General Lab Information

Daniel Olds

Associate Physicist & PDF Beamline Scientist, Hard X-ray Scattering and Spectroscopy, National Synchrotron Light Source II

Daniel Olds

Brookhaven National Laboratory

National Synchrotron Light Source II
Bldg. 741
P.O. Box 5000
Upton, NY 11973-5000

(631) 344-6133
dolds@bnl.gov

Preferred Gender Pronouns (PGPs): he, him, his

My research focus lies in combining powder diffraction techniques with in situ studies of complex materials to discover the underlying atomic origins of the relevant material properties such as reaction pathways, synthesis, decomposition mechanisms, phase-transitions, and material passivation/poisoning. I approach these challenging scientific problems with expertise in three areas: detail-oriented design of advanced sample environments optimized for total scattering methods, experience with a wide variety of scattering analysis tools, including custom data reduction and analysis routines utilizing machine learning and AI methods.

Expertise | Research | Education | Publications | Awards | Video


Expertise

Total Scattering, PDF, Diffraction, Artificial Intelligence, Machine Learning, Reinforcement Learning

Research Activities

Using Reinforcement Learning to Gamify the Beamlines

Development of a Crystallography Companion AI for High-Throughput Materials Discovery

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
 

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, 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
  • Olds D, Wang H-W, Page K (2015) DShaper: an approach for handling missing low-Qdata in pair distribution function analysis of nanostructured systems. Journal of Applied Crystallography 48:1651–1659. doi: 10.1107/s1600576715016581
  • 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
  • Peys A, White CE, Olds D, Rahier H, Blanpain B, Pontikes Y (2018) Molecular structure of CaO–FeO x –SiO 2 glassy slags and resultant inorganic polymer binders. Journal of the American Ceramic Society 101:5846–5857. doi: 10.1111/jace.15880
  • 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

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

  • I am doing science that is more important than my sleep!

    January 12, 2022

    Dan Olds is an associate physicist at Brookhaven National Laboratory where he works as a beamline scientist at NSLS-II. Dan’s research involves combining artificial intelligence and machine learning to perform real-time analysis on streaming data while beamline experiments are being performed. Often these new AI driven methods are critical to success during in situ studies of materials. These include next generational battery components, accident safe nuclear fuels, catalytic materials and other emerging technologies that will help us develop clean energy solutions to fight climate change. Dan’s #LightSourceSelfie delves into what attracted him to this area of research, the inspiration he gets from helping users on the beamline and the addictive excitement that comes from doing science at 3am.

My interview as part of the #LightSourceSelfie series organized by Lightsources.org

Daniel Olds

Brookhaven National Laboratory

National Synchrotron Light Source II
Bldg. 741
P.O. Box 5000
Upton, NY 11973-5000

(631) 344-6133
dolds@bnl.gov

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