Colloquia

¡MIRA!, NCI & APMS Fall 2021 Colloquium Schedule

Find the link here for a public calendar so you can track Colloquia events in your calendar of choice. 

Zoom links can be accessed by clicking the title of the talks below.

Meeting ID: 868 5115 5434

Password: 229703


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  • 2021
    9th September

    Martin Kirk UNM: Donor-Acceptor Systems Provide Insight into Charge Separation, Charge Transport, and Excited State Processes

    4:00 PM MST
    Location: Science and Health Building (Bldg #36), Room 106

    Abstract: Excited state interactions in spin-containing Donor-Acceptor and Donor-Bridge-Acceptor systems are important for understanding the impact of electronic coupling (Hab) on molecular electronics and how magnetic exchange interactions affect excited state processes. Our efforts have focused on determining excited state contributions to molecular bridge mediated electronic coupling, understanding how open-shell excited state singlet configurations promote long-range electron correlation, correlating magnetic exchange with molecular conductance, and developing new platforms for spin control of excited state dynamics in photoexcited donor-acceptor molecules. Using novel Donor-Bridge-Acceptor biradical and related complexes, we have been able to test recent theoretical hypotheses in molecular electronics as they relate to coherent superexchange in electron transfer/transport conduits, spin-polarized electron transport, and the control of quantum interference effects. Radical elaborated transition metal complexes represent ideal platforms for exploring the relationship between photoinduced charge separation and long-range spin correlation, impacting the solar energy, organic lighting, and molecular spintronics fields. These systems are also relevant to the emerging molecular quantum information science (QIS) field, allowing for the optical generation and manipulation of spin qubits. Here we will show how a combined spectroscopic and magentic approach, augmented by detailed bonding calculations, has provided keen insight into the electronic structure of these novel radical containing complexes in order to further our understanding of molecular electronic systems at the nanoscale.

  • 2021
    16th September

    Andrew White URochester: Iterative Peptide Discovery with Maximum Entropy Methods and Deep Learning

    4:00 PM MST
    Location: Science and Health Building (Bldg #36), Room 106

    The use of artificial intelligence for molecular design has been rapidly advancing. New generative models propose novel molecular structures to test, and deep learning can predict their molecular properties with high accuracy. The goal for these algorithms is optimizing a property by training against a large database of previously measured molecules. A major limitation is that these methods are not designed to be used concurrently with experiments and improving their accuracy as experimental data is gathered is non-trivial. Our research is focused on iterative molecular design where experiments are done concurrently instead of post-hoc in molecular design. This is accomplished by using maximum entropy biasing methods that can update predictive physics-based models with new experimental results.1 This improves predictive accuracy and ensures interpretable models. Another challenge is the scarcity of data in molecular design. We are exploring with this with advances from few-shot learning, like meta-learning.2 Meta-learning translates experience from past related systems to new ones, minimizing the number of molecules necessary to train models. I will present results of these methods applied to peptides where we have studied a variety of tasks including antimicrobial, antifouling, and solubility predictions. Peptides are a model system because there is no ambiguity in encoding and generating them because they are linear biopolymers made of 20 amino acid monomers. 1. Experimentally Consistent Simulation of Aβ21–30 Peptides with a Minimal NMR Bias. DB Amirkulova, M Chakraborty, AD White - The Journal of Physical Chemistry B, 2020 2. Investigating Active Learning and Meta-Learning for Iterative Peptide Design. R Barrett, AD White - Journal of chemical information and modeling, 2021 3. Sequence, structure, and function of peptide self-assembled monolayers. AK Nowinski, F Sun, AD White, AJ Keefe, S Jiang - Journal of the American Chemical Society, 2012.

  • 2021
    23rd September

    Helen Maynard-Casely Australian Centre for Neutron Scattering: Cryomineralogy, like mineralogy only cooler

