Abstract: Organic semiconducting polymers present a versatile platform for energy conversion and storage and sensing devices due to tunable optical and transport gaps, compatibility with electrolytes, and scalability via solution processing. The Center for Soft Photoelectrochemical Systems is an Energy Frontier Research Center that focuses on understanding the fundamental factors that control charge and matter transport processes that underpin energy conversion and storage technologies across spatiotemporal scales in scalable, durable, π-conjugated polymer materials. Within SPECS, we aim to establish design rules for robust photocathode systems that elucidate key structure–property relationships related to charge transport, charge transfer and operational durability.

Our initial device employs a bulk heterojunction (BHJ) strategy, combining PTB7-Th (hole transport) and N2200 (electron transport) polymers, deposited on passivated ITO and capped with a hydrogen evolution reaction (HER) catalyst (e.g., Pt or RuO₂), all immersed in an acidic electrolyte. Insights from optoelectronic analogs guide our focus toward enhancing chemical and mechanical interfacial stability and enabling selective charge extraction.

Efforts that will be described in this talk include multiple spectro-electrochemical methods and theoretical efforts to reveal the impact of electrochemical doping and ultimately serve as signatures to drive charge transfer reactions such as solar fuel production. Other highlights will include opportunities to functionalize various interfaces to increase rates of hydrogen evolution. 

Bio: Erin L. Ratcliff is a full professor in the School of Materials Science and Engineering and the School of Chemistry and Biochemistry at the Georgia Institute of Technology and holds a joint appointment at the National Renewable Energy Laboratory. She earned a B.A. in chemistry, mathematics,and statistics in 2003 from St. Olaf College in Northfield, Minnesota, and a Ph.D. in physical chemistry from Iowa State University in 2007. After completing a postdoc at the University of Arizona (2007-2009), she served as a research scientist and research professor in the Department of Chemistry and Biochemistry (2009-2014). She was previously an assistant and associate professor in the Department of Materials Science and Engineering and the Department of Chemical and Environmental Engineering at the University of Arizona (2014- 2024). She joined the faculty at Georgia Tech in 2024. 

Her group, Laboratory for Interface Science for Printable Electronic Materials, uses a combination of electrochemistry, spectroscopies, microscopies and synchrotron-based techniques to understand fundamental structure-property relationships of next-generation materials for energy conversion and storage and biosensing. Materials of interest include metal halide perovskites, π-conjugated materials, colloidal quantum dots and metal oxides. Current research is focused on mechanisms of electron transfer and transport across interfaces, including semiconductor-electrolyte interfaces and durability of printable electronic materials.

Ratliff was also the director of the funded Energy Frontier Research Center (EFRC) titled Center for Soft PhotoElectroChemical Systems (SPECS) and is currently the associate director of scientific continuity for SPECS. She has received several awards for her research and teaching, including the 2023 Da Vinci Fellow and the 2022 College of Engineering Researcher of the Year award at the University of Arizona, She received the Ten at Ten People of Energy Frontier Research Centers DOE Basic Energy Sciences award in 2019 and a Senior Summer Faculty Research Fellowship at the Naval Research Laboratory (2020, 2021, and 2024). Her research program has been funded by the Department of Energy Basic Energy Sciences, the Solar Energy Technology Office, Office of Naval Research, National Science Foundation and the Nano Bio Materials Consortium.

This lecture series commemorates the life and legacy of Professor Susan Odom, an energetic, productive and driven faculty member in the Department of Chemistry from 2011 to 2021. It features speakers noted for outstanding research in Professor Odom’s fields of synthetic and materials chemistry. Visit this page for more information on the Susan A. Odom lecture series.

Abstract: The Air Force Research Laboratory (AFRL) is the primary research and development organization for the United States Department of the Air Force. Our team is developing new materials and manufacturing approaches to enable the next generation of electronic and optoelectronic devices that are critical for national security. Technologies such as integrated photonics, photodetectors, optically activated switches, and electro-optic modulators demand materials with electrical and optical properties that can be precisely tuned. One promising strategy is to combine organic and inorganic components in hybrid material systems, where carefully engineered interfaces can yield properties that are not possible in either component alone.

In this presentation, I will highlight three material platforms under development in the Materials and Manufacturing Directorate at AFRL where these hybrid interfaces play a central role: transition metal dichalcogenides for optical scattering, MXenes for electromagnetic interference shielding, and organic metal halide perovskites for detecting and generating polarized light. In each case, advances in synthesis, processing, and nanoscale to microscale characterization of the organic/inorganic interfaces are key to achieving the desired performance.

