CENTER FOR THE SCIENCE OF
SYNTHESIS ACROSS SCALES
PUBLICATIONS
102. Schwarzer, M., J. Farebrother, J. Greaves, E. D. Cubuk, R. Agarwal, A. Courville, M. G. Bellemare, S.V. Kalinin, I. Mordatch, P. S. Castro, and K. M. Roccapriore. (2025). Learning and Controlling Silicon Dopant Transitions in Graphene Using Scanning Transmission Electron Microscopy. Adv. Mater. Interfaces, 2400998. DOI: https://doi.org/10.1002/admi.202400998.
101. Teng, F., H. Zhang, D. Nykypanchuk, R. Li, L. Yang, N. Tiwale, Z. Xi, M. Liu, M. He, and O. Gang. (2025). Macroscale-Area Patterning of Three-Dimensional DNA-Programmable Frameworks. Nat Commun, 16, 3238. https://doi.org/10.1038/s41467-025-58422-0
100. Shi, C., Y. Bae, M. Zhang, J. J. De Yoreo. (2025). Manipulating the Assembly and Architecture of Fibrillar Silk. Adv. Mater, 2501096. https://doi.org/10.1002/adma.202501096
99. Qi, X., S. Helland, C. Lowe, H. Larson, J. Cui, R. Zheng, M. Monahan, C-L. Chen, J. J. De Yoreo, J. Pfaendtner, and B.M. Cossairt. (2025). Toward Computation-Guided Design of Tunable Organic–Inorganic CdS Quantum Dot Binary Superlattices. Nano Letters. DOI: https://doi.org/10.1021/acs.nanolett.5c00024
98. Zhang, Z.. H.T. Chiang, Y. Xia, N. Avakyan, R. Sonani, F. Wang, E. Egelman, J.J. De Yoreo, L.D. Pozzo, and F. A. Tezcan (2025). Design of Light- and Chemically-Responsive Protein Assemblies through Host-Guest Interactions. Chem, 11, 102407. DOI: https://doi.org/10.1016/j.chempr.2024.102407
97. Larson, H., Z. Lin, F. Baneyx and B.M. Cossairt. (2025). Alternate InP Synthesis with Aminophosphines: Solution-Liquid-Solid Nanowire Growth. Nanoscale. DOI: https://doi.org/10.1039/D4NR04907A
96. Li, Y., J. Zhu, Z. Zhang, J. Wei, F. Wang, G. Meisl, T. Knowles, E, Egelman and F. A Tezcan. (2025). Transforming an ATP-dependent enzyme into a dissipative, self-assembling system. Nat. Chem. Biol. DOI: https://doi.org/10.1038/s41589-024-01811-1
95. Raghavan, A., U. Pratiush, M. Valleti, R. Liu, R. Emery, H. Funakubo, Y. Liu, P. Rack and S.V. Kalinin. (2025). Invariant Discovery of Features Across Multiple Length Scales: Applications in Microscopy and Autonomous Materials Characterization. J. Appl. Phys, 137 (3): 034901. DOI: https://doi.org/10.1063/5.0233070
94. McCutchin, C., K. Edgar, C-L. Chen, and P. Dove. (2024). Silica-Biomacromolecule Interactions: Toward a Mechanistic Understanding of Silicification. Biomacromolecules, 26 (1): 43–84. DOI: https://doi.org/10.1021/acs.biomac.4c00674.