    4:00 PM MST
    Location: Science and Health Building (Bldg #36), Room 106

    Cryomineralogy, like mineralogy only cooler. Helen Maynard-Casely Australian Nuclear Science and Technology Organisation, Sydney, Australia Ocean worlds have solid surfaces, and although water ice dominates many of these surfaces it material properties will be heavily influenced by the other chemical species it crystallises with. Moreover, studies of the minerals that form on these surfaces are clues as to what may lie below. Though we cannot yet reach these icy satellites and return a sample to Earth for investigation, we can recreate their simple compositions and extreme conditions in the laboratory. In contrast to terrestrial mineralogy, which has been subject to 100 years of laboratory measurements, we are only beginning to shed light on the range of materials that are formed on the ocean worlds. Through laboratory studies cryominerals have been shown to be just as diverse as silicates in the structures and physical properties that they exhibit [1]. From influence of sulfate on governing what water-rich hydrates form on Europa [2], to the plastic solids of methane and nitrogen that form on Pluto [3]. A new and particularly rich area of discovery recently has been the variety of minerals that are likely to be formed on Saturn’s moon Titan [4] [5]. This contribution will highlight recent developments in cryomineralogy, but also point to where much more laboratory work, and complementary modelling is needed. 1. Fortes, A.D. and M. Choukroun, Phase Behaviour of Ices and Hydrates. Space Science Reviews, 2010. 153(1-4): p. 185-218. 2. Maynard-Casely, H.E., et al., Mineral Diversity on Europa: Exploration of Phases Formed in the MgSO4–H2SO4–H2O Ternary. ACS Earth and Space Chemistry, 2021. 3. Maynard-Casely, H.E., J.R. Hester, and H.E.A. Brand, Re-examining the crystal structure behaviour of nitrogen and methane (in press). IUCrJ, 2020. 4. Maynard-Casely, H.E., et al., Prospects for mineralogy on Titan. American Mineralogist, 2018. 103(3): p. 343-349. 5. Cable, M.L., et al., Titan in a Test Tube: Organic Co-crystals and Implications for Titan Mineralogy. Accounts of Chemical Research, 2021: p. 4087-4094.

  • 2021
    30th September

    Mariana Potcoava University of Illinois at Chicago: Use of optical instrumentation for quantitative analysis of cellular biological processes

    4:00 PM MST
    Location: Science and Health Building (Bldg #36), Room 106

    My research is directed to the development of optical instrumentation for biomedical measurements and addresses two broad topics: 1) Holography in tomographic imaging, and 2) Application of Raman spectroscopy in the life sciences. Here, I will discuss our recent advances in building an incoherent detection arm for a Lattice Light-Sheet (LLS) microscope, called Incoherent Holography Lattice Light-Sheet (IHLLS). I will discuss development of this system including characterization of its performance and demonstrate a significant contrast improvement using both beads and neuronal structures within a biological test sample as well as quantitative phase imaging. The IHLLS has similar or better transverse and performance when compared to the LLS technique. In addition, the IHLLS allows for volume reconstruction from fewer z-galvo displacements, thus facilitating faster volume acquisition. I have also worked on a technology that demonstrates the potential of Raman spectroscopy to determine with high accuracy the composition changes of the fatty acids and cholesterol found in the lipid droplets of prostate cancer cells treated with various fatty acids. The methodology uses a modified least-square fitting (LSF) routine that uses highly discriminatory wavenumbers between the fatty acids present in the sample using a new Support Vector Machine (SVM) algorithm.

  • 2021
    7th October

    Manuel Quevedo University of Texas Dallas: Large Area Solid-State Radiation Detectors

    4:00 PM MST
    Location: Science and Health Building (Bldg #36), Room 106

    ABSTRACT The development of low temperature device technologies that have enabled flexible displays also present opportunities for flexible electronics and flexible integrated systems. In this presentation, we discuss fundamental materials properties including crystalline structure, interfacial reactions, doping, etc. defining performance and reliability of perovskite II-VI and oxide-based materials and devices for flexible and large area electronics. Materials characterization methods including RBS, XPS, XRD, etc. are used to analyze materials deposited by pulsed laser deposition, chemical bath deposition and inkjet printing. Finally, we demonstrate an integrated neutron / gamma ray sensor fully fabricated at UT-Dallas that includes wireless communication to a mobile device.

  • 2021
    14th October

    Brian Munsky Colorado State University: Designing Optimal Microscopy Experiments to Harvest Single-Cell Fluctuation Information while Rejecting Image Distortion Effects

