Category: Notable Grants

A manufactured product is the end of a long chain of interwoven manufacturing steps that may span geography, industries, and manufacturing processes. Each step may be optimized, yet for a step there may be uncertainty about the larger context of its contribution that if known during production would allow for greater efficiencies, better quality, and improved productivity. If a global system analysis and optimization could, in addition, be conducted cooperatively with each step during production, the end product and overall production would greatly benefit. Advances in hybrid distributed control and optimization, in highly networked cyber-physical systems, and in artificial intelligence and machine learning have opened new opportunities in cyber-enabled manufacturing. This Future Manufacturing Research Grant (FMRG) CyberManufacturing project connects and coordinates the ensemble of various manufacturing processes, operating at different manufacturing stages under a cyber-coordinated close-knit system, defined by an analytical framework, known as STREAM, a multi-stage distributed future manufacturing system. This project provides a public online repository that hosts the STREAM data, models, simulators, controllers, analytics, and empirical studies, and that facilitates sharing research experiences about STREAM with the research and industry communities. The project creates new outreach and workforce development activities for K-12, undergraduate and graduate students, as well as working professionals in the field of manufacturing. These research results will be included in the university curriculum for advanced manufacturing, architecture design, machine learning, simulation, and system control and optimization. This project is an interdisciplinary research project with three interconnected research tasks: (1) STREAM architecture design and implementation. There is a novel bridging middleware architecture to enable seamless machine interoperability, and software- and hardware-based accelerators will be built to enable efficient communication and computing in cyber-manufacturing systems. (2) STREAM modeling and quality control. There is a novel multi-layer functional graphical model to address the high-dimensional functional dependencies over STREAM machines and a spatial-temporal iterative learning control method to achieve an accurate and efficient process quality control. (3) STREAM simulation and production control. To handle the multi-level dynamic process interactions in the system that collectively meet process quality, cost, and resource constraints, there are coordinated, high-fidelity multi-resolution simulators, assisting with the hybrid control of STREAM production. These research tasks are validated in an open-source additive manufacturing testbed for the manufacture of high energy/power density supercapacitors. The modeling and analysis methodologies form a rigorous basis for continuous improvement of quality, manufacturability, and productivity of future multi-stage and distributed manufacturing systems.

Funder: National Science Foundation 

Amount: $2,333,085 

PI: Hongyue Sun, Franklin College of Arts and Sciences, Department of Statistics 

Seasonal influenza viruses cause significant disease burden. While seasonal influenza vaccines are available, these are often poorly efficacious due to mismatch with circulating virus strains, particularly in the populations at greatest risk of complications from infection, including the elderly, infant, and immunocompromised. Influenza A viruses (IAV) also pose a pandemic risk for which seasonal influenza vaccines provide no cross protection. In 2018, the National Institute of Allergy and Infectious Diseases (NIAID) released a strategic plan for developing a universal influenza vaccine and subsequently released the FOA PA-18-859, “Advancing Research Needed to Develop a Universal Influenza Vaccine.” The long-term goal of this proposal is to develop a universal influenza vaccine. We hypothesize that a flu vaccine composed of broadly cross-reactive B-and T-epitopes covalently linked to an immune adjuvant will elicit potent immune responses and protect against diverse influenza A virus infections and associated disease. This expectation is supported by our prior studies which demonstrated a fully multi- component vaccine composed of tumor associated glycopeptide B- and CTL-epitope, a peptide CD4 T cell epitope and a TLR2 agonist (Pam3CysSK4) elicited robust immune responses and protected against a stringent tumor challenge in a murine cancer model. We will chemically synthesize multi-component vaccines that are composed of conserved peptide antigens derived from IAV and an adjuvant such as Pam3CysSK4 or monophosphoryl lipid A (Aim 1). In addition, we will employ an enzymatic glycan remodeling strategy to modify recombinant hemagglutinin (rHA), which is used as a licensed flu vaccine, with various TLR agonists and DC targeting moieties (Aim 2). It is expected that the self-adjuvanting rHA vaccines will enhance antigenicity of conserved but poorly immunogenic stalk domain thereby providing heterologous protection. We will also explore whether covalent attachment of immune-potentiators to recombinant neuramidase (rHA) can enhance its immunogenicity and provide broad protection (Aim 3). The

