Publications

CSC research acknowledged in publications and presentations.

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Use was made of computational facilities purchased with funds from the National Science Foundation (CNS-1725797) and administered by the Center for Scientific Computing (CSC). The CSC is supported by the California NanoSystems Institute and the Materials Research Science and Engineering Center (MRSEC; NSF DMR 2308708) at UC Santa Barbara.

Selected Publications

2019

Molecular design of self-coacervation phenomena in block polyampholytes
Danielsen, S. P. O., McCarty, J., Shea, J. -E., Delaney, K. T., & Fredrickson, G. H. (2019). Molecular design of self-coacervation phenomena in block polyampholytes. Proceedings Of The National Academy Of Sciences, 116, 8224\textendash8232. https://doi.org/doi/10.1073/pnas.1900435116
Modeling magnetic evolution and exchange hardening in disordered magnets: The example of Mn 1- x Fe x Ru 2 Sn Heusler alloys
Decolvenaere, E., Levin, E., Seshadri, R., & Van der Ven, A. (2019). Modeling magnetic evolution and exchange hardening in disordered magnets: The example of Mn 1- x Fe x Ru 2 Sn Heusler alloys. Physical Review Materials, 3, 104411. https://doi.org/10.1103/PhysRevMaterials.3.104411
The Mitochondrial Peptide Humanin Targets, but does not Denature Amyloid Oligomers in Type II Diabetes
Levine, Z. A., Teranishi, K., Okada, A. K., Langen, R., & Shea, J. -E. (2019). The Mitochondrial Peptide Humanin Targets, but does not Denature Amyloid Oligomers in Type II Diabetes. Journal Of The American Chemical Society. https://doi.org/10.1021/jacs.9b04995
Miktoarm Stars via Grafting-Through Copolymerization: Self-Assembly and the Star-to-Bottlebrush Transition
Levi, A. E., Lequieu, J., Horne, J. D., Bates, M. W., Ren, J. M., Delaney, K. T., et al. (2019). Miktoarm Stars via Grafting-Through Copolymerization: Self-Assembly and the Star-to-Bottlebrush Transition. Macromolecules. https://doi.org/10.1021/acs.macromol.8b02321
Methane Pyrolysis with a Molten Cu\textendashBi Alloy Catalyst
Palmer, C., Tarazkar, M., Kristoffersen, H. H., Gelinas, J., Gordon, M. J., McFarland, E. W., & Metiu, H. (2019). Methane Pyrolysis with a Molten Cu\textendashBi Alloy Catalyst. Acs Catalysis. https://doi.org/10.1021/acscatal.9b01833
Measurement-driven entanglement transition in hybrid quantum circuits
Li, Y., Chen, X., & Fisher, M. P. A. (2019). Measurement-driven entanglement transition in hybrid quantum circuits. Physical Review B, 100, 134306. https://doi.org/10.1103/PhysRevB.100.134306
Mass-transfer driven spinodal decomposition in a ternary polymer solution
Tree, D. R., Santos, L. F. D., Wilson, C. B., Scott, T. R., Garcia, J. U., & Fredrickson, G. H. (2019). Mass-transfer driven spinodal decomposition in a ternary polymer solution. Soft Matter. https://doi.org/10.1039/C9SM00355J
Manganese oxidation as the origin of the anomalous capacity of Mn-containing Li-excess cathode materials
Radin, M. D., Vinckeviciute, J., Seshadri, R., & Van der Ven, A. (2019). Manganese oxidation as the origin of the anomalous capacity of Mn-containing Li-excess cathode materials. Nature Energy, 1. https://doi.org/10.1038/s41560-019-0439-6
Manganese oxidation as the origin of the anomalous capacity of Mn-containing Li-excess cathode materials
Radin, M. D., Vinckeviciute, J., Seshadri, R., & Van der Ven, A. (2019). Manganese oxidation as the origin of the anomalous capacity of Mn-containing Li-excess cathode materials. Nature Energy, 4, 639\textendash646. https://doi.org/10.1038/s41560-019-0439-6
Machine-learning the configurational energy of multicomponent crystalline solids
