Search Results (54)

This paper proposes a robust methodology for integrating process-specific data and domain expert knowledge into linked knowledge graphs. These graphs utilize an ontology that provides a standardized vocabulary for material science and facilitates the creation of semantic models for various processes along the digital process chain. A generic template for structuring processes is proposed, simplifying subsequent data retrieval. The templates of specific processes are designed collaboratively by domain and ontology experts, aided by a proposed interview template that bridges the knowledge gap. Following the digitalization of material data through semantic modeling, machine-readable data with contextual metadata is stored in a graph database, which can be efficiently queried using the SPARQL language, enabling seamless integration into data pipelines. To demonstrate this approach, a knowledge graph is developed to represent the process chain of AlSi10Mg objects manufactured via permanent mold casting, capturing their complete history from the initial manufacturing step to final non-destructive testing and mechanical characterization. This methodology enhances data interoperability and accessibility while providing context-rich data for training AI models, potentially accelerating new knowledge discovery in material science. Full article

The forming process of multi-alloy gears by metal powder injection molding is tedious, and the current design process mainly depends on the experience of designers, which seriously affects the product development cycle and forming quality. In order to solve the problem of the gear feature expression being missing, which hinders the automatic retrieval of similar parts in the analogical design process, a feature recognition and intelligent retrieval method for a multi-alloy powder injection molding gear based on partition templates is proposed in this paper. The partition templates of the gear are defined, and gear digitization is completed by using the automatic recognition algorithm. Searching for similar gear parts in the knowledge base, designers can analogically design the forming process for new parts according to the mature process of the parts in the knowledge base. The automatic identification and intelligent retrieval system developed according to this method has been implemented in two MIM (metal injection molding) product manufacturing enterprises. Case studies and industrial applications have proved the effectiveness of the system, the efficiency of identification and retrieval has been improved by more than 97%, and the number of mold tests has been reduced by 60%. Full article

In order to improve the preparation efficiency, quality stability, and large-area preparation of superhydrophobic thin films, a roll-to-roll continuous micro–nano imprinting method for the efficient preparation of superhydrophobic polymer films is proposed. A wear-resistant mold roller with hierarchical microstructure is prepared by wire electrical discharge machining (WEDM). The rheological filling model is constructed for revealing the forming mechanism of superhydrophobic polymer films during continuous micro/nano imprinting. The effects of imprinting temperature, rolling speed and the surface texture size of the template on the surface texture formation rate of polymer films are analyzed. The experimental results show that, compared with other process methods, the template processed by WEDM shows excellent wear resistance. Moreover, the optimal micro/nano imprinting parameters are the mold temperature of 190 °C (corresponding film temperature of 85 ± 5 °C), rolling speed of 3 rpm and roller gap of 0.1 mm. The maximum contact angle of the polymer film is 154°. In addition, the superhydrophobic polymer thin film has been proven to have good self-cleaning and anti-icing performance. Full article

Material deformation during nanoimprinting of aluminum (Al), copper (Cu), and gold (Au) was explored through molecular dynamics simulations. A comparative understanding of the deformation behavior of three substrate materials important for design and high-resolution pattern transfer was highlighted. In this study, we analyzed three metrics, including von Mises stresses, lattice deformation, and spring-back for the chosen materials. Of the three materials, the highest average von Mises stress of 7.80 MPa was recorded for copper, while the lowest value of 4.68 MPa was computed for the gold substrate. Relatively higher von Mises stress was observed for all three materials during the mold penetration stages; however, there was a significant reduction during the mold relaxation and retrieval stages. The Polyhedral Template Matching (PTM) method was adopted for studying the lattice dislocation of the materials. Predominantly Body-Centered Cubic (BCC) structures were observed during the deformation process and the materials regained more than 50% of their original Face-Centered Cubic (FCC) structures after mold retrieval. Gold had the lowest vertical spring-back at 6.54%, whereas aluminum had the highest average spring-back at 24.5%. Of the three materials, aluminum had the lowest imprint quality due to its irregular imprint geometry and low indentation depth after the NIL process. The findings of this research lay a foundation for the design and manufacture of Nanoimprint Lithography (NIL) molds for different applications while ensuring that the replicated structures meet the desired specifications and quality standards. Full article