immunogenicity and efficacy of the vaccine candidates will be evaluated in murine and ferret vaccination and challenge models, using innovative approaches and antigen probes to assess polyfunctional T cell responses and geminal center (GC) B cell response. This research is significant as it directly addresses multiple NIAID priorities in their strategic plan for developing a universal influenza vaccine. The results of these studies could have a significant impact as the universal influenza vaccines developed should be suitable for advancement to pre-clinical studies. Moreover, the adjuvants and approaches developed in this proposal will be applicable to other vaccines and study of the host response to influenza infection, and will have broader impacts beyond universal influenza vaccine development.

Funder: National Institutes of Health 

Amount: $3,294,848 

PI: Geert-Jan Boons, Franklin College of Arts and Sciences Department of Chemistry 

With support from the Chemical Structure, Dynamics, and Mechanisms A (CSDM-A) program in the Division of Chemistry, Melanie Reber of the University of Georgia is developing methods capable of measuring transient changes in the absorption spectra of molecules in the gas phase. Gas phase measurements, specifically in a molecular beam, allow for detailed study of the role of vibrations in excited state processes with a direct comparison to theoretical predictions. Molecular beams provide a cold and controlled environment for generating and studying small molecules but require high detection sensitivity due to the low number densities. Reber and her students will use optical enhancement cavities to increase the detection sensitivity of ultrafast transient absorption spectroscopy. Their discoveries could lead to a more complete understanding of conical intersections in vibrational excited states of organic molecules and radicals. As part of the educational component, Dr. Reber will explore how the use of art and music in teaching science impacts student learning and retention of students from all backgrounds. The students involved in the project will gain highly technical training in lasers, optics, and electronics relevant to a range of high technology fields including quantum technologies. To broaden participation and awareness of the interdisciplinary fields of physical chemistry and quantum science, Reber will teach a class for incoming first-year undergraduate students to introduce them to the science, technology, and application of quantum science. The project will look at the molecular dynamics around conical intersections with both ultrafast time resolution and high spectral resolution for a detailed characterization of the dynamics. This includes the development of new instrumental techniques that study ultrafast dynamics of molecules in the gas phase with both ultrafast time resolution and high-resolution detection. The team uses ultrafast frequency comb fiber lasers in the visible and infrared spectral regions and couples them to external optical enhancement cavities to increase the signal. This enables study of dilute species in molecular beams with ultrafast transient absorption spectroscopy. Dual comb detection techniques will be developed to provide quantum-state resolution on the absorption spectra of the resultant species. The overarching objective is to study conical intersections in excited electronic states and conical intersections between vibrational states, such as Jahn-Teller interactions. This study aims to provide a detailed description of the dynamics in the gas phase for direct comparison with theory and a more complete picture of the quantum effects in the dynamics.

Funder: National Science Foundation

Amount: $675,000

PI: Melanie Reber, Franklin College of Arts and Sciences, Department of Chemistry