93. Berlaga, A., K. Torkelson, A. Seal, J. Pfaendtner, and A.L. Ferguson. (2024). A Modular and Extensible CHARMM-Compatible Model for All-Atom Simulation of Polypeptoids. J Chem Phys, 161(24): 244901. DOI: https://doi.org/10.1063/5.0238570
92. Lowe, C., H. Larson, Y. Cai, H.T. Chiang, L.D. Pozzo, F. Baneyx and B.M. Cossairt. (2024). Induced Chirality in QDs Using Thermoresponsive Elastin-like Polypeptides. Langmuir, 41 (1): 1047–1056. DOI: https://doi.org/10.1021/acs.langmuir.4c04339
91. Biswas, A., M. Valleti, R. Vasudevan, M. Ziatdinov, and S. V. Kalinin. (2024). Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization. ASME. J. Comput. Inf. Sci. Eng, 24(12): 121005. DOI: https://doi.org/10.1115/1.4066856
90. Jin, B., Y. Chen, H. Pyles, M. D. Baer, B. A. Legg, Z. Wang, N. M. Washton, K. T. Mueller, D. Baker, G. K. Schenter, C. J. Mundy, and J. J. De Yoreo. (2024). Formation, chemical evolution and solidification of the dense liquid phase of calcium (bi)carbonate. Nat. Mater. (2024). DOI: https://doi.org/10.1038/s41563-024-02025-5
89. Naser, N., W. Wixson, H. Larson, B.M. Cossairt, L.D. Pozzo and F. Baneyx. (2024). Biomimetic Mineralization of Positively Charged Silica Nanoparticles Templated by Thermoresponsive Protein Micelles: Applications to Electrostatic Assembly of Hierarchical and Composite Superstructures. Soft Matter, 21:166-178. DOI: https://doi.org/10.1039/D4SM00907J
88. Chiang, HT., K. Vaddi, and L.D. Pozzo. (2024). Data-driven exploration of silver nanoplate formation in multidimensional chemical design spaces. Digital Discovery. DOI: 10.1039/d4dd00211c
87. Barakati, K., H. Yuan, A. Goyald and S. V. Kalinin. (2024). Physics-based reward driven image analysis in microscopy. Digital Discovery, 3, 2061-2069. DOI: https://doi.org/10.1039/D4DD00132J
86. Torkelson, K. and J. Pfaendtner. (2024). Exploration of Tertiary Structure in Sequence-Defined Polymers Using Molecular Dynamics Simulations. Biomacromolecules, 25 (10): 6439–6450. DOI: https://doi.org/10.1021/acs.biomac.4c00527
85. Shi, C., M. Zorman, X. Zhao, M. B. Salmeron, J. Pfaendtner, XY. Liu, S. Zhang, and J.J. De Yoreo. (2024). Two-dimensional silk. Science Advances. eado4142, 10. DOI: 10.1126/sciadv.ado4142
84. Slautin, B. N., Y. Liu, H. Funakubo, R. Vasudevan, M. Ziatdinov, and S. V. Kalinin. (2024). Bayesian Co-navigation: Dynamic Designing of the Materials Digital Twins via Active Learning. ACS Nano, 18: 24898–24908. DOI: https://doi.org/10.1021/acsnano.4c05368
83. Valleti, M., M. Ziatdinov, Y. Liu, and S.V. Kalinin. (2024). Physics and Chemistry from Parsimonious Representations: Image Analysis via Invariant Variational Autoencoders. npj Computational Materials, 10, 183. DOI: https://doi.org/10.1038/s41524-024-01250-5
82. Liu, Y., BD. Huey, M. Ziatdinov, and S.V. Kalinin. (2024). Physical discovery in representation learning via conditioning on prior knowledge. J. Appl. Phys, 136: 064902. DOI: 10.1063/5.0222403
81. Vijayakumar, S. Alberstein, R. Zhang, Z.,Lu, Y-S.. Chan, A., Wahl, C., Ha, J., Hunka, D., Boss, G., Sailor, M. and F. A.Tezcan. (2024). Designed 2D protein crystals as dynamic molecular gatekeepers for a solid-state device. Nature Communications, 15: 6326. DOI: https://doi.org/10.1038/s41467-024-50567-8
80. Stegmann, A., B.A. Legg, J.J. De Yoreo, and S. Zhang. (2024). Machine learning-driven descriptions of protein dynamics at solid-liquid interfaces. J-Y Yoon & C. Yu (Eds.), Machine Learning and Artificial Intelligence in Chemical and Biological Sensing (321-340), Wiley. DOI: https://doi.org/10.1016/B978-0-443-22001-2.00013-5
