Publications

The following publications feature research conducted by Trainees, faculty, and postdocs of the SEAS program.

  1. Oweida, T.J., Mahmood, A., Manning, M.D., Rigin, S., Yingling, Y.G. Merging Materials and Data Science: Opportunities, Challenges, and Education in Materials Informatics MRS Advances 5 [7, S1] 329-346. (2020) https://doi.org/10.1557/adv.2020.171
  2. Winkel, M.A., Stallrich, J.W., Storlie, C.B., Reich, B.J. Sequential Optimization in Locally Important Dimensions, Techometrics, early access available online (2020) https://doi.org/10.1080/00401706.2020.1714738
  3. De Guire, E.; Bartolo, L.; Brindle, R.; Devanathan, R.; Dickey, E.C., et al. Data‐driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities. J. Am. Ceram. Soc. 2019,102, 6385–6406. https://doi.org/10.1111/jace.16677
  4. Hu, H.; Ye, L.; Ghasemi, M.; Balar, N.; Rech, J. J.; Stuard, S. J.; You, W.; O’Connor, B. T.; Ade, H. Highly Efficient, Stable, and Ductile Ternary Nonfullerene Organic Solar Cells from a Two-Donor Polymer Blend. Adv. Mater. 2019, 31 (17), 1–8. https://doi.org/10.1002/adma.201808279.
  5. Carpenter, J. H.; Ghasemi, M.; Gann, E.; Angunawela, I.; Stuard, S. J.; Rech, J. J.; Ritchie, E.; O’Connor, B. T.; Atkin, J.; You, W.; DeLongchamp, D. M.; Ade, H. Competition between Exceptionally Long-Range Alkyl Sidechain Ordering and Backbone Ordering in Semiconducting Polymers and Its Impact on Electronic and Optoelectronic Properties. Adv. Funct. Mater. 2019, 29 (5), 1–13. https://doi.org/10.1002/adfm.201806977.
  6. Wright, A., Brent, R., Dickey, E. C., Weems, K. S., Reich, B. J., Jackson, C. R., (2019, April) A Bridge to the Ph.D. for URM Students CoNECD – The Collaborative Network for Engineering and Computing Diversity , Crystal City, Virginia, 2019 https://peer.asee.org/31735
  7. Lin, Y.; Fang, Y.; Zhao, J.; Shao, Y.; Stuard, S. J.; Nahid, M. M.; Ade, H.; Wang, Q.; Shield, J. E.; Zhou, N.; et al. Unveiling the Operation Mechanism of Layered Perovskite Solar Cells. Nat. Commun. 2019, 10 (1), 1–12. https://doi.org/10.1038/s41467-019-08958-9.
  8. Gardinier, T. C.; Kohle, F. F. E.; Peerless, J. S.; Ma, K.; Turker, M. Z.; Hinckley, J. A.; Yingling, Y. G.; Wiesner, U. High-Performance Chromatographic Characterization of Surface Chemical Heterogeneities of Fluorescent Organic-Inorganic Hybrid Core-Shell Silica Nanoparticles. ACS Nano. 2019. https://doi.org/10.1021/acsnano.8b07876.
  9. Leon, L.S., Miles, P.R., Smith, R.C., Oates, W.S. Active subspace analysis and uncertainty quantification for a polydomain ferroelectric phase-field model J. Intell. Mater. Syst. Struct. 2019, 30(14), 2027-2051. https://doi.org/10.1177/1045389X19853636