Although regenerative medicine necessitates advanced three-dimensional (3D) scaffolds for organ and tissue applications, creating intricate structures across scales, from nano- to meso-like biological tissues, remains a challenge. Electrospinning of nanofibers offers promise due to its capacity to craft not only the dimensions and surfaces of individual fibers but also intricate attributes, such as anisotropy and porosity, across various materials. In this study, we used a 3D printer to design a mold with polylactic acid for gel modeling. This gel template, which was mounted on a metal wire, facilitated microfiber electrospinning. After spinning, these structures were treated with EDTA to remove the template and were then cleansed and dried, resulting in 3D microfibrous (3DMF) structures, with average fiber diameters of approximately 1 µm on the outer and inner surfaces. Notably, these structures matched their intended design dimensions without distortion or shrinkage, demonstrating the adaptability of this method for various template sizes. The cylindrical structures showed high elasticity and stretchability with an elastic modulus of 6.23 MPa. Furthermore, our method successfully mimicked complex biological tissue structures, such as the inner architecture of the voice box and the hollow partitioned structure of the heart’s tricuspid valve. Achieving specific intricate shapes required multiple spinning sessions and subsequent assemblies. In essence, our approach holds potential for crafting artificial organs and forming the foundational materials for cell culture scaffolds, addressing the challenges of crafting intricate multiscale structures. Full article

In the production process of progressive die stamping, anomaly detection is essential for ensuring the safety of expensive dies and the continuous stability of the production process. Early monitoring processes involve manually inspecting the quality of post-production products to infer whether there are anomalies in the production process, or using some sensors to monitor some state signals during the production process. However, the former is an extremely tedious and time-consuming task, and the latter cannot provide warnings before anomalies occur. Both methods can only detect anomalies after they have occurred, which usually means that damage to the die has already been caused. In this paper, we propose a machine-vision-based method for real-time anomaly detection in the production of progressive die stamping. This method can detect anomalies before they cause actual damage to the mold, thereby stopping the machine and protecting the mold and machine. In the proposed method, a whole continuous motion scene cycle is decomposed into a standard background template library, and the potential anomaly regions in the image to be detected are determined according to the difference from the background template library. Finally, the shape- and size-adaptive descriptors of these regions and corresponding reference regions are extracted and compared to determine the actual anomaly regions. The experimental results indicate that this method can achieve reasonable accuracy in the detection of anomalies in the production process of stamping progressive dies. The experimental results demonstrate that this method not only achieves satisfactory accuracy in anomaly detection during the production of progressive die stamping, but also attains competitive performance levels when compared with methods based on deep learning. Furthermore, it requires simpler preliminary preparations and does not necessitate the adoption of the deep learning paradigm. Full article