79. Roccapriore, K.M., R. Torsi, J.A. Robinson, S.V. Kalinin, and M. Ziatdinov. (2024). Dynamic STEM-EELS for single-atom and defect measurement during electron beam transformations. Science Advances, eadn5899, 10. DOI: 10.1126/sciadv.adn5899
78. Maradesa, A., B. Py , J. Huang, Y. Lu, P. Iurilli, A. Mrozinski, H.M. Law, Y. Wang, Z. Wang, J. Li, S. Xu, Q. Meyer, J. Liu, C. Brivio, A. Gavrilyuk, K. Kobayashi, A. Bertei, N.J. Williams, C. Zhao, M. Danzer, M. Zic, P. Wu, V. Yrjänä, S. Pereverzyev, Y. Chen, A. Weber, S. V. Kalinin, J.P. Schmidt, Y. Tsur, B.A. Boukamp, Q. Zhang, M. Gaberšček, R. O’Hayre, and F. Ciucci. (2024). Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method. Joule, 8 (7): 1958-1981. DOI: https://doi.org/10.1016/j.joule.2024.05.008
77. Slautin, B. N., U. Pratiush, I.N. Ivanov, Y. Liu, R. Pant, X. Zhang, I. Takeuchi, M. Ziatdinov and S.V. Kalinin. (2024) Co-orchestration of multiple instruments to uncover structure–property relationships in combinatorial libraries. Digital Discovery, 3 (8): 1602-1611. DOI: https://doi.org/10.1039/D4DD00109E
76. Gupta, A. K., E. Zarkadoula, M. Ziatdinov, S.V. Kalinin, V.R. Paduri, J.A. Hachtel, Y. Zhang, C. Trautmann, W. J. Weber, and R. Sachan. (2024). Nanoscale core–shell structure and recrystallization of swift heavy ion tracks in SrTiO3. Nanoscale, 16 (30), 14366-14377. DOI: https://doi.org/10.1039/D4NR01974A
75. Zhai, Z., S.Y. Schmid, Z. Lin, S. Zhang, and F. Jiao. (2024). Unveiling the Nanoscale Architectures and Dynamics of Protein Assembly with in situ Atomic Force Microscopy. Aggregate, 5 (5): e604. DOI: https://doi.org/10.1002/agt2.604
74. Ziatdinov, M.A., M.Y. Yaman, Y. Liu, D. Ginger, and S.V. Kalinin. (2024). Semi-supervised learning of images with strong rotational disorder: Assembling nanoparticle libraries. Digital Discovery, 3, 1213-1220. DOI: 10.1039/D3DD00196B
73. Shao L., D. Hu, SL. Zheng, TKH. Trinh, W. Zhou, H. Wang, Y. Zong, C. Li, and C-L. Chen. (2024). Hierarchical Self-Assembly of Multidimensional Functional Materials from Sequence-Defined Peptoids. Angew. Chem. Int. Ed. e202403263, 63. DOI: 10.1002/anie.202403263
72. Zheng, R., M. Zhao, JS. Du, TR. Sudarshan, Y. Zhou, AK. Paravastu, J.J. De Yoreo, A.L. Ferguson, and C-L. Chen. (2024) Assembly of short amphiphilic peptoids into nanohelices with controllable supramolecular chirality. Nat Commun, 15: 3264. DOI: 10.1038/s41467-024-46839-y
71. Shen, H., E.M. Lynch, S. Akkineni, J.L. Watson, J. Decarreau, N.P. Bethel, I. Benna, W. Sheffler, D. Farrell, F. DiMaio, E. Derivery, J.J. De Yoreo, J. Kollman, and D. Baker. (2024). De novo design of pH-responsive self-assembling helical protein filaments. Nature Nanotechnology, 19: 1016–1021. DOI: 10.1038/s41565-024-01641-1
70. Cai, Y., N. Naser, J. Ma, and F. Baneyx. (2024). Precision loading and delivery of molecular cargo by size-controlled coacervation of gold nanoparticles functionalized with elastin-like peptides. Biomacromolecules, 25: 2390-2398. DOI: 10.1021/acs.biomac.3c01312
69. Lo, S., S.G. Baird, J. Schrier, B. Blaiszik, N. Carson, I. Foster, A. Aguilar-Granda, S.V. Kalinin, B. Maruyama, and M. Politi (2024). Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept. Digital Discovery, 3 (5): 842-868. DOI: https://doi.org/10.1039/D3DD00223C
68. Smith, B.R., B. Pant, Y. Liu, J-C. Yang, S. Jesse, A. Khojandi, S.V. Kalinin, Y. Cao, and R.K. Vasudevan. (2024). Physics-informed models of domain-wall dynamics as a route for autonomous domain wall design via reinforcement learning. Digital Discovery, 3: 456-466. DOI: 10.1039/D3DD00126A
67. Du, J., Y. Bae, and J.J. De Yoreo. (2024). Non-classical crystallization in soft and organic materials. Nature Reviews Materials, 9: 229–248. DOI: 10.1038/s41578-023-00637-ys