Natarajan, A. R., & Van der Ven, A. (2019). Machine-learning the configurational energy of multicomponent crystalline solids. Npj Computational Materials, 4, 56. https://doi.org/https://doi.org/10.1038/s41524-018-0110-y
Linear Scaling Self-Consistent Field Theory with Spectral Contour Accuracy
Vigil, D. L., ia-Cervera, C. J. G. \ \, Delaney, K. T., & Fredrickson, G. H. (2019). Linear Scaling Self-Consistent Field Theory with Spectral Contour Accuracy. Acs Macro Letters, 8, 1402\textendash1406. https://doi.org/10.1021/acsmacrolett.9b00632
Connecting the Simpler Structures to Topologically Close-Packed Phases
Natarajan, A. R., & Van der Ven, A. (2019). Connecting the Simpler Structures to Topologically Close-Packed Phases. Physical Review Letters, 121, 255701. https://doi.org/https://doi.org/10.1103/PhysRevLett.121.255701
The capricious nature of iodine catenation in I2 excess, perovskite-derived hybrid Pt(IV) compounds
Evans, H. A., Andrews, J. L., Fabini, D. H., Preefer, M. B., Wu, G., Cheetham, A. K., et al. (2019). The capricious nature of iodine catenation in I2 excess, perovskite-derived hybrid Pt(IV) compounds. Chemical Communications, 55, 588-591. https://doi.org/10.1039/c8cc07536k (Original work published 01/2019 C.E.)
Characterization of fracture in topology-optimized bioinspired networks
Nguyen, C., Peetz, D., Elbanna, A. E., & Carlson, J. M. (2019). Characterization of fracture in topology-optimized bioinspired networks. Physical Review E, 100, 042402. https://doi.org/10.1103-PhysRevE.100.042402
Charge Recombination Dynamics in Organic Photovoltaic Systems with Enhanced Dielectric Constant
Hughes, M. P., Rosenthal, K. D., Dasari, R. R., Luginbuhl, B. R., Yurash, B., Marder, S. R., & Nguyen, T. -Q. (2019). Charge Recombination Dynamics in Organic Photovoltaic Systems with Enhanced Dielectric Constant. Advanced Functional Materials, 1901269. https://doi.org/https://doi.org/10.1002/adfm.201901269
A comparison of different continuum approaches in modeling mixed-type dislocations in Al
Xu, S., Smith, L., Mianroodi, J. R., Hunter, A., Svendsen, B., & Beyerlein, I. (2019). A comparison of different continuum approaches in modeling mixed-type dislocations in Al. Modelling And Simulation In Materials Science And Engineering. https://doi.org/https://doi.org/10.1088/1361-651X/ab2d16
Complete Phase Diagram for Liquid\textendashLiquid Phase Separation of Intrinsically Disordered Proteins
McCarty, J., Delaney, K. T., Danielsen, S. P. O., Fredrickson, G. H., & Shea, J. -E. (2019). Complete Phase Diagram for Liquid\textendashLiquid Phase Separation of Intrinsically Disordered Proteins. The Journal Of Physical Chemistry Letters, 10, 1644-1652. https://doi.org/10.1021/acs.jpclett.9b00099 (Original work published 03/2019 C.E.)
Decoding signatures of structure, bulk thermodynamics, and solvation in three-body angle distributions of rigid water models
Monroe, J. I., & Shell, S. (2019). Decoding signatures of structure, bulk thermodynamics, and solvation in three-body angle distributions of rigid water models. The Journal Of Chemical Physics, 151, 094501. https://doi.org/10.1063/1.5111545
Demographic Obstacles to European Growth
Cooley, T. F., Henriksen, E., & Nusbaum, C. (2019). Demographic Obstacles to European Growth. https://doi.org/10.3386/w26503
Deep Neural Network Classifier for Variable Stars with Novelty Detection Capability
Tsang, B. T. -H., & Schultz, W. C. (2019). Deep Neural Network Classifier for Variable Stars with Novelty Detection Capability. The Astrophysical Journal Letters, 877, L14. https://doi.org/https://doi.org/10.3847/2041-8213/ab212c