With the support of the Chemical Synthesis program in the Division of Chemistry, Christopher Newton of the University of Georgia is designing novel molecular “building blocks” that improve the reactivity and versatility of molecular addition reactions. These addition reactions enable the rapid construction of complex organic molecules through the joining of two simpler fragments and this research aims to address long-standing challenges in the field that have limited its applications. The targeted reactions are expected to lead to a diverse set of cyclic structures containing carbon, oxygen, and nitrogen atoms. Detailed studies of the mechanisms underpinning these transformations will also be undertaken, helping to facilitate future discoveries. The outcomes of this research stand to have broad scientific and societal impacts including in the pharmaceutical, material, and agrochemical industries. The funded research will also support the training of a diverse body of undergraduate and graduate students in state-of-the-art chemistry techniques, helping to strengthen the future STEM (science, technology, engineering and mathematics) workforce in the United States. In addition, Dr. Newton and his team will work to create and disseminate free, open-access chemistry educational tools to reduce barriers and broaden engagement in STEM. Finally, this award will support an outreach program, in collaboration with local high school teachers, to provide hands-on laboratory experience and career guidance to the greater Athens, GA community. The overarching goal of the research program under the guidance of Christopher Newton is to develop novel, pericyclic-based strategies for the convergent synthesis of high-value complex ring systems. This study aims to tailor the reactivity of cycloaddition reactions, including the venerable Diels-Alder reaction, through the use of atypical, high oxidation state building blocks. The joining of these novel fragments leads to products of increased complexity and functionality when compared to current state-of-the-art approaches. The research plan has three distinct objectives: (i) development of the first general family of cross-coupling active Diels-Alder dienes, (ii) a one-step Diels-Alder/ring expansion route to 7- and 8-membered hetero- and carbocyclic motifs, and (iii) development of a novel, highly reactive class of aza-dienophiles. Success in these endeavors is anticipated to provide efficient access to a plethora of highly functionalized, biologically active polycyclic molecules, while also furthering fundamental understanding of structure and reactivity in this important area of reaction modality.

Funder: National Science Foundation

Amount: $770,000

PI: Christopher Newton, Franklin College of Arts and Sciences, Department of Chemistry

Cilia are thread-like microtubule-based cell extensions which function in cell locomotion, fluid transport, and signaling. Many developmental disorders and diseases are caused by defects in ciliary function and assembly. To assemble cilia of a specific size and composition, cells have to transport hundreds of different proteins from the cell body into the organelle. Intraflagellar transport (IFT), a bidirectional motility of protein particles along ciliary microtubules, is assumed to be the major pathway for protein transport in cilia. IFT is required for ciliary assembly, maintenance, and signaling, however, it remains largely unknown which proteins are transported by IFT. It is also unclear where in the cilium cargoes are unloaded from IFT and whether the amount of protein transported by IFT is regulated. Because ciliary proteins are likely to be transported as single molecules or in small clusters, the analysis of their transport requires a highly sensitive imaging technique. Using Total Internal Reflection Fluorescence (TIRF) microscopy, we have established in vivo imaging of protein transport by IFT in cilia. We will analyze protein transport in cilia using the unicelluar model Chlamydomonas reinhardtii, which allows us to combine high resolution imaging in cilia with genetic manipulation and biochemical analysis of the organelle. We performed a comprehensive analysis of ciliary transport of the axonemal protein DRC4 and showed that DRC4-GFP depends on IFT for ciliary entry and distribution along the organelle. In Specific Aim 1, we will image distinct proteins selected from different ciliary compartments and substructures to determine how they interact with IFT to move into cilia. We will address the question of how IFT particles serve as carriers for many distinct proteins and how IFT transports proteins in the correct ratio into the organelle. We will test whether protein loading onto IFT particles depends on protein supply in the cell body and to which extent unloading of cargoes from IFT is spatially controlled. Our data show that the transport frequency of DRC4 is greatly increased when cilia grow, suggesting that the capacity of the IFT pathway can be modulated. The regulation of IFT is the focus of Specific Aim 2. We will analyze whether IFT particles isolated from growing and steady-state cilia are biochemically distinct and how cargo transport is affected in IFT mutants with small defects in the particle. The control of cargo influx is likely to be a prerequisite to establish a specific length of cilia, which is critical for its motile and signaling functions. We will analyze IFT and cargo transport in mutants with defects in ciliary length regulation such as long flagella 2 (lf2). LF2 encodes a widely conserved CDK-like kinase with an emerging role in disease. IFT is disturbed in lf2 cilia; we will test the hypothesis that LF2 kinase is a regulator of IFT, which when defective results in overloading of IFT particles. We noted that IFT proteins accumulate in mutants with structural defects in cilia, which might indicate a feedback mechanism on the IFT pathway which alerts the cell of incorrectly assembled cilia. We will test whether cells use the IFT pathway to monitor the correct size and structure of cilia.