66. Cai, Y., X. Qi, J. Boese, Y. Zhao, B. Hellner, J. Chun, C. Mundy, and F. Baneyx. (2024). Towards predictive control of reversible nanoparticle assembly with solid-binding proteins. Soft Matter, 20: 1935-1942. DOI: 10.1039/D4SM00094C
65. M. Valleti, R.K. Vasudevan, M.A. Ziatdinov, and S.V. Kalinin. (2024). Deep kernel methods learn better: From cards to process optimization. Machine Learning Science & Technology, 5: 015012. DOI: 10.1088/2632-2153/ad1a4f
64. Torkelson, K., N.Y. Naser, X. Qi, Z. Li, W. Yang, K. Pushpavanam, C-L. Chen, F. Baneyx, and J. Pfaendtner. (2024). Rational design of novel biomimetic sequence-defined polymers for mineralization applications. Chemistry of Materials, 36: 786-794. DOI: 10.1021/acs.chemmater.3c02216
63. Davila-Hernandez, F.A., B. Jin, H. Pyles, S. Zhang, Z. Wang, T.F. Huddy, A.K. Bera, A. Kang, C-L. Chen, J.J. De Yoreo, and D. Baker. (2023). Directing polymorph specific calcium carbonate formation with de novo protein templates. Nature Communications, 14: 1-11. DOI: 10.1038/s41467-023-43608-1
62. Ziatdinov, M, C.Y.T. Wong, and S.V. Kalinin. (2023). Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders. Machine Learning: Science and Technology, 4 (4): 045033. DOI: https://doi.org/10.1088/2632-2153/ad073b
61. Lachowski, K.J., HT. Chiang, K. Torkelson, W. Zhou, S. Zhang, J. Pfaendtner, and LD. Pozzo. (2023). Anisotropic gold nanomaterial synthesis using peptide facet specificity and timed intervention. Langmuir, 39: 15878-15888. DOI: 10.1021/acs.langmuir.3c01577
60. Yang, W., B. Cai, K.J. Lachowski, Q. Yin, J.J. De Yoreo, L.D. Pozzo, and C-L. Chen. (2023). Insights into the biomimetic synthesis of 2D ZnO nanomaterials through peptoid engineering. Journal of Physical Chemistry Letters, 14: 9732-9739. DOI: 10.1021/acs.jpclett.3c01882
59. Jin, B., Y. Chen, J. Tao, K.J. Lachowski, M.E. Bowden, Z. Zhang, L.D. Pozzo, N.M. Washton, K.T. Mueller, and J.J. De Yoreo. (2023). Multi-step nucleation of a crystalline silicate framework via a structurally precise prenucleation cluster. Angewandte Chemie, 62: 1-7. DOI: 10.1002/anie.202303770
58. Schmid, S.Y., K. Lachowski, HT. Chiang, L. Pozzo, J.J. De Yoreo, and S. Zhang. (2023). Mechanisms of biomolecular self-assembly investigated through in situ observations of structures and dynamics. Angewandte Chemie, 62: 1-29. DOI: 10.1002/anie.202309725
57. Larson, H. and B. Cossairt. (2023). Indium-poly(carboxylic acid) ligand interactions modify InP quantum dot nucleation and growth. Chemistry of Materials, 35: 6152-6160. DOI: 10.1021/acs.chemmater.3c01309
56. Alamdari, S. and J. Pfaendtner. (2023). Origins of conformational heterogeneity in peptoid helices formed by chiral N-1 phenylethyl sidechains. Journal of Physical Chemistry B, 127: 6163-6170. DOI: 10.1021/acs.jpcb.3c02576
55. Alamdari, S., K. Torkelson, X. Wang, C-L. Chen, A.L. Ferguson, and J. Pfaendtner. (2023). Thermodynamic basis for stabilization of helical peptoids by chiral sidechains. Journal of Physical Chemistry B, 127: 6171-6183. DOI: 10.1021/acs.jpcb.3c01913
54. Zhao, M., S. Zhang, R. Zheng, S. Alamdari, C.J. Mundy, J. Pfaendtner, L. Pozzo, C-L. Chen, J.J. De Yoreo, and A.L. Ferguson. (2023). Computational and experimental determination of the properties, structure, and stability of peptoid nanosheets and nanotubes. Biomacromolecules, 24: 2618-2632. DOI: 10.1021/acs.biomac.3c00107
53. Yaman, M.Y., S.V. Kalinin, K.N. Guye, D.S. Ginger, and M. Ziatdinov. (2023). Learning and predicting photonic responses of plasmonic nanoparticle assemblies via dual variational autoencoders. Small, 19: 2205893. DOI: 10.1002/smll.202205893
