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Polymers
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Advances in Injection Molding and Polymers Processing
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Advances in Injection Molding and Polymers Processing

A special issue of Polymers (ISSN 2073-4360). This special issue belongs to the section "Polymer Processing and Engineering".

Deadline for manuscript submissions: closed (15 October 2024) | Viewed by 1778

Special Issue Editor

Dr. Lu Zhang

E-Mail Website
Guest Editor
1. College of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China
2. State Key Laboratory of Precision Manufacturing for Extreme Service Performance, Changsha 410083, China
Interests: polymer processing; micro- and nano-manufacturing; flame-retardant polymers
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Injection molding, a versatile process that allows for the mass production of complex components, has long been a cornerstone of the plastics industry. Injection-molded products are widely used in our daily lives, especially in fields like automotive, mobile phones, and household appliances. In recent research, variable new processes have emerged to enable injection-molded products with unique functions or high performances, like micro-/nano-injection molding, intelligent injection molding, ultrasonic-/air-/fluid-assisted plasticization and molding, etc. In addition, the emerging of novel materials like lightweight, green, and engineering plastics and fiber-reinforced plastics also drives innovations in mold design and molding processes. Besides, sensors and actuators, engineering simulations, and artificial intelligence are also essential to help understand the filling of the cooling steps as well as to enhance the quality and efficiency of the injection molding process.

The aim of this Special Issue is to present the latest research on “Recent Developments in Polymer Injection Molding”. We invite researchers to contribute to this Special Issue by submitting related articles and review papers.

Dr. Lu Zhang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Polymers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • precise injection molding
  • mold design and simulation
  • intelligent injection molding
  • ultrasonic-/air-/fluid-assisted injection molding
  • injection molding with fiber-reinforced plastics
  • lightweight/green/engineering plastics
  • process optimization

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Published Papers (1 paper)

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Research

21 pages, 4067 KiB  
Article
Enhancing Brain–Computer Interfaces through Kriging-Based Fusion of Sparse Regression Partial Differential Equations to Counter Injection Molding View of Node Displacement Effects
by Hanjui Chang, Yue Sun, Shuzhou Lu and Yuntao Lan
Polymers 2024, 16(17), 2507; https://doi.org/10.3390/polym16172507 - 3 Sep 2024
Viewed by 1216
Abstract
Injection molding is an efficient and precise manufacturing technology that is widely used in the production of plastic products. In recent years, injection molding technology has made significant progress, especially with the combination of in-mold electronics (IME) technology, which makes it possible to [...] Read more.
Injection molding is an efficient and precise manufacturing technology that is widely used in the production of plastic products. In recent years, injection molding technology has made significant progress, especially with the combination of in-mold electronics (IME) technology, which makes it possible to embed electronic components directly into the surface of a product. IME technology improves the integration and performance of a product by embedding conductive materials and functional components in the mold. Brain–computer interfaces (BCIs) are a rapidly growing field of research that aims to capture, analyze, and feedback brain signals by directly connecting the brain to external devices. The Utah array, a high-density microelectrode array, has been widely used for the recording and transmission of brain signals. However, the traditional fabrication method of the Utah array suffers from high cost and low integration, which limits its promotion in practical applications. The lines that receive EEG signals are one of the key parts of a brain–computer interface system. The optimization of injection molding parameters is particularly important in order to effectively embed these lines into thin films and to ensure the precise displacement of the line nodes and the stability of signal transmission during the injection molding process. In this study, a method based on the Kriging prediction model and sparse regression partial differential equations (PDEs) is proposed to optimize the key parameters in the injection molding process. This method can effectively predict and control the displacement of nodes in the film, ensure the stability and reliability of the line during the injection process, and improve the accuracy of EEG signal transmission and system performance. The optimal injection parameters were finally obtained: a holding pressure of 525 MPa, a holding time of 50 s, and a melting temperature of 285 °C. Under this condition, the average node displacement of UA was reduced from the initial 0.19 mm to 0.89 µm, with an optimization rate of 95.32%. Full article
(This article belongs to the Special Issue Advances in Injection Molding and Polymers Processing)
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