Dataset Information

Effect of Deep Cryogenic Treatment on Wear and Galling Properties of High-Speed Steels.

ABSTRACT: New approaches to improving wear resistance with an affordable and noncomplex technology, such as deep cryogenic treatment, (DCT0), are receiving attention. The aim of this study is to investigate the effect of DCT on the friction and wear performance of high-speed steels. AISI M2, AISI M3:2 and AISI M35 were heat-treated under different conditions, and then investigated under dry sliding conditions. Tribological testing involved different contact conditions, prevailing wear mechanisms and loading conditions. The DCT effect on sliding wear resistance depends on HSS steel grade, as well as contact conditions and wear mode, whereas it improves the dynamic impact of the wear and galling resistance.

SUBMITTER: Jovicevic-Klug P

PROVIDER: S-EPMC8705678 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Effect of Deep Cryogenic Treatment on Wear and Galling Properties of High-Speed Steels.

Jovičević-Klug Patricia P Sedlaček Marko M Jovičević-Klug Matic M Podgornik Bojan B

Materials (Basel, Switzerland) 20211209 24

New approaches to improving wear resistance with an affordable and noncomplex technology, such as deep cryogenic treatment, (DCT0), are receiving attention. The aim of this study is to investigate the effect of DCT on the friction and wear performance of high-speed steels. AISI M2, AISI M3:2 and AISI M35 were heat-treated under different conditions, and then investigated under dry sliding conditions. Tribological testing involved different contact conditions, prevailing wear mechanisms and loadi ...[more]

PMID: 34947156

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Project description:Background and objectivePortable confocal microscopy (PCM) is a low-cost reflectance confocal microscopy technique that can visualize cellular details of human skin in vivo. When PCM images are acquired with a short exposure time to reduce motion blur and enable real-time 3D imaging, the signal-to-noise ratio (SNR) is decreased significantly, which poses challenges in reliably analyzing cellular features. In this paper, we evaluated deep learning (DL)-based approach for reducing noise in PCM images acquired with a short exposure time.Study design/materials and methodsContent-aware image restoration (CARE) network was trained with pairs of low-SNR input and high-SNR ground truth PCM images obtained from 309 distinctive regions of interest (ROIs). Low-SNR input images were acquired from human skin in vivo at the imaging speed of 180 frames/second. The high-SNR ground truth images were generated by registering 30 low-SNR input images obtained from the same ROI and summing them. The CARE network was trained using the Google Colaboratory Pro platform. The denoising performance of the trained CARE network was quantitatively and qualitatively evaluated by using image pairs from 45 unseen ROIs.ResultsCARE denoising improved the image quality significantly, increasing similarity with the ground truth image by 1.9 times, reducing noise by 2.35 times, and increasing SNR by 7.4 dB. Banding noise, prominent in input images, was significantly reduced in CARE denoised images. CARE denoising provided quantitatively and qualitatively better noise reduction than non-DL filtering methods. Qualitative image assessment by three confocal readers showed that CARE denoised images exhibited negligible noise more often than input images and non-DL filtered images.ConclusionsResults showed the potential of using a DL-based method for denoising PCM images obtained at a high imaging speed. The DL-based denoising method needs to be further trained and tested for PCM images obtained from disease-suspicious skin lesions.

Dataset Information

Effect of Deep Cryogenic Treatment on Wear and Galling Properties of High-Speed Steels.

Publications

Effect of Deep Cryogenic Treatment on Wear and Galling Properties of High-Speed Steels.

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