52. Biswas, A., R. Vasudevan, M. Ziatdinov, and S.V. Kalinin. (2023). Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach. Machine Learning Science and Technology, 4: 1-15. DOI: 10.1088/2632-2153/acb316
51. Alberstein, R.G., J.L. Prelesnik, E. Nazouki, S. Zhang, J.J. De Yoreo, J. Pfaendtner, F.A. Tezcan, and C.J. Mundy. (2023). Discrete orientations of interfacial waters direct crystallization of mica-binding proteins. Journal of Physical Chemistry Letters, 14: 80-87. DOI: 10.1021/acs.jpclett.2c02948
50. Yang, W., Y. Zhou, B. Jin, X. Qi, B. Cai, Q. Yin, J. Pfaendtner, J.J. De Yoreo, and C-L. Chen. (2023). Designing sequence-defined peptoids for fibrillar self-assembly and silicification. Journal of Colloid and Interface Science, 634: 450-459. DOI: 10.1016/j.jcis.2022.11.136
49. Shao, L., J. Ma, J.L. Prelesnik, Y. Zhou, M. Nguyen, M. Zhao, S.A. Jenekhe, S.V. Kalinin, A.L. Ferguson, J. Pfaendtner, C.J. Mundy, J.J. De Yoreo, F. Baneyx, and C-L. Chen. (2022). Hierarchical materials from high information content macromolecular building blocks: Construction, dynamic interventions, and prediction. Chemical Reviews, 122: 17397-17478. DOI: 10.1021/acs/chemrev.2c00220
48. Valetti, M., R.K. Vasudevan, M.A. Ziatdinov, and S.V. Kalinin. (2022). Bayesian optimization in continuous spaces via virtual process embeddings. Digital Discovery, 1: 910-925. DOI: 10.1039/D2DD00065B
47. J. Ma, B. Jin, K. N. Guye, M. E. Chowdhury, N. Y. Naser, C-L. Chen, J. J. De Yoreo, and F. Baneyx. (2023). Controlling Mineralization with Protein-Functionalized Peptoid Nanotubes. Adv. Mater, 35, 2207543. DOI: 10.1002/adma.202207543
46. Vaddi, K., H.T. Chiang, and L.D. Pozzo. (2022). Autonomous retrosynthesis of gold nanoparticles via spectral shape matching. Digital Discovery, 1: 502-510. DOI: 10.1039/D2DD00025C
45. Lachowski, K., K. Vaddi, N. Naser, F. Baneyx, and L.D. Pozzo. (2022). Multivariate analysis of peptide-driven nucleation and growth of Au nanoparticles. Digital Discovery, 1: 427-439. DOI: 10.1039/D2DD00017B
44. Jian, T., Y. Zhou, P. Wang, W. Yang, P. Mu, X. Zhang, X. Zhang, and C-L. Chen. (2022). Highly stable and tunable peptoid/hemin enzymatic mimetics with natural peroxidase-like activities. Nature Communications, 13: 1-13. DOI: 10.1038/s41467-022-30285-9
43. Monahan, M., M. Homer, S. Zhang, R. Zheng, C-L. Chen, J.J. De Yoreo, and B.M. Cossairt. (2022). Impact of nanoparticle size and surface chemistry on peptoid self-assembly. ACS Nano, 16: 8095-8106. DOI: 10.1021/acsnano.2c01203
42. Zhang, S., R. Sadre, B.A. Legg, H. Pyles, T. Perciano, E.W. Bethel, D. Baker, O. Rubel, and J.J. De Yoreo. (2022). Rotational dynamics and transition mechanisms of surface-adsorbed proteins. Proceedings of the National Academy of Sciences, 119: 1-10. DOI: 10.1073/pnas.2020242119
41. Jin, B., F. Yan, X. Qi, B. Cai, J. Tao, X. Fu, S. Tan, P. Zhang, J. Pfaendtner, N.Y. Naser, F. Baneyx, X. Zhang, J.J. De Yoreo, and C-L. Chen. (2022). Peptoid-directed formation of five-fold twinned Au nanostars through particle attachment and facet stabilization. Angewandte Chemie, 61: 1-11. DOI: 10.1002.anie.202201980
40. Ziatdinov, M., A. Ghosh, and S.V. Kalinin. (2022). Physics makes the difference: Bayesian optimization and active learning via augmented Gaussian process. Machine Learning Science and Technology, 3: 1-10. DOI: 10.1088/2632-2153/ac4baa
39. Qi, X., Y. Zhao, K. Lachowski, J. Boese, Y. Cai, O. Dollar, B. Hellner, L. Pozzo, J. Pfaendtner, J. Chun, F. Baneyx, and C.J. Mundy. (2022). Predictive theoretical framework for dynamic control of bioinspired hybrid nanoparticle self-assembly. ACS Nano, 16: 1919-1928. DOI: 10.1021/acsnano.1c04923