Nanoporous anodic aluminum oxide (AAO) is an important template for 1D nanomaterial synthesis. It is used as an etching template for nanopattern transfer in a variety of contexts, including nanostructured material synthesis, electrical sensors, optical sensors, photonic and electronic devices, photocatalysis, and hardness and anticorrosion improvement. In this review, we focus on various fabrication methods, pore geometry modification, and recent advances of AAO, as well as sensor applications linked to our environment, daily life, and safety. Pore geometry is concerned with the material composition, applied voltage mold, electrolyte type, temperature, and anodizing time during the fabrication of AAOs and for adjusting their pore size and profile. The applied voltage can be divided into four types: direct current anodization (DCA), reverse pulse anodization, pulse anodization (PA), and hybrid pulse anodization (HPA). Conventional AAOs are fabricated using DCA and mild anodization (MA) at a relatively low temperature (−5~15 °C) to reduce the Joule heating effect. Moreover, the issues of costly high-purity aluminum and a long processing time can be improved using HPA to diminish the Joule heating effect at relatively high temperatures of 20–30 °C with cheap low-purity (≤99%) aluminum. The AAO-based sensors discussed here are primarily divided into electrical sensors and optical sensors; the performance of both sensors is affected by the sensing material and pore geometry. The electrical sensor is usually used for humidity or gas measurement applications and has a thin metal film on the surface as an electrode. On the contrary, the AAO optical sensor is a well-known sensor for detecting various substances with four kinds of mechanisms: interference, photoluminescence, surface plasma resonance, and surface-enhanced Raman scattering (SERS). Especially for SERS mechanisms, AAO can be used either as a solid support for coating metal nanoparticles or a template for depositing the metal content through the nanopores to form the nanodots or nanowires for detecting substances. High-performance sensors will play a crucial role in our living environments and promote our quality of life in the future. Full article

This systematic review was aimed at gathering the clinical and technical applications of CAD/CAM technology for craniofacial implant placement and processing of auricular prostheses based on clinical cases. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, an electronic data search was performed. Human clinical studies utilizing digital planning, designing, and printing systems for craniofacial implant placement and processing of auricular prostheses for prosthetic rehabilitation of auricular defects were included. Following a data search, a total of 36 clinical human studies were included, which were digitally planned and executed through various virtual software to rehabilitate auricular defects. Preoperative data were collected mainly through computed tomography scans (CT scans) (55 cases); meanwhile, the most common laser scanners were the 3dMDface System (3dMD LLC, Atlanta, Georgia, USA) (6 cases) and the 3 Shape scanner (3 Shape, Copenhagen, Denmark) (6 cases). The most common digital design software are Mimics Software (Mimics Innovation Suite, Materialize, Leuven, Belgium) (18 cases), Freeform software (Freeform, NC, USA) (13 cases), and 3 Shape software (3 Shape, Copenhagen, Denmark) (12 cases). Surgical templates were designed and utilized in 35 cases to place 88 craniofacial implants in auricular defect areas. The most common craniofacial implants were Vistafix craniofacial implants (Entific Medical Systems, Goteborg, Sweden) in 22 cases. A surgical navigation system was used to place 20 craniofacial implants in the mastoid bone. Digital applications of CAD/CAM technology include, but are not limited to, study models, mirrored replicas of intact ears, molds, retentive attachments, customized implants, substructures, and silicone prostheses. The included studies demonstrated a predictable clinical outcome, reduced the patient’s visits, and completed the prosthetic rehabilitation in reasonable time and at reasonable cost. However, equipment costs and trained technical staff were highlighted as possible limitations to the use of CAD/CAM systems. Full article

The aim of the present study was to determine the orbital reconstructive effect of customized orbital implants using three-dimensional (3D) printed templates compared with conventional manual-bending implants using computed tomography (CT)-based orbital volume measurements. This retrospective study reviewed the medical records and 3D-CT images of 90 patients who underwent medial, inferior, or inferomedial orbital wall reconstruction. The selected patients were categorized into two groups: (1) the 3D group that underwent surgery using 3D-printed customized orbital implant templates and (2) the manual group that received a conventional manual technique to mold the implant. The volume discrepancy (VD) was obtained by subtracting the volume of the contralateral unaffected eye from that of the injured eye. Of the 90 patients, 33 and 57 were divided into the 3D and manual groups, respectively. The volumes on the contralateral unaffected side and on the pre- and postoperative injured sides were 22.5 ± 2.9, 23.7 ± 3.0, and 22.3 ± 2.8 cm³ (mean ± SD), respectively, in the 3D group, and 21.5 ± 2.5, 22.7 ± 2.8, and 21.2 ± 2.7 cm³ in the manual group. The postoperative VD did not differ between the 3D (–0.2 ± 0.3 cm³) and manual (–0.3 ± 0.9 cm³) groups (p = 0.794). The volume on the postoperative injured side did not differ significantly from that on the contralateral unaffected side in the 3D group, but these did differ significantly in the manual group. Postoperative VD also increased with the preoperative VD in the manual group (Pearson correlation coefficient = 0.548, p = 0.001), whereas there was no such association in the 3D group. The orbital volume restoration effect had superior surgical outcomes for large fractures using the customized orbital implant with 3D-printed templates compared with manual-bending implants. Full article

