Daniel Olds
Physicist & HRD Beamline Lead Scientist, Hard X-Ray Methods Program, National Synchrotron Light Source II
Brookhaven National Laboratory
National Synchrotron Light Source II
Bldg. 741
P.O. Box 5000
Upton, NY 11973-5000
(631) 344-6133
dolds@bnl.gov
Pronouns: he, him, his
Daniel Olds is a physicist at NSLS-II and the lead scientist of the High Resolution Diffraction (HRD) beamline, where he brings together advanced synchrotron science with groundbreaking AI innovations. He develops and implements advanced computational methods to automate beamline operations and streamline data analysis, transforming traditional experiments into dynamic, real-time discovery engines. By integrating cutting-edge AI solutions with state-of-the-art X-ray diffraction techniques, he is unlocking unprecedented insights into the atomic realm and driving breakthrough innovations that captivate the scientific community and beyond.
Expertise | Research | Education | Appointments | Publications | Awards | Video
Expertise
Daniel's expertise spans the dynamic intersection of condensed matter physics, chemistry, materials science, and artificial intelligence. He works with a diverse set of user groups on a wide range of scientific challenges, supporting them both at the beamlines and in their data analysis. He has expertise in powder diffraction and Pair-Distribution Function (PDF) methods, successfully integrating AI into beamline operations to revolutionize data acquisition and analysis. From pioneering autonomous experiment control—including real-time AI-driven control of multiple beamlines simultaneously—to developing methods that swiftly interpret complex diffraction data, his work drives innovation and transformative advances in the field.
Research Activities
AI/ML's Bright Future at NSLS-II
NEXT-III at NSLS-II: A New Approach to Beamline Design and Development
Using Reinforcement Learning to Gamify the Beamlines
Development of a Crystallography Companion AI for High-Throughput Materials Discovery
Advancing Discovery with Artificial Intelligence and Machine Learning at NSLS-II
Education
Ph.D. in Physics, Michigan State University, 2013
M.S. in Physics, Michigan State University, 2008
B.S. in Physics, Michigan State University, 2005
Professional Appointments
2024 - Present HRD Lead Beamline Scientist, Brookhaven National Laboartory
2018 - 2024 PDF Beamline Scientist, Brookhaven National Laboratory
2015 - 2018 Postdoctoral Researcher, Oak Ridge National Laboratory
2013 - 2015 Postdoctoral Researcher, Los Alamos National Laboratory
Selected Publications
- Maffettone PM, Lynch JK, Caswell TA, Cook CE, Campbell SI, Olds D (2021) Gaming the beamlines—employing reinforcement learning to maximize scientific outcomes at large-scale user facilities. Machine Learning: Science and Technology 2:025025. doi: 10.1088/2632-2153/abc9fc
- Maffettone PM, Campbell S, Hanwell MD, et al (2022) Delivering real-time multi-modal materials analysis with enterprise beamlines. Cell Reports Physical Science 3:101112. https://doi.org/10.1016/j.xcrp.2022.101112
- Maffettone PM, Banko L, Cui P, Lysogorskiy Y, Little MA, Olds D, Ludwig A, Cooper AI (2021) Crystallography companion agent for high-throughput materials discovery. Nature Computational Science 1:290–297. doi: 10.1038/s43588-021-00059-2
- Campbell SI, Allan DB, Barbour AM, Olds D, Rakitin MS, Smith R, Wilkins SB (2021) Outlook for artificial intelligence and machine learning at the NSLS-II. Machine Learning: Science and Technology 2:013001. doi: 10.1088/2632-2153/abbd4e
- Olds D, Lawler KV, Paecklar AA, Liu J, Page K, Peterson PF, Forster PM, Neilson JR (2017) Capturing the Details of N2 Adsorption in Zeolite X Using Stroboscopic Isotope Contrasted Neutron Total Scattering. Chemistry of Materials 30:296–302. doi: 10.1021/acs.chemmater.7b04594
- Olds D, Saunders CN, Peters M, Proffen T, Neuefeind J, Page K (2018) Precise implications for real-space pair distribution function modeling of effects intrinsic to modern time-of-flight neutron diffractometers. Acta Crystallographica Section A Foundations and Advances 74:293–307. doi: 10.1107/s2053273318003224
- Liu J, Olds D, Peng R, Yu L, Foo GS, Qian S, Keum J, Guiton BS, Wu Z, Page K (2017) Quantitative Analysis of the Morphology of {101} and {001} Faceted Anatase TiO2 Nanocrystals and Its Implication on Photocatalytic Activity. Chemistry of Materials 29:5591–5604. doi: 10.1021/acs.chemmater.7b01172
- Fabini DH, Siaw TA, Stoumpos CC, Laurita G, Olds D, Page K, Hu JG, Kanatzidis MG, Han S, Seshadri R (2017) Universal Dynamics of Molecular Reorientation in Hybrid Lead Iodide Perovskites. Journal of the American Chemical Society 139:16875–16884. doi: 10.1021/jacs.7b09536
Awards & Recognition
President of the Pittsburgh Diffraction Society
Chair of the Powder Diffraction Special Interest Group (SIG) of the American Crystallography Association
Recipient of Etter Student Award from Neutron Scientific Interest Group at the 2017 American Crystallographic Association Meeting for “Improving the accuracy of time of flight neutron total scattering data analysis” – New Orleans (LA)
Poster Prize Awarded at RMCProfile School for “DShaper - A program to efficiently handle 2016 the effects of missing low-Q data in pair distribution function analysis of nanostructured systems” – Oak Ridge (TN)
Featured Video
Meet your New Lab Partner: AI
January 9, 2025
Daniel Olds, a beamline scientist at Brookhaven Lab, discusses how beamlines at the National Synchrotron Light Source II (NSLS-II) can communicate back and forth without human interaction. In this installment of NSLS-II Science Shorts, learn how artificial intelligence drives experiments and analyzes results while controlling multiple beamlines simultaneously.
A short talk of mine presenting how beamlines at the National Synchrotron Light Source II (NSLS-II) can use artificial intelligence (AI) to drive experiments and analyzes results while controlling multiple beamlines simultaneously.
Brookhaven National Laboratory
National Synchrotron Light Source II
Bldg. 741
P.O. Box 5000
Upton, NY 11973-5000
(631) 344-6133
dolds@bnl.gov
