CAREER: Bio-inspired Nonequilibrium Design Principles of Molecular Information Machines

NONTECHNICAL SUMMARY

This CAREER Award supports the research and integrated educational efforts toward developing a new theoretical framework to guide the design of intelligent, responsive materials that mimic living organisms. Intelligent responses allow an entity to smartly discern and respond to the complex spatial and temporal changes of surroundings. For example, a bacterium can actively gather information from the environment and swim toward foods or flee from toxins. Such intelligent responses, ubiquitously observed in living organisms, must operate far from the steady state of thermal equilibrium. So, they cannot be described by the equilibrium theory of classical thermodynamics. Instead, a novel non-equilibrium theory is required to explain and predict the intelligent responsiveness in the fundamental building blocks of materials – molecules.

The main aim of this project is to develop a non-equilibrium theory to quantitatively predict the intelligence of a molecule's response to external stimuli. The theory will capture the relationship between the intelligence of the molecule's response, its robustness to environmental noise, and how far it needs to be driven away from thermal equilibrium. To accomplish this aim, the research team will combine numerical simulation techniques with the modern theory of non-equilibrium physics. In addition, the team will construct generic toy models that distill the essential dynamics of molecules' non-equilibrium responses. This project will lead to a set of fundamental and generic statements and predictions as design principles for intelligent materials. These activities will provide students with a cross-disciplinary training program combining mathematics, statistical physics, chemistry, and biophysics and mentorship and professional development skills.

The PI and the research team will partner with the Morehead Planetarium and Science Center at the University of North Carolina-Chapel Hill to engage the public. This collaboration involves outreach activities such as Family Science Day and Launch Lab events to make the scientific principles behind the research available to the students and teachers in middle schools, kids and families, and the public.

TECHNICAL SUMMARY

This CAREER Award supports the research and integrated education to elucidate the design of microscopic information machines that autonomously sense, memorize, and respond to spatiotemporal patterns of external stimuli, such as pH, temperature, and chemical environments. These microscopic machines will serve as fundamental building blocks of next-generation novel materials and smart nano-robots. Attaining this goal will transform the field of novel functional and active materials by imparting life-like attributes to otherwise inert molecular complexes and deepen our understanding of thermodynamics, information, and intelligence in the chemistry, biology, and material science communities.

Living organisms, maintained far from equilibrium by constantly dissipating energy and producing entropy, can actively sense, memorize, and respond to complex information hidden in environmental conditions. Biological systems have evolved to utilize diverse ingenious nonequilibrium mechanisms to maintain robust and accurate performance, typically at the cost of energy dissipation or the speed of response. The strategic goal of the research is to elucidate nonequilibrium mechanisms of energy extraction, information sensing and storage, noise resistance, and robustness in connection to entropy production and to develop a universal theory to predict and optimize the performance of generic microscopic information machines. Specifically, this research will address the following questions: What are the general nonequilibrium thermodynamic principles behind these mechanisms? What are the possible mechanisms to better extract and dissipate energy for the optimal performance of smart materials and intelligent molecular complexes? What can one learn from the physical understanding of biological systems to help the design of artificial molecular complexes to achieve similar or better information processing?

The specific aims of the research are to (1) use a hybrid energy landscape approach to describe the nonequilibrium flows of energy caused by a time-varying environment, and (2) find the thermodynamic limit of memory capacity in macromolecular complexes and general relation between the ability of pattern recognition and system's energy-landscape complexity as reflected in its topology and geometry, and (3) lift the ideal-environment assumption to include the backaction from the system and the thermal fluctuations, and understand the counter-intuitive stochasticity induced comprehensive sensing mechanism.

The research activities are closely integrated with education and outreach efforts: both graduate and undergraduate students will be exposed to cutting-edge tools and concepts via direct involvement participation in a novel course module of 'thermodynamics of information processing' that is to be included in the re-designed course 'Thermodynamics and Introduction to Thermal Statistics'. The PI will collaborate with the Center for Faculty Excellence at UNC to acquire knowledge and guidance regarding the up-to-date educational tools and methodologies and obtain frequent quantifiable evaluations to guarantee the success of the re-designed course. The PI and the research team will work with visitors and high school teachers and students in North Carolina by collaborating with the Morehead Planetarium and Science Center on Family Science Day and during the Launch Lab events. Morehead will provide evaluation data to the PI that examines the extent to which the event's main communications goals are met and provide further guidance on improving the public's engagement.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.