Cho In Ho, Ji Myung Gi, Kim Jaeyoun
Department of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA, 50011, USA.
Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, 50011, USA.
Sci Rep. 2023 Aug 22;13(1):13649. doi: 10.1038/s41598-023-41022-7.
Nature finds a way to leverage nanotextures to achieve desired functions. Recent advances in nanotechnologies endow fascinating multi-functionalities to nanotextures by modulating the nanopixel's height. But nanoscale height control is a daunting task involving chemical and/or physical processes. As a facile, cost-effective, and potentially scalable remedy, the nanoscale capillary force lithography (CFL) receives notable attention. The key enabler is optical pre-modification of photopolymer's characteristics via ultraviolet (UV) exposure. Still, the underlying physics of the nanoscale CFL is not well understood, and unexplained phenomena such as the "forbidden gap" in the nano capillary rise (unreachable height) abound. Due to the lack of large data, small length scales, and the absence of first principles, direct adoptions of machine learning or analytical approaches have been difficult. This paper proposes a hybrid intelligence approach in which both artificial and human intelligence coherently work together to unravel the hidden rules with small data. Our results show promising performance in identifying transparent, physics-retained rules of air diffusivity, dynamic viscosity, and surface tension, which collectively appear to explain the forbidden gap in the nanoscale CFL. This paper promotes synergistic collaborations of humans and AI for advancing nanotechnology and beyond.
大自然总能找到利用纳米纹理来实现所需功能的方法。纳米技术的最新进展通过调节纳米像素的高度，赋予了纳米纹理迷人的多功能性。但纳米级高度控制是一项艰巨的任务，涉及化学和/或物理过程。作为一种简便、经济高效且具有潜在可扩展性的解决方法，纳米级毛细力光刻（CFL）受到了显著关注。关键促成因素是通过紫外线（UV）曝光对光聚合物特性进行光学预改性。然而，纳米级CFL的潜在物理原理尚未得到很好的理解，并且存在许多无法解释的现象，例如纳米毛细管上升中的“禁带”（无法达到的高度）。由于缺乏大数据、小长度尺度以及第一性原理，直接采用机器学习或分析方法一直很困难。本文提出了一种混合智能方法，其中人工智能和人类智能协同工作，以从小数据中揭示隐藏的规则。我们的结果表明，在识别透明的、保留物理特性的空气扩散率、动态粘度和表面张力规则方面具有良好的性能，这些规则似乎共同解释了纳米级CFL中的禁带。本文促进了人类与人工智能的协同合作，以推动纳米技术及其他领域的发展。
