DMREF: Deblurring our View of Atomic Arrangements in Complex Materials for Advanced Technologies

Project Personnel

Simon J. L. Billinge

Principal Investigator

Columbia University in the City of New York


Daniel Hsu

Columbia University in the City of New York


Qiang Du

Columbia University in the City of New York


Funding Divisions

Division of Materials Research (DMR), Division of Mathematical Sciences (DMS), Office of Multidisciplinary Activities (OMA)

We already have devices that turn sunlight into electricity and use sunlight to split water into precious hydrogen fuel, but issues such as device efficiency and cost mean that the current technologies cannot be taken to the vast scale needed for our modern needs. This puzzle may be solved by the use of advanced materials that perform their tasks - energy conversion, cancer cell killer, or whatever it may be - with greater efficiency. This project will bring greater clarity to this situation by marrying together advances in applied mathematics from diverse areas such as image recognition, information theory and machine learning, which are having transformative impacts in commerce, law enforcement and so on, and applying them to the problem of recognizing atomic arrangements in materials of the highest complexity. The approach will to solve multi-scale structures of materials by marrying together the latest advances in the processing of x-ray scattering data from nanomaterials, such as atomic pair distribution function (PDF) analysis, with other sources of input information such as small angle scattering, EXAFS and other spectroscopies, as well as inputs from first principle theory such as DFT, but place them in a rigorous mathematical framework and a robust computational framework such that the information content in the data may be utilized to the greatest extent possible whilst taking into account uncertainties from statistical and systematic uncertainties. The mathematical framework will utilize the latest developments in stochastic optimization, uncertainty quantification including function-space Bayesian methods, machine learning and image recognition.


A cloud platform for atomic pair distribution function analysis: PDFitc
L. Yang, E. A. Culbertson, N. K. Thomas, H. T. Vuong, E. T. S. Kjær, K. M. Ø. Jensen, M. G. Tucker, and S. J. L. Billinge
Cluster-mining: an approach for determining core structures of metallic nanoparticles from atomic pair distribution function data
S. Banerjee, C. Liu, K. M. Ø. Jensen, P. Juhás, J. D. Lee, M. Tofanelli, C. J. Ackerson, C. B. Murray, and S. J. L. Billinge
Algorithm for distance list extraction from pair distribution functions
R. Gu, S. Banerjee, Q. Du, and S. J. L. Billinge
Proton–Electron Conductivity in Thin Films of a Cobalt–Oxygen Evolving Catalyst
C. N. Brodsky, D. K. Bediako, C. Shi, T. P. Keane, C. Costentin, S. J. L. Billinge, and D. G. Nocera
Recent results on assigned and unassigned distance geometry with applications to protein molecules and nanostructures
S. J. L. Billinge, P. M. Duxbury, D. S. Gonçalves, C. Lavor, and A. Mucherino
Direct Observation of Dynamic Symmetry Breaking above Room Temperature in Methylammonium Lead Iodide Perovskite
A. N. Beecher, O. E. Semonin, J. M. Skelton, J. M. Frost, M. W. Terban, H. Zhai, A. Alatas, J. S. Owen, A. Walsh, and S. J. L. Billinge
Structures of Hard Phases in Thermoplastic Polyurethanes
M. W. Terban, R. Dabbous, A. D. Debellis, E. Pöselt, and S. J. L. Billinge
Atomic electron tomography: 3D structures without crystals
J. Miao, P. Ercius, and S. J. L. Billinge
Assigned and unassigned distance geometry: applications to biological molecules and nanostructures
S. J. L. Billinge, P. M. Duxbury, D. S. Gonçalves, C. Lavor, and A. Mucherino
Control of electronic properties of 2D carbides (MXenes) by manipulating their transition metal layers
B. Anasori, C. Shi, E. J. Moon, Y. Xie, C. A. Voigt, P. R. C. Kent, S. J. May, S. J. L. Billinge, M. W. Barsoum, and Y. Gogotsi

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Research Highlights

Data-mining our Way to Better Nanoparticle Structures
Simon Billinge (Columbia University)
Control of Electronic Properties of MXenes
Simon Billinge (Columbia University)
The Mathematics of Finding Atoms in Nanoparticles
Simon Billinge (Columbia University)
Teaching a Machine to See Symmetry Where We Can’t
Daniel Hsu, Qiang Du, Simon Billinge (Columbia University)

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Designing Materials to Revolutionize and Engineer our Future (DMREF)