    4:00 PM MST
    Location: Science and Health Building (Bldg #36), Room 106

    Abstract: Modern fluorescence labeling and optical microscopy approaches have made it possible to experimentally observe every stage of basic gene regulatory processes, even at the level of individual DNA, RNA, and protein molecules, in living cells, and within fluctuating environments. To complement these observations, the mechanisms and parameters of discrete stochastic models can be rigorously inferred to reproduce and quantitatively predict every step of the central dogma of molecular biology. As single-cell experiments and stochastic models become increasingly more complex and more powerful, the number of possibilities for their integrated application increases combinatorically, requiring efficient approaches for optimized experiment design. In this presentation, we will introduce two model-driven experimental design approaches: one based on detailed mechanistic simulations of optical experiments, and the other on a new formulation of Fisher Information for discrete stochastic process models. Using combinations of real biological experiments and realistic simulated data for single-gene transcription and single-RNA translation, we will demonstrate how experiment design approaches can be reformulated to account for non-gaussian noise within individual cells as well as for non-trivial measurement noise effects due to optical distortions and image processing errors. Bio: Dr. Munsky received B.S. and M.S. degrees in Aerospace Engineering from the Pennsylvania State University in 2000 and 2002, respectively, and his Ph.D. in Mechanical Engineering from the University of California at Santa Barbara in 2008. Following his graduate studies, Dr. Munsky worked at the Los Alamos National Laboratory — as a Director’s Postdoctoral Fellow (2008-2010), as a Richard P. Feynman Distinguished Postdoctoral Fellow in Theory and Computing (2010-2013), and as a Staff Scientist (2013). He joined the Department of Chemical and Biological Engineering and the School of Biomedical Engineering as an Assistant Professor in January of 2014 and was promoted to Associate professor in 2020. He Dr. Munsky is best known for his discovery of Finite State Projection algorithm, which has enabled the efficient study of probability distribution dynamics for stochastic gene regulatory networks. Dr. Munsky’s research interests at CSU are in the integration of stochastic models with single-cell experiments to identify predictive models of gene regulatory systems and more complex biological systems, and his research is actively funded by the W M Keck Foundation, the NIGMS (MIRA), and the NSF (CAREER). Dr. Munsky is excited about the future the introduction of tools from physics and engineering into the quantitative study and modeling of biological processes, and he would love to talk about this with you!

  • 2021
    21st October

    Edward Maginn Notre Dame: Understanding the Thermophysical Properties of Charged Fluids Using Molecular Simulations: A Journey from Molten Salts, to Ionic Liquids, and Back Again

    4:00 PM MST
    Location: Science and Health Building (Bldg #36), Room 106

    High temperature molten salts were some of the first liquids to be studied in the 1960s and 1970s using the newly invented methods of molecular dynamics and Monte Carlo simulations. Simple salts such as 1:1 alkali halides were particularly attractive systems to model, given computational and algorithmic limitations of the time and the availability of experimental data against which computed properties are compared. Furthermore, there was a great deal of interest in understanding how charged fluids could be modeled computationally and whether both thermodynamic and transport properties could be captured using potentials that consisted of separate terms to treat long-range Coulombic interactions and shorter-ranged repulsion and dispersion interactions. Despite their importance in applications such as metal processing, heat transfer, and nuclear power, molten salt research fell out of favor, only to be replaced at the turn of the 21st century by low temperature “ionic liquids” – a new type of molten salt that was liquid at room temperature. Ionic liquids share many of the same properties as their high temperature cousins, but they also can have both polar and non-polar domains, giving them some unique solvation properties. Due to their low melting temperature, it is also much easier to study ionic liquids than molten salts. In this talk, I will demonstrate how molecular simulations can help us understand how the thermophysical properties of high temperature molten salts and low temperature ionic liquids depend upon things such as structure, charge density, and composition. Motivated by applications such as battery electrolytes, solvents for gas separations, and safer nuclear energy generation, I will show how molecular simulations, machine learning, and advanced experimental characterization methods are helping us better understand these fascinating charged fluids.

  • 2021
    28th October

    Doug Shepherd ASU: Scalable, high-speed, 3D imaging of molecular biology in action

    4:00 PM MST
    Location: Science and Health Building (Bldg #36), Room 106

    ABSTRACT: Continued advancements in biomedical optical microscopy and fluorescent labeling techniques have enabled multi-dimensional visualization of biology in action at the single-molecule level. For example, multiple large-scale efforts are currently underway to create nanoscale spatial maps of thousands of individual RNA and protein species in millions of cells across all human organs. Many of the experiments across these efforts rely on multiplexed fluorescence molecular imaging. The quality and confidence of biological knowledge extracted from the resulting digital images depend on the molecular labeling strategy, the optical microscope's design, and detector choices. Compromises are often necessary to achieve the required volume, imaging speed, number of molecules, samples, or other biologically driven experimental design criteria. Such compromises inevitably increase uncertainty when quantifying molecular identity and dynamics. I will discuss our recent efforts to reduce uncertainty in quantitative molecular imaging through improvements to the optical methods and computational tools used for high-speed, high-resolution, multiplexed, and volumetric fluorescence molecular imaging. Our efforts include a high numerical aperture oblique plane microscopy framework for 3D spatial transcriptomics in human tissue and a digital micromirror-based structured illumination microscopy framework for live-cell, sub-diffraction limited imaging. BIO: Douglas Shepherd is an assistant professor in the Center for Biological Physics and the Department of Physics at Arizona State University. Prior to joining Arizona State University, he was an assistant professor in the Departments of Physics and Pharmacology at the University of Colorado Denver Anschutz Medical Campus from 2013-2019. He received his Ph.D. in Physics from Colorado State University and was a postdoctoral fellow at the Center for Integrated Nanotechnologies and Center for Nonlinear Studies at Los Alamos National Laboratory from 2011-2013. The focus of his research is developing quantitative imaging and statistical inference tools to build predictive models of genetic regulation in multi-cellular systems.