  10. Hu, J., Oswald, I.W.H., Hu, H., Stuard, S.J., Nahid, M.M., Yan, L., CHen, Z., Ade, H., Neilson, J.R., You, W. Aryl-Perfluoroaryl Interaction in Two-Dimensional Organic–Inorganic Hybrid Perovskites Boosts Stability and Photovoltaic Efficiency, ACS Materials Lett. 2019, 1 (1), 171–176. https://doi.org/10.1021/acsmaterialslett.9b00102
  11. Hu, J.; Oswald, I. W. H.; Stuard, S. J.; Nahid, M. M.; Zhou, N.; Williams, O. F.; Guo, Z.; Yan, L.; Hu, H.; Chen, Z.; et al. Synthetic Control over Orientational Degeneracy of Spacer Cations Enhances Solar Cell Efficiency in Two-Dimensional Perovskites. Nat. Commun. 2019, 10 (1), 1–12. https://doi.org/10.1038/s41467-019-08980-x.
  12. Peerless, J. S.; Milliken, N. J. B.; Oweida, T. J.; Manning, M. D.; Yingling, Y. G. Soft Matter Informatics: Current Progress and Challenges. Adv. Theory Simulations 2019. https://doi.org/10.1002/adts.201800129.
  13. Li, F.; Cabral, M. J.; Xu, B.; Cheng, Z.; Dickey, E. C.; Lebeau, J. M.; Wang, J.; Luo, J.; Taylor, S.; Hackenberger, W.; et al. Giant Piezoelectricity of Sm-Doped Pb(Mg1/3Nb2/3)O3-PbTiO3 Single Crystals. Science 2019, 1 (April), 264–268.
    doi:10.1126/science.aaw2781
  14. Kang, Q., Ye, L., Xu, B., An, C., Stuard, S.J., Zhang, S., Yao, H., Ade, H., Hou, J., A Printable Organic Cathode Interlayer Enables over 13% Efficiency for 1-cm 2 Organic Solar Cells. Joule 2019, 3 (1), 227-239. https://doi.org/10.1016/j.joule.2018.10.024
  15. Leon, L.; Smith, R. C.; Oates, W. S.; Miles, P. Analysis of a Multi-Axial Quantum-Informed Ferroelectric Continuum Model: Part 2—Sensitivity Analysis. J. Intell. Mater. Syst. Struct. 2018, 29 (13), 2840–2860. doi.org/10.1177/1045389X18781024
  16. Miles, P.; Leon, L.; Smith, R. C.; Oates, W. S. Analysis of a Multi-Axial Quantum Informed Ferroelectric Continuum Model: Part 1—Uncertainty Quantification. J. Intell. Mater. Syst. Struct. 2018, 29 (13), 2823–2839. doi.org/10.1177/1045389X18781023
  17. Bakerman, J.; Pazdernik, K.; Wilson, A.; Fairchild, G.; Bahran, R. Twitter Geolocation. ACM Trans. Knowl. Discov. Data 2018, 12 (3), 1–17. https://doi.org/10.1145/3178112.
  18. Leon, L. S.; Smith, R. C.; Oates, W. S.; Miles, P. Active Subspace Uncertainty Quantification for a Polydomain Ferroelectric Phase-Field Model. In Proceedings of SPIE; 2018; Vol. 10596, p 25. https://doi.org/10.1117/12.2297207.
  19. Cabral, M. J.; Zhang, S.; Dickey, E. C.; Lebeau, J. M. Gradient Chemical Order in the Relaxor Pb(Mg1/3Nb2/3)O3. Appl. Phys. Lett. 2018, 112 (8). doi: 10.1063/1.5016561
  20. Peerless, J. S.; Bowers, G. H.; Kwansa, A. L.; Yingling, Y. G. Effect of C60 Adducts on the Dynamic Structure of Aromatic Solvation Shells. Chem. Phys. Lett. 2017, 678, 79–84. https://doi.org/10.1016/j.cplett.2017.04.010