38. Li, Z., D.K. Tran, M. Nguyen, T. Jian, F. Yan, S.A. Jenekhe, and C-L. Chen. (2022). Amphiphilic peptoid directed self-assembly of oligoanilines into highly crystalline conducting nanotubes. Macro-Molecular Rapid Communications, 43: 1-9. DOI: 10.1002/marc.202100639
37. Zhao, M., K.J. Lachowski, S. Zhang, S. Alamdari, J. Sampath, P. Mu, C.J. Mundy, J. Pfaendtner, J.J. De Yoreo, C-L. Chen, L.D. Pozzo, and A.L. Ferguson. (2022). Hierarchical self-assembly pathways of peptoid helices and sheets. Biomacromolecules, 23: 992-1008. DOI: 10.1021/acs.biomac.1c01385
36. Morozovska, A.N., E.A. Eliseev, A. Biswas, N.V. Morozovsky, and S.V. Kalinin. (2021). Effect of surface ionic screening on polarization reversal and phase diagrams in thin antiferroelectric films for information and energy storage. Physical Review Applied, 16: 1-18. DOI: 10.1103/PhysRevApplied.16.044053
35. Biswas, A., A.N. Morozovska, M. Ziatdinov, E.A. Eliseev, and S.V. Kalinin. (2021). Multi-objective Bayesian optimization of ferroelectric materials with interfacial control for memory and energy storage applications. Journal of Applied Physics, 130: 1-20. DOI: 10.1063/5.0068903
34. Zhao, M. (2021). Hierarchical assemblies of polypeptoids for rational design of advanced functional nanomaterials. Biopolymers, 112: 1-14. DOI: 10.1002/bip.23469
33. Zhu, J., N. Avakyan, A. Kakkis, A. Hoffnagle, K. Han, Y. Li, Z. Zhang, T. Choi, Y. Na, C-J Yu, and F.A. Tezcan. (2021). Protein assembly by design. Chemical Reviews, 121: 13701-13796. DOI: 10.1021/acs.chemrev.1c00308
32. Li, Z., B. Cai, W. Yang, and C-L. Chen. (2021). Hierarchical nanomaterials assembled from peptoids and other sequence-defined synthetic polymers. Chemical Reviews, 121: 14031-14087. DOI: 10.1021/acs.chemrev.1c00024
31. Lee, D.C., K.N. Guye, R.K. Paranji, K. Lachowski, L.D. Pozzo, D.S. Ginger, and S.H. Pun. (2021). Dual-stimuli responsive single-chain polymer folding via intrachain complexation of tetramethoxyazobenzene and β-cyclodextrin. Langmuir, 37: 10126-10134. DOI: 10.1021/acs.langmuir.1c01442
30. Muckel, F., K.N. Guye, S.M. Gallagher, Y. Liu, and D.S. Ginger. (2021). Tuning hybrid exciton-photon fano resonances in two-dimensional organic-inorganic perovskite thin films. Nano Letters, 21: 6124-6131. DOI: 10.1021/acs.nanolett.1c01504
29. Guye, K.N., H. Shen, M.Y. Yaman, G.Y. Liao, D. Baker, and D.S. Ginger. (2021). Importance of substrate-particle repulsion for protein-templated assembly of metal nanoparticles. Langmuir, 37: 9111-9119. DOI: 10.1021/acs.langmuir.1c01194
28. Yaman, M.Y., K.N. Guye, M. Ziatdinov, H. Shen, D. Baker, S.V. Kalinin, and D.S. Ginger. (2021). Alignment of Au nanorods along de novo designed protein nanofibers studied with automated image analysis. Soft Matter, 17: 6109-6115. DOI: 10.1039/D1SM00645B
27. Yang, W., Q. Yin and C-L. Chen. (2021). Designing sequence-defined peptoids for biomimetic control over inorganic crystallization. Chemistry of Materials, 33: 3047-3065. DOI: 10.1021/acs.chemmater.1c00243
26. Prelesnik, J.L., R.G. Alberstein, S. Zhang, H. Pyles, D. Baker, J. Pfaendtner, J.J. De Yoreo, F.A. Tezcan, R.C. Remsing, and C.J. Mundy. (2021). Ion-dependent protein-surface interactions from intrinsic solvent response. Proceedings of the National Academy of Sciences, 118: 1-9. DOI: 10.1073/pnas.2025121118
25. Pushpavanam, K., B. Hellner, and F. Baneyx. (2021). Interrogating biomineralization one amino acid at a time: Amplification of mutational effects in protein-aided titania morphogenesis through reaction-diffusion control. Chemical Communications, 57: 4803-4806. DOI: 10.1039/D1CC01521D
