Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments

Journal Article · Tue Oct 14 00:00:00 UTC 2025 · ACS Nanoscience Au

DOI: https://doi.org/10.1021/acsnanoscienceau.5c00106 · OSTI ID:3019781

Bulanadi, Ralph ^[1]; Chowdhury, Jawad ^[1]; Funakubo, Hiroshi  ^[2]; Ziatdinov, Maxim ^[3]; Vasudevan, Rama  ^[1]; Biswas, Arpan ^[4]; Liu, Yongtao  ^[1]

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1. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
2. Institute of Science Tokyo, Yokohama (Japan)
3. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
4. University of Tennessee, Knoxville, TN (United States)

Autonomous experiments (AEs) are transforming how scientific research is conducted by integrating artificial intelligence with automated experimental platforms. Current AEs primarily focus on the optimization of a predefined target; while accelerating this goal, such an approach limits the discovery of unexpected or unknown physical phenomena. Here, we introduce a novel framework, INS²ANE (Integrated Novelty Score−Strategic Autonomous Non-Smooth Exploration), to enhance the discovery of novel phenomena in autonomous microscopy experimentation. Our method integrates two key components: (1) a novelty scoring system that evaluates the uniqueness of experimental results and (2) a strategic sampling mechanism that promotes exploration of under-sampled regions even if they appear less promising by conventional criteria. We validate this approach on a preacquired data set with a known ground truth comprising of image−spectral pairs. We further implement the process on autonomous scanning probe microscopy experiments. INS²ANE significantly increases the diversity of explored phenomena in comparison to conventional optimization routines, enhancing the likelihood of discovering previously unobserved phenomena. These results demonstrate the potential for autonomous microscopy experiments to enhance the scientific discovery by navigating complex experimental spaces to uncover novel phenomena.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: Japan Science and Technology Agency (JST); MEXT; National Science Foundation (NSF); USDOE; USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF)
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 3019781
• Journal Information: ACS Nanoscience Au, Journal Name: ACS Nanoscience Au Journal Issue: 1 Vol. 6; ISSN 2694-2496
• Publisher: American Chemical Society (ACS)Copyright Statement
• Country of Publication: United States
• Language: English