Bio: Dr. Joshua Kennedy received his B.Sc. in Physics from the College of Charleston and his Ph.D. in Physics from the University of Utah. Before joining the Air Force Research Laboratory in 2014, he worked at the University of Texas at Dallas and at NASA’s Johnson Space Center. He is now a Senior Research Physicist at AFRL, where he leads the Agile Electronic Materials and Processes Research Team in the Materials and Manufacturing Directorate at Wright-Patterson Air Force Base, Ohio.

Abstract: The Periodic Table is a cornerstone of chemistry, but its validity is challenged by the extreme properties of superheavy elements (SHEs, Z ≥ 104) and actinides (Z > 88). Relativistic effects, stemming from their large nuclear masses, significantly alter their chemical behaviors, potentially limiting the predictive power of the Periodic Table. Recent breakthroughs have provided insights into the chemistry of these elements, including the direct identification of molecular species formed by actinium (Ac, Z = 89) and nobelium (No, Z = 102) ions.

Using a cutting-edge, atom-at-a-time technique at the 88-Inch Cyclotron Facility at Lawrence Berkeley National Laboratory, we have synthesized and characterized molecular species produced by these ions in reactions with H2O and N2. Our findings underscore the importance of direct identification in SHE chemistry experiments and offer new perspectives on the chemical properties of these enigmatic elements.

This presentation will explore the current state of superheavy element chemistry research, highlighting recent advances and future directions for unraveling the mysteries of SHE chemistry. By pushing the boundaries of our understanding, we aim to shed light on the chemical behaviors of these extraordinary elements and challenge our current understanding of the Periodic Table.

Bio: Jennifer Pore leads an innovative gas phase chemistry program at Lawrence Berkeley National Laboratory, where she investigates the fundamental properties of superheavy elements, examining them one atom at a time. A San Francisco native, she earned her Bachelor of Science at Mills College, a women's college in Oakland, CA. She then moved to Canada to complete her Master’s and Ph.D. in nuclear science before returning to California and joining the Lawrence Berkeley team. Her primary research interest focuses on probing the chemical properties of superheavy elements to explore whether the periodic table should be reorganized. Jennifer has recently received a DOE Early Career Award to further investigate the chemistry of superheavy elements.

Abstract: Sensors and actuators are fundamental building blocks of next-generation human-machine interfaces. This talk presents our recent efforts to establish closed-loop, bidirectional communication and feedback within living systems, with an emphasis on the chemical dimension. The first part of the talk introduces a novel class of flexible, miniaturized probes inspired by biofuel cells for monitoring synaptic release of glutamate in the central nervous system. The resulting sensors can detect real-time changes in glutamate within the biologically relevant concentration range. These advances could aid in basic neuroscience studies and translational engineering, as the sensors provide a diagnostic tool for neurological disorders. The second part of the talk presents our recent work on a bio-integrated gustatory interface, “e-Taste,” which addresses the underrepresented chemical dimension in current VR/AR technologies. This system facilitates remote perception and replication of taste sensations through the coupling of physically separated sensors and actuators with wireless communication modules. Together, these efforts aim to advance the co-design of systems capable of capturing signals and providing feedback, addressing the relatively underexplored chemical aspect in many fields.

Bio: Jinghua Li received her B.S. degree in Biological Sciences from Shandong University, China, in 2011. She earned her Ph.D. from Duke University, United States, in chemistry in 2016. She spent 2016–2019 as a postdoctoral fellow at Northwestern University before joining the Department of Materials Science and Engineering at The Ohio State University as an assistant professor in 2019. Her two focus areas are: 1) fundamental understandings on synthesis chemistry and interfacial properties of thin-film materials as bio-interfaces; and 2) engineering efforts on application of these materials for the next generation wearable/implantable biomedical devices to bridge the gap between rigid machine and soft biology. Her faculty position is funded, in part, by the Discovery Themes Initiative in the area of Chronic Brain Injury, which has promoted faculty hires and support of critical materials needs in the areas of imaging, diagnosis, and treatment of brain injury. Dr. Li supports the Center for Design and Manufacturing Excellence, Nanotech West, and the Center for Electron Microscopy and Analysis with her expertise in the function of biomaterials. Dr. Li has been recognized as the 2025 Alfred P. Sloan Research Fellow, 2024 ACS Materials Au Rising Star, 2024 Nanoscale Emerging Investigator, and 2023 OSU Early Career Innovator of the Year. She also received the DARPA Young Faculty Award, NIH Trailblazer Award, OSU Lumley Research Award and OSU Chronic Brain Injury Program Paper of the Year Award.

