iTSSe TSS ADVANCED MATERIALS & PROCESSES | APRIL 2024 41 iTSSe TSS ANTIVIRAL AND ANTIBACTERIAL COLD SPRAY COATING APPLICATION ON RUBBER SUBSTRATE, DISRUPTION IN DISEASE TRANSMISSION CHAIN Dulal C. Saha, Scott J. Boegel, Shazia Tanvir, Christiane L. Nogueira, Marc G. Aucoin, William A. Anderson, and Hamid Jahed The objective of this study was to prepare a copper- coated rubber surface using cold spray technology with improved virucidal and antimicrobial properties to fight against highly transmissible viruses and bacteria. A successful cold spray coating was produced using irregular-shaped pure Cu powder on an escalator handrail rubber. The powder particles and the deposited coatings (single and double pass) were characterized in terms of particle morphology and size distribution, coating surface, and coat/ substrate cross-section properties. (Fig. 1) The Journal of Thermal Spray Technology (JTST), the official journal of the ASM Thermal Spray Society, publishes contributions on all aspects— fundamental and practical— of thermal spray science, including processes, feedstock manufacture, testing, and characterization. As the primary vehicle for thermal spray information transfer, its mission is to synergize the rapidly advancing thermal spray industry and related industries by presenting research and development efforts leading to advancements in implementable engineering applications of the technology. The following JTST papers are among the 2023 Editor’s Choice selections from Editor-in-Chief André McDonald and are now free to access. In addition to the print publication, JTST is available online through springerlink.com. For more information, visit asminternational.org/tss. Fig. 1 — EDX mapping for Cu distribution on coating surfaces, double pass. JTST HIGHLIGHTS 12 Fig. 2 — Synthetic image generated by the GAN (generative adversarial network). ARTIFICIAL INTELLIGENCE MODELS FOR ANALYZING THERMALLY SPRAYED FUNCTIONAL COATINGS Parth Mahendru, Moussa Tembely, and Ali Dolatabadi Characterizing thermally sprayed coatings remains challenging due to the interplay between different operating and process parameters. Currently, no general framework exists for accurately predicting the coating characteristics under specific operating conditions. In this paper, artificial intelligence models were employed to investigate a case study of generating superhydrophobic coatings by suspension plasma spray (SPS), an emerging thermal spray process that can produce coatings with micro and nano-scale features. (Fig. 2)
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