The main motivation of this work was to demonstrate a hollow telescopic rod structure that could be used for minimally invasive surgery. The telescopic rods were fabricated using 3D printing technology to make mold flips. During fabrication, differences in biocompatibility, light transmission, and ultimate displacement were compared between telescopic rods fabricated via different processes, so as to select the appropriate process. To achieve these goals, flexible telescopic rod structures were designed and 3D-printed molds were fabricated using Fused Deposition Modeling (FDM) and Stereolithography (SLA) techniques. The results showed that the three molding processes had no impact on the doping of the PDMS specimens. However, the FDM molding process had lower surface flatness accuracy compared to SLA. The SLA mold flip fabrication exhibited superior surface accuracy and light transmission compared to the other methods. The sacrificial template method and the use of HTL direct demolding technique had no significant impact on cellular activity and biocompatibility, but the mechanical properties of the PDMS specimens were weakened after swelling recovery. The height and radius of the hollow rod were found to have a significant impact on the mechanical properties of the flexible hollow rod. The hyperelastic model was fitted appropriately with the mechanical test results, and the ultimate elongation increased with an increase in hollow–solid ratios under the uniform force. Full article

High Z (atomic number) metallic foams with a low density and high purity are urgent demands in high energy-density physical experiments. They suppress plasma expansion and convert the laser pulses to X-rays more uniformly and efficiently. Thus, we synthesized an ultralow-density and high-purity Au foam hohlraum with a hierarchical porous structure via a template-dealloying method in this paper. Silica (SiO₂) beads were introduced as the sacrificial templates due to their high stability at an elevated temperature. The Au and Ag nanoparticles were successively deposited onto the SiO₂ templates via an electroless deposition process to form an Ag@Au@SiO₂ core-shell structure. Cylindrical Ag@Au@SiO₂ hohlraum was achieved using a filter-casting technique with a patented mold. Afterward, an Au-Ag alloy was generated during 36 h of calcination at 400 °C. Self-supported Au foam hohlraum with the hierarchical porous structure was gained after the SiO₂ templates were removed, followed by the dealloying of the Ag from the Au-Ag alloy. A self-supporting Au foam hohlraum with a density as low as 0.2 g/cm³ and a purity of 99.37% was achieved, and the density decreased by about 44.5% when compared with our previous Au foam (density: 0.36 g/cm³, purity: less than 96%) using microspherical polystyrene as the sacrificial template. Thus, the ultralow-density, high-purity Au foam hohlraum may exhibit profound application in high-energy physical experiments in the near future. Full article

Thermoplastic molded regenerated silk fibroin was proposed as a structural material in tissue engineering applications, mainly for application in bone. The protocol allows us to obtain a compact non-porous material with a compression modulus in the order of a Giga Pascal in dry conditions (and in the order of tens of MPa in wet conditions). This material is produced by compressing a lyophilized silk fibroin powder or sponge into a mold temperature higher than the glass transition temperature. The main purpose of the produced resin was the osteofixation and other structural applications in which the lack of porosity was not an issue. In this work, we introduced the use of citric acid in the thermoplastic molding protocol of silk fibroin to obtain porosity inside the structural material. The citric acid powder during the compression acted as a template for the pore formation. The mean pore diameter achieved by the addition of the higher amount of citric acid was around 5 μm. In addition, citric acid could effectively crosslink the silk fibroin chain, improving its mechanical strength. This effect was proved both by evaluating the compression modulus (the highest value recorded was 77 MPa in wet conditions) and by studying the spectra obtained by Fourier transform infrared spectroscopy. This protocol may be applied in the near future to the production of structural bone scaffolds. Full article