Abstract: Synthetic DNA nanotechnology facilitates the design and fabrication of nanoscale particles and devices with diverse applications. Leveraging a growing toolkit of DNA self-assembly methods, it is possible to construct both two- and three-dimensional structures ranging from nanometer to micron scales. The biophysical and biochemical properties of DNA — combined with its compatibility with various organic and inorganic nanoparticles and its predictable base-pairing rules — have made it an ideal material for single-molecule studies, photonics, plasmonics, synthetic biology and healthcare applications. In this work, we present our efforts in developing DNA-based platforms to organize inorganic and organic nanoparticles and biosensors precisely. We investigate how these DNA scaffolds can control the positioning and orientation of nanoparticles to enhance their photophysical properties. Additionally, we explore the behavior of DNA nanostructures when introduced into mammalian cell cytosol, a critical step toward creating biocompatible delivery systems for therapeutic and diagnostic purposes. Finally, we will discuss our recent efforts in building gene-encoded DNA nanoparticles, a promising advancement in the development of targeted delivery systems.

Website: https://www.mathurnanolab.com/

Abstract: Molecular characterization of Atmospheric Organic Aerosol (OA) using advanced methods of high-resolution mass spectrometry provides essential insights into the composition, properties, and behavior of chemical constituents, contributing to a more comprehensive understanding of its environmental impacts. These studies have enabled the identification and quantification of specific components of OA, including light-absorbing chromophores, such as phenolic, quinone and nitroaromatic compounds, N-heteroatom compounds, polycyclic aromatic hydrocarbons, etc. Through comprehensive understanding the chemical composition of OA, we can now assess its sources and atmospheric transformations. Recent investigations have also broadened their scope to explore the partitioning of OA species between the particle and gas phases. These measurements yield valuable data on particle-to-gas transition enthalpies and apparent volatilities of individual OA species, crucial for constructing volatility basis sets (VBS). The resulting VBS distributions enable an assessment of equilibrium gas-particle partitioning across various atmospheric conditions of organic mass loadings, temperatures, and pressures relevant to Earth’s atmosphere. Furthermore, novel parameterization models leverage chemical characterization and volatility datasets to evaluate the viscoelastic properties of OA. This comprehensive molecular understanding of OA chemistry is essential for predicting their ability to undergo chemical reactions, partition between gas and particle phases, and impact atmospheric environment and related processes, such as radiative forcing of climate and cloud formation. This presentation will provide an overview of recent advancements in this field and outline future directions for continued research. 

Bio: Professor Alexander Laskin is a Professor in the Department of Chemistry with a courtesy appointment in the Department of Earth Atmospheric and Planetary Sciences at Purdue University in West Lafayette, Indiana. He received his M.Sc. in Mechanical Engineering from St. Petersburg Polytechnical Institute, Russia, and his Ph.D. in Physical Chemistry from The Hebrew University of Jerusalem, Israel. Dr. Laskin’s group advances aerosol and multiphase environmental chemistry with discoveries that reframe sources, composition, and climate/health impacts. 

He is actively involved in the scientific community, serving as a Co-editor of the Atmospheric Chemistry and Physics journal since 2013, and as a member of the Editorial Board for Aerosol Science and Technology and Scientific Reports. His honors include the NASA Honor Award (FIREX-AQ Group Achievement) in 2019 and being named a W.R. Willey Research Fellow of the Environmental Molecular Sciences Laboratory at PNNL in 2018.

