 3D clothing printing. It proposes an intelligent optimisation framework integrating computer graphics and machine learning, shifting from experience-driven to closed-loop optimisation. Implicit surface modelling and finite element simulation are used to extract geometric and physical features, while a deep neural network surrogate model enables rapid prediction of forming performance. The multi-objective Bayesian optimisation (MOBO) algorithm optimises lattice parameters and printing paths for comfort and material efficiency. A parametric-machine learning collaborative design framework supports large-scale parameter optimisation. Experimental results show high geometric forming accuracy, with average root mean square error (RMSE) values of 0.081 mm (shoulder), 0.092 mm (armhole), 0.073 mm (waistline), and 0.087 mm (hem). Average printing time is reduced to 85.3 minutes, and average material consumption is only 100.4 grams. The method successfully achieves multi-objective synergistic optimisation of forming quality, mechanical properties and wearing comfort.
  Keywords: machine learning; computer graphics; 3D printing of garments; implicit surface modelling; multi-objective Bayesian optimisation; MOBO; material forming accuracy.
  DOI: 10.1504/IJMPT.2026.10079855
   
  

• Open Access

  Zonal material design and performance evaluation of cooling protective clothing based on human body thermal moisture distribution map ( Free Full-text Access )

  by Xiaoxi Zhao, Feifei Song 
  Abstract: In the design of protective clothing for high-temperature operations, this paper addresses the issues of insufficient overall thermal comfort and redundant material functions caused by differences in local thermal and moisture loads on the human body. A zonal material design method based on measured thermal and moisture distribution maps is adopted. The core of this method is to map the measured human body thermal and moisture load distribution into a spatial demand map, and accordingly divide it into high, medium and low functional zones. For each zone, thermal conductivity and moisture permeability parameters are precisely matched to construct a differentiated material library. Zonal cutting is performed based on a three-dimensional human body model, and a seamless hot-pressing process is used to achieve multi-material integration. Furthermore, gradient transition rules between materials and a double-layer composite structure are defined to ensure interface thermal and moisture compatibility and dynamic wearing stability, forming a closed-loop design system from physiological data to product structure.
  Keywords: high-temperature work; cooling protective clothing; thermal and humidity distribution map; zoned materials; 3D human body model.
  DOI: 10.1504/IJMPT.2026.10079856