Pradhan A, Müser M H, Miller N, Abdelnabe J P, Afferrante L, Albertini D, Aldave D A, Algieri L, Ali N, Almqvist A, Amann T, Ares P, Balzer B N, Baugh L, Berberich E A, Björling M, Bobji M S, Bottiglione F, Brodmann B, Cai W, Carbone G, Carpick R W, Cassin F, Cayer-Barrioz J, Chowdhury M I, Ciavarella M, Cihan E, Huang D, Delplanque E, Deptula A J, Descartes S, Dhinojwala A, Dienwiebel M, Dini D, Dunn A C, Edwards C, Eriten M, Esawi A, Espinosa-Marzal R M, Fang L, Fatemi A, Fidd C, Gabriel D, Gaslain F, Giordano G, Gómez-Herrero J, Gontard L, Gosvami N N, Greenwood G, Greiner C, Grejtak T, Haroun A, Hasan M, Hoppe S, Isa L, Jackson R L, Jang S, Johnson O, Kaiser F, Kalin M, Kalliorinne K, Karanjkar P H, Kim S H, Kinzelberger S, Klapetek P, Krick B A, Kumar C, Kumar N, Kumar S, LaMascus P, Larsson R, Laux P, Lee M J, Lee P M, Lee W, Leriche C, Li J, Li Y, Li Y-S, Lubrecht T A, Lyashenko I A, Ma C, Ma T, Maaboudallah F, Mahmood S, Mangolini F, Marian M, Mazuyer D, Meng Y, Menga N, Miller T, Mulvihill D M, Najah M, Nečas D, Papadopoulos C I, Papangelo A, Pauli M, Persson B N J, Peterson A, Pitenis A A, Podsiadlo P, Polajnar M, Popov V L, Požar T, Prasad A, Prieto G, Putignano C, Rahman M H, Ramisetti S B, Raumel S, Reyes I J, Rodriguez N, Rodríguez Ripoll M, Rojacz H, Sainsot P, Samodurova A, Savio D, Scaraggi M, Schaefer F, Scherrer S W, Schulze K D, Shaffer K E, Sidebottom M A, Skaltsas D, Soni J, Spies C, Stachowiak G W, Steinhoff L, Strandwitz N C, Sun K, Tripathi S, Tuckart W R, Ugar S, Valtr M, Van Meter K E, Vdovak J, Vilhena J G, Violano G, Vorlaufer G, Walczak M, Weber B, Woloszynski T, Wolski M, Yadav A, Yastrebov V A, Yongjian M, Yuan L, Yus J, Zhang J, Zhang X, Zheng Q, Pastewka L, Jacobs T D B
Department of Mechanical Engineering and Materials Science, University of Pittsburgh, 3700 O'Hara St., Pittsburgh, PA 15261 USA.
Department of Materials Science and Engineering, Saarland University, Campus C6 3, 66123 Saarbrücken, Germany.
Tribol Lett. 2025;73(3):110. doi: 10.1007/s11249-025-02014-y. Epub 2025 Jul 26.
Surface performance is critically influenced by topography in virtually all real-world applications. The current standard practice is to describe topography using one of a few industry-standard parameters. The most commonly reported number is a, the average absolute deviation of the height from the mean line (at some, not necessarily known or specified, lateral length scale). However, other parameters, particularly those that are scale-dependent, influence surface and interfacial properties; for example the local surface slope is critical for visual appearance, friction, and wear. The present Surface-Topography Challenge was launched to raise awareness for the need of a multi-scale description, but also to assess the reliability of different metrology techniques. In the resulting international collaborative effort, 153 scientists and engineers from 64 research groups and companies across 20 countries characterized statistically equivalent samples from two different surfaces: a "rough" and a "smooth" surface. The results of the 2088 measurements constitute the most comprehensive surface description ever compiled. We find wide disagreement across measurements and techniques when the lateral scale of the measurement is ignored. Consensus is established through scale-dependent parameters while removing data that violates an established resolution criterion and deviates from the majority measurements at each length scale. Our findings suggest best practices for characterizing and specifying topography. The public release of the accumulated data and presented analyses enables global reuse for further scientific investigation and benchmarking.
The online version contains supplementary material available at 10.1007/s11249-025-02014-y.
在几乎所有实际应用中，表面性能都受到形貌的严重影响。当前的标准做法是使用一些行业标准参数之一来描述形貌。最常报告的数值是a，即高度相对于平均线的平均绝对偏差（在某个不一定已知或指定的横向长度尺度下）。然而，其他参数，特别是那些与尺度相关的参数，会影响表面和界面特性；例如，局部表面斜率对视觉外观、摩擦和磨损至关重要。发起当前的表面形貌挑战，旨在提高人们对多尺度描述需求的认识，同时评估不同计量技术的可靠性。在由此产生的国际合作努力中，来自20个国家的64个研究小组和公司的153名科学家和工程师对来自两个不同表面（一个“粗糙”表面和一个“光滑”表面）的统计等效样本进行了表征。2088次测量的结果构成了有史以来编制的最全面的表面描述。当忽略测量的横向尺度时，我们发现不同测量和技术之间存在广泛分歧。通过依赖尺度的参数建立共识，同时去除违反既定分辨率标准且在每个长度尺度上偏离多数测量的数据。我们的研究结果提出了表征和指定形貌的最佳实践方法。累积数据和所呈现分析的公开发布使得全球能够重新使用这些数据，以进行进一步的科学研究和基准测试。
在线版本包含可在10.1007/s11249-025-02014-y获取的补充材料。