Funder: National Institutes for Health

Amount: $2,522,709

PI: Karl Lechtreck, Franklin College of Arts and Sciences, Department of Cellular Biology

Following a stroke, hand dexterity does not recover fully for most patients, significantly reducing quality of life. Optimal and effective assessment and therapies for achieving hand dexterity are currently lacking due, in part, to limited scientific knowledge of human hand dexterity in health and disease. Hand dexterity hinges on multiple essential behavioral components embedded in a highly interactive neural circuit. How the behavioral components interact and how they are supported by descending neural pathways are still unclear. The long- term goal of this research is to build a predictive model and identify key behavioral and neural principles for designing targeted therapies to facilitate the reacquisition of hand dexterity to improve quality of life. The current objective of this project is to investigate behavioral and neural mechanisms of hand dexterity and its impairment and recovery after stroke. The central hypothesis is that three essential components of hand function, finger individuation, precision grip, and power grip, largely rely on three distinct control variables, flexibility, coordination, and strength, and separable descending pathways: direct- and indirect-corticospinal tract (CST), and reticulospinal tract (RST). The rationale for this project is that directly comparing different components of dexterity using kinematics/kinetics at the same levels of granularity, combined with the most advanced measures of descending neural pathway structure and function holds promise in a new model of hand dexterity. Two specific aims are proposed to test the central hypothesis: 1) characterize effect of stroke on individuation, precision grip, and power grip; and 2) determine if stroke-related disruption in the structure and function of three descending neural pathways are associated with three behavioral components. Under Aim 1, chronic stroke patients and healthy controls’ Individuation and Precision Grip will be directly compared using isometric forces recorded in high resolution at all ten fingertips in 3D, and their interaction with Power Grip will be examined. Under Aim 2, high-resolution tractography using diffusion-weighted MRI will be obtained to assess structural integrity of the three descending pathways. Transcranial magnetic stimulation (TMS) paired with peripheral nerve stimulation will be used to assess functional involvement of the three pathways using short-, long-, and extra-long interval modulation of Hoffmann-reflex. Under Aim3, a model will be built to map severity of impairment in behavioral measures to neurophysiological markers derived from Aim 1&2 to test the hypothesis that stroke survivors’ direct-, indirect-CST and RST measures will be predictive of individuation, precision grip, and power grip behaviors, respectively. The proposal is innovative because it reconceptualizes dexterity by, for the first time, directly assessing essential components of dexterity behaviors and descending pathways with cutting-edge techniques and builds a neural model from these findings. It is significant because findings from this project will guide the creation of sensitive clinical assessments and redefine therapeutic interventions for optimal hand rehabilitation after stroke to enhance patients’ quality of life.

