Nicholas Kotov
University of Michigan, MI·Materials Science
Matter built from particles, from Roman cement to modern 3D-printed composites, has shaped technology for millennia, yet there is still no general theory that predicts what a jumble of mismatched particles will do once assembled. A related gap exists in biology and medicine: the molecules being used as drugs and disease markers keep getting bigger, from antibodies to packaged nucleic acids to exosomes and whole immune cells, and conventional light-based analysis struggles with structures that large.
- Fields
Materials Science
Engineering
Chemistry
- Topics
chiral nanostructures
chirality
second-harmonic generation
- Grants
- 2 known grants, through Aug 2028
What they work on
- Develop CHIRON, a chiroptical second-harmonic light scattering method, by exploiting the giant nonlinear optical response of chiral nanostructures, whose lack of central symmetry makes signals strong enough to read from a single particle.
- Form biocomplexes between chiral nanoparticles and large biological targets such as antibodies, liposomes, exosomes and immune cells, and use single-particle multiplexing for rapid, label-free, high-throughput identification.
- Deconvolute the nonlinear optical signal using a tensorial description of nonlinearity parameters that separates direction-dependent components, and implement a quantum light source with entangled photons to widen applicability.
- Build graph-theoretical descriptions of colloidal ensembles made of particles with complex shapes and varied spatiotemporal arrangements, adapting network theory tools from social and economic networks to particle-based matter.
- Establish quantitative relationships between graph representations of colloidal structure and mechanical, electrical and chemical properties, validating predictions on model particle systems at macro, micro and nanoscales.
- Explore how emergence, self-assembly and criticality in communities of strongly interacting polydisperse particles generate complex structures, and translate the results into additive manufacturing case studies.
More about the research
Two projects address these gaps, one building a mathematical and computational framework for complex particle systems, the other turning the optical properties of twisted nanoparticles into a tool for identifying large biological structures.
Why it matters
Antibody drugs, exosomes and circulating immune cells are increasingly used as therapies and disease markers but are hard to detect and characterize with existing methods; a label-free, single-particle optical technique could give faster and more selective identification of these targets. On the materials side, a predictive framework linking particle-level structure to bulk mechanical, electrical and chemical properties could guide 3D printing and other additive manufacturing with real, imperfect particle feedstocks rather than idealized ones.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Shaul Mukamel
University of California-Irvine, CA·Chemistry
Develop models and computational tools to predict and interpret spectroscopy signals made with entangled photons, combining electronic structure and quantum dynamics simulations.
Yamuna Phal
Colorado School of Mines, CO·Chemistry
Build a mid-infrared imaging instrument capable of non-destructive, spatially resolved analysis of chiral drug interactions inside biological tissues, using molecules' infrared absorption as a chemical fingerprint.
Patrick Vaccaro
Yale University, CT·Chemistry
Measure electronic circular birefringence of isolated, solvent-free chiral molecules using cavity ring-down polarimetry, a mirror-cavity method sensitive to tiny polarization rotations, to benchmark theoretical predictions of optical activity.
The school
University of Michigan: 124 labs on PI Pages, $2.1B a year on research, 963 research doctorates a year.
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