  • 2021
    4th November

    Claire White Princeton: Department of Civil and Environmental Engineering and the Andlinger Center for Energy and the Environment, Princeton University

    4:00 PM PST
    Location: Science and Health Building (Bldg #36), Room 106

    ABSTRACT: With the world facing a climate crisis due to increasing CO2 emissions, there is pressing need to develop and implement sustainable construction/engineering materials across the globe. Alkali-activated materials (AAMs) are one such sustainable alternative to conventional Portland cement concrete; yet questions remain regarding the long-term behavior of AAMs. Furthermore, for Portland cement, the use of extensive clinker substitution to reduce CO2 emissions has led to changes to the underlying chemistry of the main binder gel (calcium-silicate-hydrate, C-S-H, gel), where it is uncertain how these novel supplementary cementitious materials augment the long-term behavior (e.g., gel stability and pore structure) of the cement binder. In this talk, I will outline how fundamental materials science research is being used to address the long-term behavior unknowns of AAMs and certain Portland cement-based systems, where we are linking key experimental techniques with atomistic and larger length scale simulations. In particular, to assess gel stability in calcium-rich AAMs, we have used density functional theory (DFT), synchrotron-based X-ray pair distribution function (PDF) analysis and nuclear magnetic resonance (NMR) to investigate the influence of alkali and alumina incorporation on the structure and thermodynamics of C-S-H gel. The DFT results point toward a clear upper limit for sodium incorporation, beyond which the stability of the phase is compromised, while the experimental results show how alumina can be utilized to combat the destabilizing effects of sodium. We have also used DFT to uncover the early stage formation behavior of C-S-H gel and the influence of sodium and alumina, which has led to a tentatively proposed formation mechanism of the gel. SPEAKER BIO: Claire White is an associate professor in the Department of Civil and Environmental Engineering and the Andlinger Center for Energy and the Environment, and is the acting associate director for research in the Andlinger Center for Energy and the Environment. She holds associated faculty status in the Departments of Chemical and Biological Engineering, and Mechanical and Aerospace Engineering, the Princeton Institute for the Science and Technology of Materials, High Meadows Environmental Institute, and Princeton Institute for Computational Science and Engineering. She completed her graduate studies in 2010 at the University of Melbourne supported by an Australian Postgraduate Award from the Australian government. After receiving her PhD, she worked as a postdoc at Los Alamos National Laboratory and was awarded a Director’s Postdoctoral Fellowship to research the atomic structure of low-CO2 alkali-activated materials. In 2013 she joined Princeton University. White’s research focuses on understanding and optimizing engineering and environmental materials, including sustainable cements and materials for carbon capture, utilization and storage. One main thrust of her research portfolio entails the discovery and control of the chemical mechanisms responsible for formation and long-term degradation of low-CO2 cements and related systems. A second thrust is the development of new 2D materials for carbon capture with significantly reduced energy requirements for material regeneration. This research spans multiple length and time scales, utilizing advanced synchrotron and neutron-based experimental techniques, and includes the use and development of atomic and mesoscale simulation methodologies. Professor White is the recipient of a number of awards including an NSF CAREER Award, the RILEM Gustavo Colonnetti Medal, and the Howard B. Wentz Jr. Junior Faculty Award (Princeton University), and has been listed numerous times on the Princeton Engineering Commendation List for Outstanding Teaching.

  • 2021
    11th November

    Grad students date 1: TBA

    4:00 PM PST
    Location: Science and Health Building (Bldg #36), Room 106

  • 2021
    18th November

    Grad students date 2: TBA

    4:00 PM PST
    Location: Science and Health Building (Bldg #36), Room 106

  • 2021
    2nd December