Abstract: Molecular characterization of Atmospheric Organic Aerosol (OA) using advanced methods of high-resolution mass spectrometry provides essential insights into the composition, properties, and behavior of chemical constituents, contributing to a more comprehensive understanding of its environmental impacts. These studies have enabled the identification and quantification of specific components of OA, including light-absorbing chromophores, such as phenolic, quinone and nitroaromatic compounds, N-heteroatom compounds, polycyclic aromatic hydrocarbons, etc. Through comprehensive understanding the chemical composition of OA, we can now assess its sources and atmospheric transformations. Recent investigations have also broadened their scope to explore the partitioning of OA species between the particle and gas phases. These measurements yield valuable data on particle-to-gas transition enthalpies and apparent volatilities of individual OA species, crucial for constructing volatility basis sets (VBS). The resulting VBS distributions enable an assessment of equilibrium gas-particle partitioning across various atmospheric conditions of organic mass loadings, temperatures, and pressures relevant to Earth’s atmosphere. Furthermore, novel parameterization models leverage chemical characterization and volatility datasets to evaluate the viscoelastic properties of OA. This comprehensive molecular understanding of OA chemistry is essential for predicting their ability to undergo chemical reactions, partition between gas and particle phases, and impact atmospheric environment and related processes, such as radiative forcing of climate and cloud formation. This presentation will provide an overview of recent advancements in this field and outline future directions for continued research. 

Bio: Professor Alexander Laskin is a Professor in the Department of Chemistry with a courtesy appointment in the Department of Earth Atmospheric and Planetary Sciences at Purdue University in West Lafayette, Indiana. He received his M.Sc. in Mechanical Engineering from St. Petersburg Polytechnical Institute, Russia, and his Ph.D. in Physical Chemistry from The Hebrew University of Jerusalem, Israel. Dr. Laskin’s group advances aerosol and multiphase environmental chemistry with discoveries that reframe sources, composition, and climate/health impacts. 

He is actively involved in the scientific community, serving as a Co-editor of the Atmospheric Chemistry and Physics journal since 2013, and as a member of the Editorial Board for Aerosol Science and Technology and Scientific Reports. His honors include the NASA Honor Award (FIREX-AQ Group Achievement) in 2019 and being named a W.R. Willey Research Fellow of the Environmental Molecular Sciences Laboratory at PNNL in 2018.

Organic semiconductors (OSC) are of interest for a wide range of flexible optoelectronics applications, including transistors, solar cells, and sensors, to name a few. Despite their promise, the design and optimization of OSC pose significant challenges due to the complexity of the structures of the molecular building blocks, varied packing configurations of these building blocks in the solid state, which impacts the optical and electronic response, and sensitivity of the solid-state packing to material processing conditions. Accurately predicting the solid-state properties of OSC traditionally requires high-level quantum mechanical methods. These methods, however, can be computationally demanding, particularly for large molecules or when there is interest in extensive material screenings. Overcoming this computational bottleneck is essential to enabling the efficient design of OSC, which would reduce the experimental trial-and-error approach used in material discovery. Moreso, the holy grail of computational study is to be able to accurately and efficiently predict the molecular packing configurations and associated properties of OSC. This dissertation aims to address some of these challenges by developing computational approaches that leverage machine learning (ML) models to accelerate the study of OSC. ML promises to facilitate faster material screening and optimization by offering an alternative to direct quantum mechanical calculations. Specifically, this dissertation describes the development of ML models for intermolecular interactions, including noncovalent interactions (NCI) and electronic couplings (EC). Conventional quantum mechanical methods used to investigate OSC are introduced, and ML approaches are reviewed. The dissertation then discusses the generation of large, high-quality datasets for NCI from symmetry-adapted perturbation theory (SAPT), and the development of ML models to efficiently predict NCI. An active learning approach for the high-throughput derivation of optimal training sets for NCI predictions is then developed, and the training set is used to train new ML models. Finally, ML models to predict EC from three-dimensional (3D) molecular dimer geometries are implemented for the rapid, on-the-fly prediction of ECs across thermally sampled conformations obtained through molecular dynamics (MD) simulations to enable rapid materials characterization during simulation. Ultimately, this dissertation presents a framework that integrates ML with quantum mechanical insights, offering a scalable solution to accelerate OSC discovery and optimization.

KEYWORDS: Organic Semiconductors (OSC), Density Functional Theory (DFT), Symmetry-Adapted Perturbation Theory (SAPT), Noncovalent Interactions (NCI), Electronic Couplings (EC), Machine Learning (ML).