24. Pushpavanam, K., J. Ma, Y. Cai, N.Y. Naser, and F. Baneyx. (2021). Solid-binding proteins: Bridging synthesis, assembly, and function in hybrid and hierarchical materials fabrication. Annual Review of Chemical and Biomolecular Engineering, 12: 333-357. DOI: 10.1146/annurev-chembioeng-102020-015923
23. Wang, M., Y. Song, S. Zhang, X. Zhang, X. Cai, Y. Lin, J.J. De Yoreo, and C-L. Chen. (2021). Programmable two-dimensional nanocrystals assembled from POSS-containing peptoids as highly efficient artificial light-harvesting systems. Science Advances, 7: 1-8. DOI: 10.1126/sciadv.abg1448
22. Kalinin, S.V., S. Zhang, M. Valetti, H. Pyles, D. Baker, J.J. De Yoreo, and M. Ziatdinov. (2021). Disentangling rotational dynamics and ordering transitions in a system of self-organizing protein nanorods via rotationally invariant latent representations. ACS Nano, 15: 6471-6480. DOI: 10.1021/acsnano.0c08914
21. Ma, J., B. Cai, S. Zhang, T. Jian, J.J. De Yoreo, C-L. Chen, and F. Baneyx. (2021). Nanoparticle-mediated assembly of peptoid naonsheets functionalized with solid-binding proteins: Designing heterostructures for hierarchy. Nano Letters, 21: 1636-1642. DOI: 10.1021/acs.nanolett.0c04285
20. Monahan, M., B. Cai, T. Jian, S. Zhang, G. Zhu, C-L Chen, J.J. De Yoreo, and B. Cossairt. (2021). Peptoid-directed assembly of CdSe Nanoparticles. Nanoscale, 13: 1273-1282. DOI: 10.1039/D0NR07509D
19. Ziatdinov, M., S. Zhang, O. Dollar, J. Pfaendtner, C.J. Mundy, X. Li, H. Pyles, D. Baker, J.J. De Yoreo, and S.V. Kalinin. (2021). Quantifying the dynamics of protein self-organization using deep learning analysis of atomic force microscopy data. Nano Letters, 21: 158-165. DOI: 10.1021/acs.nanolett.0c03447
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17. Alamdari, S., S.J. Roeters, T.W. Golbek, L. Schmüser, T. Weidner, and J. Pfaendtner. (2020). Orientation and conformation of proteins at the air-water interface determined from integrative molecular dynamics simulations and sum frequency generation spectroscopy. Langmuir, 36: 11855-11865. DOI: 10.1021/acs.langmuir.0c01881
16. Sampath, J., S. Alamdari, and J. Pfaendtner. (2020). Closing the gap between modeling and experiments in the self-assembly of biomolecules at interfaces and in solution. Chemistry of Materials, 32: 8043-8059. DOI: 10.1021/acs.chemmater.0c01891
15. Zhao, M., J. Sampath, S. Alamdari, G. Shen, C-L. Chen, C.J. Mundy, J. Pfaendtner, and A.L. Ferguson. (2020). MARTINI-compatible coarse-grained model for the mesoscale simulation of peptoids. The Journal of Physical Chemistry B, 124: 7745-7764. DOI: 10.1021/acs.jpcb.0c04567
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8. Sampath, J., A. Kullman, R. Gebhart, G. Drobny, and J. Pfaendtner. (2020). Molecular recognition and specificity of biomolecules to titanium dioxide from molecular dynamics simulations. npj Computational Materials, 6: 1-8. DOI: 10.1038/s41524-020-0288-7
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5. Luo, Y., Y. Song, M. Wang, T. Jian, S. Ding, P. Mu, Z. Liao, Q. Shi, X. Cai, H. Jin, D. Du, W-J Dong, C-L. Chen, and Y. Lin. (2019). Bioinspired peptoid nanotubes for targeted tumor cell imaging and chemo-photodynamic therapy. Small, 15: 1-8. DOI: 10.1002/smll.201902485
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1. Dunakey, S.J.G., B.L. Coyle, A. Thomas, M. Xu, B.J.F. Swift, and F. Baneyx. (2019). Selective labeling and decoration of the ends and sidewalls of single-walled carbon nanotubes using mono- and bispecific solid-binding fluorescent proteins. Bioconjugate Chemistry, 30: 959-965. DOI: 10.1021/acs.bioconjchem.9b00097
SUBMITTED AND ACCEPTED PAPERS
The following papers are in-prep, have been submitted, or are accepted for publication in peer-reviewed journals.
