All Publications


  • Generalizable density functional theory based photoemission model for the accelerated development of photocathodes and other photoemissive devices PHYSICAL REVIEW B Antoniuk, E. R., Yue, Y., Zhou, Y., Schindler, P., Schroeder, W., Dunham, B., Pianetta, P., Vecchione, T., Reed, E. J. 2020; 101 (23)
  • Combining Superionic Conduction and Favorable Decomposition Products in the Crystalline Lithium-Boron-Sulfur System: A New Mechanism for Stabilizing Solid Li-Ion Electrolytes. ACS applied materials & interfaces Sendek, A. D., Antoniuk, E. R., Cubuk, E. D., Ransom, B. n., Francisco, B. E., Buettner-Garrett, J. n., Cui, Y. n., Reed, E. J. 2020; 12 (34): 37957–66

    Abstract

    We report a solid-state Li-ion electrolyte predicted to exhibit simultaneously fast ionic conductivity, wide electrochemical stability, low cost, and low mass density. We report exceptional density functional theory (DFT)-based room-temperature single-crystal ionic conductivity values for two phases within the crystalline lithium-boron-sulfur (Li-B-S) system: 62 (+9, -2) mS cm-1 in Li5B7S13 and 80 (-56, -41) mS cm-1 in Li9B19S33. We report significant ionic conductivity values for two additional phases: between 0.0056 and 0.16 mS/cm -1 in Li2B2S5 and between 0.0031 and 9.7 mS cm-1 in Li3BS3 depending on the room-temperature extrapolation scheme used. To our knowledge, our prediction gives Li9B19S33 and Li5B7S13 the second and third highest reported DFT-computed single-crystal ionic conductivities of any crystalline material. We compute the thermodynamic electrochemical stability window widths of these materials to be 0.50 V for Li5B7S13, 0.16 V for Li2B2S5, 0.45 V for Li3BS3, and 0.60 V for Li9B19S33. Individually, these materials exhibit similar or better ionic conductivity and electrochemical stability than the best-known sulfide-based solid-state Li-ion electrolyte materials, including Li10GeP2S12 (LGPS). However, we predict that electrolyte materials synthesized from a range of compositions in the Li-B-S system may exhibit even wider thermodynamic electrochemical stability windows of 0.63 V and possibly as high as 3 V or greater. The Li-B-S system also has a low elemental cost of approximately 0.05 USD/m2 per 10 μm thickness, which is significantly lower than that of germanium-containing LGPS, and a comparable mass density below 2 g/cm3. These fast-conducting phases were initially brought to our attention by a machine learning-based approach to screen over 12,000 solid electrolyte candidates, and the evidence provided here represents an inspiring success for this model.

    View details for DOI 10.1021/acsami.9b19091

    View details for PubMedID 32700896

  • Machine Learning-Assisted Discovery of Solid Li-Ion Conducting Materials CHEMISTRY OF MATERIALS Sendek, A. D., Cubuk, E. D., Antoniuk, E. R., Cheon, G., Cui, Y., Reed, E. J. 2019; 31 (2): 342–52
  • New Assembly-Free Bulk Layered Inorganic Vertical Heterostructures with Infrared and Optical Bandgaps NANO LETTERS Antoniuk, E. R., Cheon, G., Krishnapriyan, A., Rehn, D. A., Zhou, Y., Reed, E. J. 2019; 19 (1): 142–49

    Abstract

    In principle, a nearly endless number of unique van der Waals heterostructures can be created through the vertical stacking of two-dimensional (2D) materials, resulting in unprecedented potential for material design. However, this widely employed synthetic method for generating van der Waals heterostructures is slow, imprecise, and prone to introducing interlayer contaminants when compared with synthesis methods that are scalable to industrially relevant scales. Herein, we study the properties of a new class of layered bulk inorganic materials that has recently been reported, which we call assembly-free bulk layered inorganic heterostructures, wherein the individual layers are of dissimilar chemical composition, distinguishing them from commonly studied layered materials. We find that these bulk materials exhibit properties similar to vertical heterostructures, but without the complex and unscalable stacking process. Using state-of-the-art computational approaches, we study the electronic properties of livingstonite (HgSb4S8), a naturally occurring mineral that is a bulk lattice-commensurate heterostructure. We find that isolated bilayers of livingstonite have an intralayer HSE-06 band gap of 2.08eV. This is the first report of a naturally occurring van der Waals heterostructure with a calculated band gap in the visible spectrum. We also studied the electronic properties of tetragonal Ti3Bi4O12, Sm2Ti3Bi2O12, orthorhombic Ti3Bi4O12, Nb3Bi5O15, LaTiNbBi2O9 and AgPbBrO and found some of them are potentially well suited for photovoltaic applications. We also provide characterization of the electronic structure of the isolated bilayer and monolayer subcomponents of the bulk heterostructures. The report of the properties of these materials significantly enhances the library of known van der Waals heterostructures.

    View details for DOI 10.1021/acs.nanolett.8b03500

    View details for Web of Science ID 000455561300017

    View details for PubMedID 30525679

  • Revealing the Spectrum of Unknown Layered Materials with Superhuman Predictive Abilities JOURNAL OF PHYSICAL CHEMISTRY LETTERS Cheon, G., Cubuk, E. D., Antoniuk, E. R., Blumberg, L., Goldberger, J. E., Reed, E. J. 2018; 9 (24): 6967–72

    Abstract

    We discover the chemical composition of over 1000 materials that are likely to exhibit layered and two-dimensional phases but have yet to be synthesized. This includes two materials our calculations indicate can exist in distinct structures with different band gaps, expanding the short list of two-dimensional phase change materials. While databases of over 1000 layered materials have been reported, we provide the first full database of materials that are likely layered but yet to be synthesized, providing a roadmap for the synthesis community. We accomplish this by combining physics with machine learning on experimentally obtained data and verify a subset of candidates using density functional theory. We find our model performs five times better than practitioners in the field at identifying layered materials and is comparable or better than professional solid-state chemists. Finally, we find that semi-supervised learning can offer benefits for materials design where labels for some of the materials are unknown.

    View details for PubMedID 30481462