Funder: National Institutes for Health

Amount: $2,736,478

PI: Jing Xu, Mary Frances Early College of Education

This project aims to optimize circularity, from the city up, transforming the linear consumption model of raw material extraction, production, use, and disposal that dominates the global economy. This linear model has led to serious unintended worldwide issues, from pollution to resource depletion. This project will reimagine how we design, from molecules and materials to buildings and communities. The newly updated and expanded Circularity Assessment Protocol (CAP) framework will be co-implemented with 11 cities. CAP integrates the open data tool Debris Tracker with data freely available, joining data from nearly 100 countries around the world. The new portal for this project will house the data from Phase I and Phase II communities aiming to foster global dialogue about community circularity and creating meaningful change. To increase circularity, the researchers will help communities address systemic and intersectional issues, including pollution burdens, lack of infrastructure, and lack of access to services. The project will further develop a platform for underrepresented voices through an existing podcast called Aquathread, produced and recorded at WUGA, the University of Georgia’s NPR affiliate. This research will continue to increase public scientific literacy and engagement with science and technology through the use of open data and free mobile citizen science apps; improve the well-being of individuals in society by reducing waste and improving the built environment; and develop a diverse, globally competitive workforce. All communities, partners, and the public will have access to project data, facilitating the use of science and technology to inform public policy and support decision-making. In contrast to the linear economy of “take, make, waste,” circular economy (CE) decouples economic growth from resource consumption. CE principles are based on the efficient use of resources and eliminating waste from product life cycles. This project will tackle the complex challenges that currently inhibit the circular economy’s growth by deeply integrating diverse disciplines through the researchers’ proven holistic systems framework. In Phase II, the newly updated and expanded Circularity Assessment Protocol (CAP) framework will be used to converge circularity across plastics (exploring polyfluoroalkyl substance-free alternatives), organic materials, and the built environment in 11 cities. In Phase I of this project, a circularity path was connected and converged across multiple materials and scales in two large metropolitan areas. Phase II will expand this work by training local implementation partners, and further developing a novel dynamic data and education portal. This portal will include city and metadata dashboards to facilitate inter- and intra-community dialogue to create systems change. Project partners include the Resilient Cities Network, a city-led network that brings together over 200 Chief Resilience Officers, practitioners, and researchers; the 2030 Districts Network of cities working to catalyze transformation in the built environment to mitigate the effects of climate change; Mississippi River Cities and Towns Initiative Mayors; and the Upper Midwest Association for Campus Sustainability (UMACS). This network of networks is the next step in expanding this project into a sustainable future as a continued resource and platform for sharing amongst cities around the world catalyzing change.

Funder: National Science Foundation

Amount: $5,000,000

PI: Jenna Jambeck, Institute for Resilient Infrastructure Systems

This project is centered around the creation and validation of an innovative digital framework to foster an ethical manufacturing ecosystem where machine ethics, including legality, integrity, and accountability, is mandated throughout the product design-fabrication-service life cycle. In the era of Industry 4.0, manufacturing systems are enhanced with advanced technologies and interconnectivity. While this evolution significantly expands the functionalities and accessibility of manufacturing machinery, it also introduces unprecedented ethical challenges in manufacturing regulation, such as malicious use of customizable fabrication (e.g., counterfeit goods and 3D printed weapons). This project pioneers the exploration of ethical Industry 4.0 and anchors principles of legality, integrity, and accountability as fundamental components in the digital manufacturing ecosystem. Specifically, the team designs and implements a set of computational methods and digital tools to provide ethical assurances spanning each stage of the design-fabrication-service life cycle from design, to fabrication, to service. By leveraging existing research platforms and local manufacturing partners, the ethical framework can be integrated and validated within real-world manufacturing testbeds. This project has multi-dimensional educational and societal impacts. The project can necessitate the inclusion of ethics and regulation compliance promotion within Industry 4.0. Moreover, the project also contributes significantly to the education of the future manufacturing workforce, promotes public awareness of manufacturing ethics, and brings benefits to the US manufacturing sector and general society. This research project explores principles of ethics as new functional components and constructs a digital framework that tackles technical obstacles in ethical Industry 4.0, including intellectual property (IP) protection, data security and privacy, regulation, and compliance. The team investigates and develops an ethical cyber layer, incorporating a set of computational algorithms, architecture, and software, to enhance the legality, integrity, and accountability of the digital manufacturing system. The technical thrusts in this project are threefold: (1) an efficient and robust ethical design checking mechanism using nonlinear matching algorithms for complex 3D digital models imported to manufacturing machines to avoid IP theft and malicious design; (2) ethical fabrication monitoring tools for manufacturing machines via secure computation with high privacy needs, limited annotated samples, and diverse operation conditions; and (3) ethical product tracking to analyze product texture fingerprint and assist the forensics of source machine identification with illegal and non-integrity usage. The validated resources and tools, including advanced models, algorithms, software and test benches, and educational materials, will be publicly available.