    Theses & Dissertations

  21. McDowell, S.M. A Sequential Analysis of X-ray Diffraction Data, M.S. Thesis, North Carolina Central University (2019) ISBN: 1085656225, 9781085656221
  22. Peerless, J. S. Nanoparticle-Solvent Interactions: Design Insight from Atomic Simulation, Ph.D. Dissertation, North Carolina State University (2019) URI: http://www.lib.ncsu.edu/resolver/1840.20/36445.
  23. Leon, L. S. Parameter Subset Selection and Subspace Analysis Techniques Applied to a Polydomain Ferroelectric Material Phase-Field Energy Model, Ph.D. Dissertation, North Carolina State University (2018) URI: http://www.lib.ncsu.edu/resolver/1840.20/35537.
  24. Cabral, M. J. Quantifying Short-Range Chemical and Structural Order in Complex Oxides via Scanning Transmission Electron Microscopy, Ph.D. Dissertation, North Carolina State University (2018) URI: http://www.lib.ncsu.edu/resolver/1840.20/35613.
  25. Bourne, N., Small Frobenius Functionals on the Maximal Parabolic Subalgebras of sl(n,F), M.S. Thesis, North Carolina Central University (2018) ISBN: 0438267311, 9780438267312

    Book Chapters

  26. Reynolds, J.R., Thompson, B.C., Skotheim, T.A., Ye, L., Stuard, S.J., Ade, H. (2019) “Soft X-Ray Scattering Characterization of Polymer Semiconductors” John R. Reynolds, Barry C. Thompson, Terje A. Skotheim (Eds.) Handbook of Conducting Polymers: Conjugated Polymers: Properties, Processing, and Applications pp. 427-458. Abingdon, United Kingdom. Taylor & Francis Group. http://doi.org/10.1201/9780429190520-13
  27. Singh, S.; Paterson, A. R.; Wendelberger, L. J.; Fancher, C. M.; Reich, B. J.; Smith, R. C.; Wilson, A. G.; Jones, J. L. Algorithms in Diffraction Profile Analysis. Handbook on Big Data and Machine Learning in the Physical Sciences Volume 1: Big Data Methods in Experimental Materials Discovery, Big, Deep, and Smart Data in Physical and Chemical Imaging; Foster, Ian, Kalinin, S., Ed.; World Scientific Publishers, 2019. https://doi.org/10.1142/9789811204555_0015
  28. Paterson, A., Reich, B., Smith, R., Wilson, A., Jones, J. (2018). Bayesian Approaches to Uncertainty Quantification and Structure Refinement from X-ray Diffraction. Materials Discovery and Design: Data Science and Optimal Learning, eds. T. Lookman, S. Eidenbenz, F.Alexander and C. Barnes, Springer International Publishing. vol 280, pp. 81-102. Print ISBN: 978-3-319-99464-2. https://doi.org/10.1007/978-3-319-99465-9_4

    NRT-Motivating Publications by SEAS Faculty

  • Monitoring charge separation processes in quasi-one-dimensional organic crystalline structures
    Adrian Popescu, Robert A. Younts, Benjamin Hoffman, Terry McAfee, Daniel B. Dougherty, Harald W. Ade, Kenan Gundogdu, and Igor V. Bondarev
    doi: 10.1021/acs.nanolett.7b02471
  • Statistical and image analysis for characterizing simulated atomic-scale damage in crystals
    D. Li, B.J. Reich, D.W. Brenner
    https://doi.org/10.1016/j.commatsci.2017.03.054
  • How predictable is plastic damage at the atomic scale?
    D. Li, E. W. Bucholz, G. Peterson, B.J. Reich, J. C. Russ, and D.W. Brenner
    http://dx.doi.org/10.1063/1.4977420
  • Use of Bayesian Inference in Crystallographic Structure Refinement via Full Diffraction Profile Analysis
    Chris M. Fancher, Zhen Han, Igor Levin, Katharine Page, Brian J. Reich, Ralph C. Smith, Alyson G. Wilson & Jacob L. Jones
    doi:10.1038/srep31625
    https://www.nature.com/articles/srep31625
  • A Bayesian approach to modeling diffraction profiles and application to ferroelectric materials
    T. Iamsasri, J. Guerrier, G. Esteves, C. M. Fancher, A. G. Wilson, R. C. Smith, E. A. Paisley, R. Johnson-Wilke, J. F. Ihlefeld, N. Bassiri-Gharb and J. L. Jones
    https://doi.org/10.1107/S1600576716020057
  • A three-dimensional polyhedral unit model for grain boundary structure in fcc metals
    Arash Dehghan Banadaki & Srikanth Patala
    doi:10.1038/s41524-017-0016-0
    https://www.nature.com/articles/s41524-017-0016-0
  • Lowest energy Frenkel and charge transfer exciton intermixing in one-dimensional copper phthalo-cyanine molecular lattice
    I.V. Bondarev, A. Popescu, R. A. Younts, B. Hoffman, T. McAfee, D.B. Dougherty, K. Gundogdu, and H.W. Ade
    http://dx.doi.org/10.1063/1.4968821
  • Quantification of parameter and model uncertainty for shape memory alloy bending actuators
    John H Crews, Ralph C Smith
    doi: 10.1177/1045389X13490842
    http://journals.sagepub.com/doi/full/10.1177/1045389X13490842
  • Quantification of parameter uncertainty for robust control of shape memory alloy bending actuators
    John H Crews, Jerry A McMahan, Ralph C Smith and Jennifer C Hannen
    https://doi.org/10.1088/0964-1726/22/11/115021