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    <identifier>10.57760/sciencedb.012an</identifier>
    <datestamp>2026-09-10T14:50:23Z</datestamp>
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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:date>2026-09-10</dc:date>
  <dc:title>Research Progress on Tribological Properties of Laser-Textured Solid/Liquid Self-Lubricating Surfaces</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.012an</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Laser surface texturing (LST), an advanced surface engineering technique that integrates bio-inspired design with high-performance lubricants, has emerged as a promising strategy with significant research interest and practical applications in tribology. It enables precise fabrication of micro/nano-scale structures with tailored geometry, dimensions, and spatial distribution on material surfaces, substantially enhancing lubrication performance and wear resistance of friction pairs. This review systematically examines the processing mechanisms of LST, the effects of key texturing parameters&amp;mdash;such as area density, geometric morphology, size, and depth&amp;mdash;on tribological behavior, and the synergistic roles of textured coatings (e.g., metal-based, sulfide-based, and organic/inorganic composites) under various lubrication regimes. Studies show that rational texture design can enhance hydrodynamic lift, promote lubricant film formation, and trap wear debris, leading to significant reductions in friction coefficient and wear rate. Furthermore, this article summarizes the application outcomes of texture design in engineering materials, offering theoretical insights and technical guidance for the development of high-performance tribological systems.</dc:description>
  <dc:subject>laser texturing; laser parameters; lubricating surface; micro-nano structure; frictional properties</dc:subject>
  <dc:creator>Ji Xinyuan</dc:creator>
  <dc:creator>Zhang Yuankang</dc:creator>
  <dc:creator>Hou Yuanyuan</dc:creator>
  <dc:creator>Ba Zhaowen</dc:creator>
  <dc:creator>Wu Yongling</dc:creator>
  <dc:creator>Liu Mingming</dc:creator>
  <dc:creator>Guo Zhiguang</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.16078/j.tribology.2025144</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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