Since 3D printing allows for patient-specific dosage forms, it has become a major focus in pharmaceutical research. However, it is difficult to scale up drug product manufacturing. Injection molding has been used in conjunction with hot-melt extrusion to mass produce drug products, but making tailored solid dosage forms with this technology is neither cost-effective nor simple. This study explored the use of a combination of fused filament fabrication and injection molding to create patient-specific solid dosage forms. A tablet fixation and location template was used to overprint directly on injection-molded tablet bases, and theophylline was combined with polycaprolactone and Kollidon^® VA64 via hot-melt extrusion to produce the filament. Dynamic mechanical analysis was used to evaluate the brittleness of the filament, and differential scanning calorimetry was used to analyze the thermal results. The results showed that theophylline had a flow promoting effect on the polymer blend and that overprinted tablets were manufactured faster than 3D-printed tablets. Drug release studies also showed that overprinted tablets released faster than injection-molded tablets. This method demonstrates the potential of hybrid manufacturing for the pharmaceutical industry as a means of bridging the gap between personalized dosage forms and mass production. Full article

Artificial intelligence technology has enabled the manufacturing industry and actively guided its transformation and promotion for the past few decades. Injection molding technology is a crucial procedure in mechanical engineering and manufacturing due to its adaptability and dimensional stability. An essential step in the injection molding process is quality inspection and manual visual inspection is still used in conventional quality control, but this open-loop working method has issues with subjectivity and real-time monitoring capacity. This paper proposes an integrated “processing–matching–classification–diagnosis” concept based on machine vision and deep learning that allows for efficient and intelligent diagnosis of injection molding in complex scenarios. Based on eight categories of failure images of plastic components, this paper summarizes the theoretical method of processing fault categorization and identifies the various causes of defects from injection machines and molds. A template matching mechanism based on a new concept—arbitration function $J\left({\psi }_{ij}\right)$—provided in this paper, matches the edge features to achieve the initial classification of plastic components images. A conventional VGG16 network is innovatively upgraded in this work in order to further classify the unqualified plastic components. The classification accuracy of this improved VGG16 reaches 96.67%, which is better than the 53.33% of the traditional network. The accuracy, responsiveness, and resilience of the quality inspection are all improved in this paper. This work enhances production safety while promoting automation and intelligence of fault diagnosis in injection molding systems. Similar technical routes can be generalized to other industrial scenarios for quality inspection problems. Full article

As the foremost component of wearable devices, flexible pressure sensors require high sensitivity, wide operating ranges, and great stability. In this paper, a pressure sensor comprising a regular batten microstructure active layer is presented. First, the influences of the dimensional parameters of the microstructures on the performances of the sensors were investigated by the mechanical finite element method (FEM). Then, parameters were optimized and determined based on the results of this investigation. Next, active layers were prepared by molding multiwalled carbon nanotube/polyurethane (MWCNT/PU) conductive composite using a printed circuit board template. Finally, a resistive flexible pressure sensor was fabricated by combining an active layer and an interdigital electrode. With advantages in terms of the structure and materials, the sensor exhibited a sensitivity of up to 46.66 kPa⁻¹ in the range of 0–1.5 kPa and up to 6.67 kPa⁻¹ in the range of 1.5–7.5 kPa. The results of the experiments show that the designed flexible pressure sensor can accurately measure small pressures and realize real-time human physiological monitoring. Furthermore, the preparation method has the advantages of a low cost, simple design, and high consistency. Thus, it has potential to promote the development of flexible sensors, wearable devices, and other related devices. Full article