3D Printing for Polymer Science Visualization

Open Access

Year : 2024 | Volume :12 | Special Issue : 04 | Page : 96-101
By

Princy Tyagi,

  1. Assistant Professor, Computer Science & Engineering, Swami Rama Himalayan University Dehradun,, uttarakhand, India

Abstract

The burgeoning field of 3D printing offers exciting possibilities for various scientific disciplines. This paper explores the potential integration of 3D printing technology within the realm of polymer analysis. While the core focus of memory forensics investigations lies in digital forensics, the concept of 3D printing complex data structures presents intriguing possibilities for the visualization and communication of findings in polymer science. Here, we propose a future research avenue where 3D printing could be employed to create physical representations of intricate polymeric structures derived from analytical techniques. This could revolutionize the communication of complex polymer morphologies, enhancing collaborative research efforts and potentially leading to advancements in polymer design and characterization. The information technology landscape is undergoing a period of explosive growth. Data processing capabilities have surged in both speed and accuracy, while storage capacities have ballooned, allowing for the easy accumulation of vast troves of digital information. This accessibility, however, presents a double-edged sword. While it facilitates information sharing and analysis, it also creates tempting opportunities for criminal activity. Sensitive data, like passwords and credit card PINs, becomes a target for malicious actors. As a result, the onus falls on security professionals to safeguard this critical information. This review will explore the various tools and techniques available for conducting memory forensics investigations on Windows systems. We will examine both open-source and commercial solutions, evaluating their strengths and limitations. Furthermore, the paper will discuss the potential of integrating 3D printing technology into the digital forensics’ workflow. By creating physical representations of complex data structures extracted from memory, 3D printing could potentially enhance the visualization and communication of forensic findings. Finally, the paper will conclude by proposing avenues for future research in the field of memory forensics. This includes exploring the integration of artificial intelligence and machine learning for automating memory analysis tasks, as well as investigating the feasibility of using advanced memory acquisition techniques for real-time incident response. By fostering innovation in these areas, we can empower digital forensic investigators to more effectively combat cybercrime and safeguard sensitive data.

Keywords: Polymer, Memory forensics, Computer Forensics, Chemical imaging. 3D Printing.

[This article belongs to Special Issue under section in Journal of Polymer and Composites (jopc)]

How to cite this article:
Princy Tyagi. 3D Printing for Polymer Science Visualization. Journal of Polymer and Composites. 2024; 12(04):96-101.
How to cite this URL:
Princy Tyagi. 3D Printing for Polymer Science Visualization. Journal of Polymer and Composites. 2024; 12(04):96-101. Available from: https://journals.stmjournals.com/jopc/article=2024/view=171684


Browse Figures

References

  1. Ankam AK. Implementation of a Windows Tool to Conduct Live Forensics Acquisition in Windows Systems. Diss. Texas A&M University. 2012.
  2. Wagner J, Rasin A, Grier J. Database forensic analysis through internal structure carving. Digital Investigation. 2015 Aug 1;14:S106-15.
  3. Zhao Q, Cao T. Collecting Sensitive Information from Windows Physical Memory. J. Comput.. 2009 Jan 1;4(1):3-10.
  4. Schuster A. Searching for processes and threads in Microsoft Windows memory dumps. digital investigation. 2006 Sep 1;3:10-6.
  5. Mann HK, Chhabra GS. Volatile memory forensics: a legal perspective. International Journal of Computer Applications. 2016;155(3):11-5.
  6. Prakash V, Williams A, Garg L, Savaglio C, Bawa S. Cloud and edge computing-based computer forensics: Challenges and open problems. Electronics. 2021 May 21;10(11):1229.
  7. Hejazi SM, Talhi C, Debbabi M. Extraction of forensically sensitive information from windows physical memory. digital investigation. 2009 Sep 1;6:S121-31.
  8. Skadron K, Ahuja PS, Martonosi M, Clark DW. Improving prediction for procedure returns with return-address-stack repair mechanisms. InProceedings. 31st Annual ACM/IEEE International Symposium on Microarchitecture 1998 Dec 2 (pp. 259-271). IEEE.
  9. Hausknecht K, Foit D, Burić J. RAM data significance in digital forensics. In2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) 2015 May 25 (pp. 1372-1375). IEEE.
  10. Eoghan C. Tool review–Winhex Digital Investigation. Issue. 2004;2:114-28.
  11. Hausknecht K, Foit D, Burić J. RAM data significance in digital forensics. In2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) 2015 May 25 (pp. 1372-1375). IEEE.
  12. Vázquez JA, Casteleiro-Roca JL, Jove E, Zayas-Gato F, Quintián H, Calvo-Rolle JL. Data collection description for evaluation and analysis of engineering students’ academic performance. InInternational Conference on EUropean Transnational Education 2020 Aug 15 (pp. 317-328). Cham: Springer International Publishing.
  13. Kechagias JD, Ninikas K, Vakouftsi F, Fountas NA, Palanisamy S, Vaxevanidis NM. Optimization of laser beam parameters during processing of ASA 3D-printed plates. The International Journal of Advanced Manufacturing Technology. 2024 Jan;130(1):527-39.

Special Issue Open Access Review Article
Volume 12
Special Issue 04
Received March 1, 2024
Accepted July 16, 2024
Published July 18, 2024

Check Our other Platform for Workshops in the field of AI, Biotechnology & Nanotechnology.
Check Out Platform for Webinars in the field of AI, Biotech. & Nanotech.