Impact of Colloidal Forces and Broken Symmetry on the Design of a Protein-Material Interface. Sakshi Yadav Schmid, Benjamin Helfrecht, Amy Stegmann, Benjamin A. Legg, Harley Pyles, Jiajun Chen, John R. Edison, Maxim Ziatdinov, Zdenek Preisler, Orion Dollar, Stephen Whitelam, Sergei Kalinin, David Baker, Christopher J. Mundy, Shuai Zhang, and James De Yoreo. (Submitted)
Active Deep Kernel Learning of Molecular Functionalities: Realizing Dynamic Structural Embeddings. Ghosh, A., M. Ziatdinov, and S.V. Kalinin. (Submitted)
Rapid optimization in high dimensional space by deep kernel learning augmented genetic algorithms. Valleti, M., A. Raghavan, and S.V. Kalinin. (Submitted)
Unsupervised Reward-Driven Image Segmentation in Automated Scanning Transmission Electron Microscopy Experiments. Barakati, K., U. Pratiush, A.C. Houston, G. Duscher and S.V. Kalinin. (Submitted)
Steric Modulation of Protein-Mediated Nanoparticle Assembly: Controlling Cluster Size, Polydispersity and FRET Responses. Cai, Y., W. Idso, W.C. Wixson, N.Y. Naser, Z. Lin and F. Baneyx. (Submitted)
Leveraging Hydration Forces for Size-Specific Nanoparticle Enrichment With a Redox-Responsive Silica-Binding Elastin-Like Polypeptide: From Steric Repulsion to Bridging Flocculation through Disulfide Reduction. Lin, Z. and F. Baneyx. (Submitted)
Validating a computational model of a de novo protein template for CaCO3 with ssNMR. Emily G. Saccuzzo-Close, Andrew Lipton, Harley Pyles, Hoang Trinh, Ying Chen, Garry Buchko, David Baker, Wendy Shaw. (In prep)
De novo design of metal-oxide templating proteins. Amijai Saragovi, Harley Pyles, Timothy F. Huddy, Wenzhao Dai, Xinqi Li, Andrew J. Borst, Nikita Hanikel, Alexis Courbet, Paul Kwon, Fátima A. Dávila-Hernández, Ryan Kibler, Dionne K. Vafeados, Aza Allen, Kenneth D. Carr, Asim K. Bera, Alex Kang, Evans Brackenbrough, Sakshi Schmid, Yuna Bae, Lance Stewart, Shuai Zhang, James De Yoreo, David Baker. (Submitted)
Inhibition of ice recrystallization with designed twistless helical repeat proteins. Robbert J. de Haas, Harley Pyles, Timothy F. Huddy, Jannick van Ossenbruggen, Chuanbao Zheng, Daniëlle van den Broek, Ann Carr, Asim K. Bera, Alex Kang, Evans Brackenbrough, Emily Joyce, Banumathi Sankaran, David Baker, Ilja K. Voets, Renko de Vries. (Submitted)
Efficient Analysis of Small-Angle Scattering Curves for Large Biomolecular Assemblies Using Monte Carlo Methods. Huat Thart Chiang, Zhiyin Zhang, Kiran Vaddi, Akif Tezcan, Lilo Pozzo. (Submitted)
Autonomous Phase Mapping of Gold Nanoparticles Synthesis with Differentiable Models of Spectral Shape. Kiran Vaddi, Huat Thart-Chiang, Aleksandra Grey, Zachery Wiley, Lilo Pozzo. (Submitted)
Machine Learning-Guided High Throughput Screening of Car9 Sequence Isomers to Study Sequence-Dependent Binding Behavior. A. Sonpal and J. Pfaendtner. (Submitted)
Controlling the Outcomes of Templated Silicification by Genetic Engineering of a Thermoresponsive Silica-Binding Elastin-Like Polypeptide. W. Wixson, N. Naser, A. Sonpal, J. Pfaendtner, and F. Baneyx. (Submitted)
A Comparative Study of Silica-Binding Peptides on Amorphous Silica and Ordered Quartz. K. Torkelson and J. Pfaendtner. (In Prep)
Exploration of Facet Selectivity in Calcium Phosphate Binding Peptides Using Molecular Dynamics Simulations. K. Torkelson, M. Zorman, and J. Pfaendtner (In Prep)
Templating semiconductor growth with structured de novo protein interfaces. A. Saragovi, H. Pyles, T. Huddy, W. Dai, X. Li, A. Borst, N. Hanikel, A. Courbet, P. Kwon , A. Dávila-Hernández, D. Vafeados, A. Allen, K. Carr, A. Bera, A. Kang , E. Brackenbrough, S.Yadav, Y. Bae, L. Stewart, S. Zhang, J. De Yoreo, D. Baker. (Submitted)