Person:
Grover, Martha A.

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    Optimal Feedback Control of Crystallization
    (Georgia Institute of Technology, 2017-01-24) Grover, Martha A. ; Georgia Institute of Technology. Institute for Electronics and Nanotechnology ; Georgia Institute of Technology. School of Chemical and Biomolecular Engineering
    The organization of a large collection of particles into an ordered crystalline array is needed for many applications, including pharmaceutical separations, nuclear waste disposal, and optoelectronic metamaterials. Due to improvements in sensing technology, it is now becoming possible to monitor the crystalline state in real time during the crystallization process, and this sensor technology opens up new possibilities for feedback control. Here we monitor the crystalline state and use this data to build an empirical model. An optimal feedback policy is then calculated using the empirical model along with dynamic programming. Alternatively, the empirical model can be calculated from simulation “data” coming from a detailed particle-level simulation. Experimental results demonstrating the method will be presented for molecular crystallization and colloidal crystallization.
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    Group Intelligence Audio Track
    ( 2017-04) Parsons, Christopher J. ; Salaita, Meisa K. ; Hughes, Catherine H. ; Lynn, David G. ; Fristoe, Adam ; Fristoe, Ariel ; Grover, Martha A. ; Georgia Institute of Technology. School of Chemical and Biomolecular Engineering
    The Group Intelligence Audio Track as supplemental to the article: "Group Intelligence: An Active Learning Exploration of Diversity in Evolution" in the Journal of Chemical Education (DOI: 10.1021/acs.jchemed.6b00518)
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    Universal sequence replication, reversible polymerization and early functional biopolymers: a model for the initiation of prebiotic sequence evolution
    (Georgia Institute of Technology, 2012-04) Walker, Sara Imari ; Grover, Martha A. ; Hud, Nicholas V. ; Georgia Institute of Technology. Center for Organic Photonics and Electronics ; Georgia Institute of Technology. Center for Chemical Evolution ; Georgia Institute of Technology. School of Chemical and Biomolecular Engineering ; Georgia Institute of Technology. School of Chemistry and Biochemistry
    Many models for the origin of life have focused on understanding how evolution can drive the refinement of a preexisting enzyme, such as the evolution of efficient replicase activity. Here we present a model for what was, arguably, an even earlier stage of chemical evolution, when polymer sequence diversity was generated and sustained before, and during, the onset of functional selection. The model includes regular environmental cycles (e.g. hydration-dehydration cycles) that drive polymers between times of replication and functional activity, which coincide with times of different monomer and polymer diffusivity. Template-directed replication of informational polymers, which takes place during the dehydration stage of each cycle, is considered to be sequence-independent. New sequences are generated by spontaneous polymer formation, and all sequences compete for a finite monomer resource that is recycled via reversible polymerization. Kinetic Monte Carlo simulations demonstrate that this proposed prebiotic scenario provides a robust mechanism for the exploration of sequence space. Introduction of a polymer sequence with monomer synthetase activity illustrates that functional sequences can become established in a preexisting pool of otherwise non-functional sequences. Functional selection does not dominate system dynamics and sequence diversity remains high, permitting the emergence and spread of more than one functional sequence. It is also observed that polymers spontaneously form clusters in simulations where polymers diffuse more slowly than monomers, a feature that is reminiscent of a previous proposal that the earliest stages of life could have been defined by the collective evolution of a system-wide cooperation of polymer aggregates. Overall, the results presented demonstrate the merits of considering plausible prebiotic polymer chemistries and environments that would have allowed for the rapid turnover of monomer resources and for regularly varying monomer/polymer diffusivities.
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    Model reduction and control of state-affine probabilistic systems for atomic-scale dynamics
    (Georgia Institute of Technology, 2004-03-15) Grover, Martha A. ; Georgia Institute of Technology. Office of Sponsored Programs ; Georgia Institute of Technology. School of Chemical and Biomolecular Engineering ; Georgia Institute of Technology. Office of Sponsored Programs ; Gallivan, Martha Grover
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    Career: a system approach to materials processing
    (Georgia Institute of Technology, 2009-07-30) Grover, Martha A. ; Georgia Institute of Technology. Office of Sponsored Programs ; Georgia Institute of Technology. School of Chemical and Biomolecular Engineering ; Georgia Institute of Technology. Office of Sponsored Programs
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    Prediction and Design in Chemical Evolution
    (Georgia Institute of Technology, 2013-09-10) Grover, Martha A. ; Georgia Institute of Technology. Institute for Bioengineering and Bioscience ; Georgia Institute of Technology. School of Chemical and Biomolecular Engineering
    Discrete atoms and molecules interact to form macromolecules and even larger mesoscale assemblies, ultimately yielding macroscopic structures and properties. A quantitative relationship between the nanoscale discrete interactions and the macroscale properties is required to design, optimize, and control such systems; yet in many applications, predictive models do not exist or are computationally intractable.