Organic semiconductors (OSC) are of interest for a wide range of flexible optoelectronics applications, including transistors, solar cells, and sensors, to name a few. Despite their promise, the design and optimization of OSC pose significant challenges due to the complexity of the structures of the molecular building blocks, varied packing configurations of these building blocks in the solid state, which impacts the optical and electronic response, and sensitivity of the solid-state packing to material processing conditions. Accurately predicting the solid-state properties of OSC traditionally requires high-level quantum mechanical methods. These methods, however, can be computationally demanding, particularly for large molecules or when there is interest in extensive material screenings. Overcoming this computational bottleneck is essential to enabling the efficient design of OSC, which would reduce the experimental trial-and-error approach used in material discovery. Moreso, the holy grail of computational study is to be able to accurately and efficiently predict the molecular packing configurations and associated properties of OSC. This dissertation aims to address some of these challenges by developing computational approaches that leverage machine learning (ML) models to accelerate the study of OSC. ML promises to facilitate faster material screening and optimization by offering an alternative to direct quantum mechanical calculations. Specifically, this dissertation describes the development of ML models for intermolecular interactions, including noncovalent interactions (NCI) and electronic couplings (EC). Conventional quantum mechanical methods used to investigate OSC are introduced, and ML approaches are reviewed. The dissertation then discusses the generation of large, high-quality datasets for NCI from symmetry-adapted perturbation theory (SAPT), and the development of ML models to efficiently predict NCI. An active learning approach for the high-throughput derivation of optimal training sets for NCI predictions is then developed, and the training set is used to train new ML models. Finally, ML models to predict EC from three-dimensional (3D) molecular dimer geometries are implemented for the rapid, on-the-fly prediction of ECs across thermally sampled conformations obtained through molecular dynamics (MD) simulations to enable rapid materials characterization during simulation. Ultimately, this dissertation presents a framework that integrates ML with quantum mechanical insights, offering a scalable solution to accelerate OSC discovery and optimization.

KEYWORDS: Organic Semiconductors (OSC), Density Functional Theory (DFT), Symmetry-Adapted Perturbation Theory (SAPT), Noncovalent Interactions (NCI), Electronic Couplings (EC), Machine Learning (ML).

Cerebrovasculature refers to the network of blood vessels in the brain, and its coupling with neurons plays a critical role in regulating ion exchange, molecule transport, nutrient and oxygen delivery, and waste removal in the brain. Abnormalities in cerebrovasculature and disruptions of the blood supply are associated with a variety of cerebrovascular and neurodegenerative disorders. Nanocarriers, a nano-sized drug delivery system synthesized from various materials, have been designed to encapsulate therapeutic agents and overcome delivery challenges in crossing the blood-brain barrier (BBB) to achieve targeted and enhanced therapy for these diseases. Unraveling the transport of drugs and nanocarriers in the cerebrovasculature is important for pharmacokinetic and hemodynamic studies but is challenging due to difficulties in detecting these particles within the circulatory system of a live animal. In this dissertation, we developed a technique to achieve real-time in vivo tracking of nanocarriers in the cerebrovasculature using fluorescence correlation spectroscopy (FCS), which has great potential for determining the pharmacokinetics of drugs and nanocarriers, as well as for studying disease-related connections between the cerebrovascular and neurodegenerative diseases.

We utilized novel fluorescent probes composed of DNA-stabilized silver nanocluster (DNA-Ag₁₆NC), that emit in the first near-infrared window (NIR-I) upon two-photon excitation in the second NIR window (NIR-II), encapsulated in liposomes, which were then used to measure cerebral blood flow rates in live mice with high spatiotemporal resolution by two-photon in vivo FCS. Liposome encapsulation concentrated and protected DNA-Ag₁₆NCs from in vivo degradation, enabling the quantification of cerebral blood flow velocity within individual capillaries of a living mouse. We also loaded another DNA-stabilized silver nanocluster (DNA640), which exhibited higher quantum yield and anti-Stokes fluorescence upon upconversion absorption, into cationic mesoporous silica nanoparticles (CMSNs) and successfully coated them with liposomes. The cerebrovasculature was chronically labeled using an adeno-associated viral (AAV) vector encoding Alb-mNG secretion into the bloodstream, combined with FCS under upconversion excitation, enabling real-time observation of the flow velocity and particle number of DNA640-CMSN-liposomes within the capillaries. We applied our proposed techniques to study the cerebrovascular structure and blood flow velocity in Alzheimer's disease mouse models and to explore the effects of disease-related conditions on vasoconstriction and vasodilation.

KEYWORDS: Cerebrovascular, nanocarrier, FCS, NIR fluorescence, DNA-AgNC, in vivo

Zoom link: https://uky.zoom.us/j/5984755867?omn=87194697892

Meeting ID: 598 475 5867.