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When contrasted with natural biopolymers, it is clear that our ability to design soft materials with comparable structural, electronic, and ionic functionalities is severely limited. The design of these materials would be greatly facilitated by predictive models that capture multiscale structure-function relationships; however, such efforts require the challenging integration of an ensemble of theoretical and computational techniques to accurately describe the electronic, nuclear, and mesoscopic degrees of freedom that influence material performance. My research focuses on the development of predictive multiscale computational methodologies that accurately characterize structural, electronic, and ionic phenomena in soft materials, with the goal of advancing rational design strategies for functional soft materials.

My research group will operate at the intersection of engineering, chemistry, and physics, enabling us to study fundamental and applied problems at multiple spatial and temporal resolutions. My initial research efforts will comprise three areas:

• I will develop and apply multiscale computational models that treat electronic and reactive phenomena at coarse-grained spatiotemporal resolutions. These methodological developments will dramatically enhance the length and timescales for chemically-predictive coarse-grained modeling of electronic and reactive phenomena. Specific target applications will include mechanically-induced bond-breaking and triboelectricity in polymers, morphology-dependent electronic structure in organic semiconductors, and polymer chemical degradation pathways.
• I will apply multiscale simulation techniques to design the conformational and morphological properties of bioelectronics polymers (conjugated polyelectrolytes), as well as to quantify their combined electronic and ionic transport properties.. The utility of organic polymers for combined electronic and ionic conductivity, and the fundamental mechanisms underlying mixed conductivity in organic materials, are currently unexplored.
• I will apply multiscale computational techniques to understand the mechanisms of contact electrification and design new materials with optimized triboelectric properties. Triboelectricity (static electricity) is one of the least understood and most prevalent physical properties of organic materials. Despite the acute influence of nanoscale structure on contact electrification, the role of bond-breaking, ion transfer, and electron transfer are unexplored at a molecular scale.

Teaching Interests: In addition to my research interests, I am a committed educator. As an undergraduate at Wesleyan University, I co-designed a course on the Physics of Sustainability in addition to serving as a teaching assistant for General Physics I & II. I continued my pedagogical development at Northwestern University by completing the Northwestern Teaching Certificate Program, as well as being a teaching assistant for a variety of graduate and undergraduate chemistry courses. As a post-doc at the University of Chicago, I co-instructed the Introduction to Molecular Modeling course for molecular engineering Ph.D. students.

Background: I received my Ph.D. in 2016 from Northwestern University working as a NSF GRFP fellow and Northwestern Presidential fellow with Profs. Mark Ratner and Lin Chen. My graduate work focused on the development of models characterizing self-assembly, photophysics, and electronic transport in organic semiconductors. I then began a postdoc with Prof. Juan de Pablo in the summer of 2016 and was subsequently awarded the Maria Goeppert Mayer Fellowship in the Materials Sciences Division at Argonne National Laboratory, which allowed me to function as an independent researcher. My postdoctoral work has concerned the development of statistical sampling and coarse-graining algorithms, machine learning-enhanced simulation, and the structure and dynamics of polymeric and glassy interfaces. This postdoctoral work has been recognized by the 2019 MRS Postdoctoral Award and the 2019 ACS PHYS Young Investigator Award.

Successful Proposals: Argonne LDRD Named Fellow Call, NSF Graduate fellowship, UChicago Research Computing Cluster, Argonne Laboratory Computing Resource Center.

Selected Publications:

1. Jackson, N.E.; Bowen, A.S.; Antony, L.A.; Webb, M.A.; Vishwanath, V.; de Pablo, J.J. “Electronic Structure at Coarse-Grained Resolutions from Supervised Machine Learning,” Adv., 2019, 5 (3); eaav1190.
2. Yu, J.*; Jackson, N.E.*; Xu, X.; Morgenstern, Y.; Kaufman, Y.; Ruths, M.; de Pablo, J.J.; Tirrell, M. “Multivalent counterions diminish the lubriity of polyelectrolyte brushes,” Science, 2018, 360 (6396), pp 1434-1438.
3. Jackson, N.E.; Chen, L.X.; Ratner, M.A. “Charge Transport Network Dynamics in Molecular Aggregates,” Natl. Acad. Sci., 2016, 113 (31), pp 8595-8600.
4. Jackson, N.E.; Kohlstedt, K.L.; Savoie, B.M.; Olvera de la Cruz, M.; Schatz, G.C.; Chen, L.X.; Ratner, M.A. “Conformational Order in Aggregates of Conjugated Polymers,” J. Am. Chem. Soc., 2015, 137 (19), pp 6254-6262.