Funder: National Science Foundation

Amount: $565,778

PI: Hongyue Sun, Franklin College of Arts and Sciences, Department of Statistics

Dynamic binary translation (DBT), used to translate executable code from one instruction set architecture to another, supports a range of essential applications, including architectural simulators, hardware emulators, runtime optimizers, program analysis tools, software testing platforms, and more. However, existing DBT systems have not kept up with the rapid evolution of computer software and hardware. For instance, existing DBT systems suffer from significant execution inefficiencies due to the poor quality of the translated binary code. As a consequence, it becomes increasingly challenging to adopt DBT for many important applications, especially those in emerging domains, e.g., machine learning and graph processing. The goal of this project is to modernize DBT systems through a series of novel innovations. A key insight is that the translation between different computer instruction sets –usually represented in assembly language– is similar to the translation between different natural languages. Inspired by this insight, this project will invent novel translation approaches to produce high-quality binary code. The innovations developed by this project will improve the performance efficiency of DBT systems when running binary code. Moreover, they will enhance the capability of DBT systems to support important applications. More efficient, more capable, and more powerful DBT systems, as modernized by this project, will not only benefit current DBT applications, but also enable DBT applications in new frontiers, producing long-lasting impacts. The innovative technologies developed in this project will provide insights for the research community to push forward the DBT field. Additionally, this project will assemble a set of well-organized teaching and mentoring activities to promote research experiences for undergraduates and create a more diverse and inclusive educational environment.

Funder: National Science Foundation

Amount: $599,977

PI: Wenwen Wang, School of Computing

This project seeks to understand how plants control the synthesis of cellulose, a critically important polysaccharide that governs plant growth and development. Cellulose is an important component of food, fiber, textiles, and fuel for human and forage animals. While many of the enzymes that participate in cellulose synthesis in land plants have been identified, it is still unclear how plants make the decision to produce more or less cellulose. The Wallace lab will use advanced genetic, biochemical, and cell biological techniques to elucidate how cellulose biosynthesis is controlled during normal plant development and in response to changing environmental conditions, such as heat, drought, salt stress, and limiting nutrients. This information will be utilized to engineer plants with increased cellulose contents that could be used as biomass feedstocks for the synthesis of sustainable value-added products or as more efficient feedstocks for forage animals. By understanding how cellulose biosynthesis is controlled, the investigator also expects to provide a foundation for understanding how this fundamental feature of plant cell biology is linked to plant growth and development. Additionally, this project will support the research training of graduate, undergraduate, and high school students from diverse and under-represented backgrounds. This project will also support the course development of a quantitative mass spectrometry module for undergraduate students as well as public outreach through local agricultural events and web-based videos. The long-term goal is to understand how plant cellulose biosynthesis is controlled by post-translational phosphorylation, and to utilize this knowledge to increase cellulose output under changing environmental conditions. The central hypothesis guiding this research effort is that CESA (Cellulose synthase A) subunits and other CSC (Cellulose Synthase Complex) components are phosphorylated by protein kinases involved in the brassinosteroid signaling cascade, and these phosphorylation events regulate CSC velocity or subcellular localization. Specific Aim 1 employs biochemical and genetic methods to identify brassinosteroid-regulated protein kinases that phosphorylate and regulate components of the CSC and to understand how these regulatory events control plant growth and development. Specific Aim 2 utilizes advanced quantitative proteomic methods to investigate how changing environmental conditions lead to alterations in CSC phosphorylation. Specific Aim 3 focuses on determining how phosphorylation of CESA subunits influences the in vitro enzymatic activity of cellulose biosynthesis. The unifying goal of this work is to develop a holistic understanding of how post-translational phosphorylation regulates that activity of the CSC both in vitro and in vivo.

Funder: National Science Foundation

Amount: $915,280

PI: Ian Wallace, Franklin College of Arts and Sciences, Department of Biochemistry and Molecular Biology