Grants

DEPT OF DEFENSE.DEFENSE LOGISTICS AGENCY.DLA ENERGY.DLA ENERGY

Department of War Nationwide Coal-based Power Purchase Agreement (PPA)

NSF

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI) Program, this Departmental/Division Transformation Track project at the University of California Merced aims to: 1) understand how challenges to engaging in field research may harm the success of undergraduates in the Department of Life and Environmental Sciences (LES) and 2) devise sustainable solutions to remove barriers and promote success for all students in the department. Many scientific disciplines rely heavily on field work, including ecology, biology, and the earth, atmospheric, and ocean sciences, yet broadly engaging students in field-based STEM fields remains a challenge. This project will develop high-impact research experiences for students that capture the breadth of LES disciplines, as part of a sustainable, student-centered plan to develop workforce skills and growth. These activities will improve student experiences and training and accelerate their trajectory towards environmental careers. This project aims to attract and retain more students in LES majors; complete a departmental self-assessment to strengthen curricula; highlight the impact of LES careers throughout the curriculum; and support high-impact research experiences for students. These aims will ensure that department practices designed to benefit all students will remain sustainable as LES continues to grow and transform. The project will use qualitative and quantitative data to assess the outcomes of different interventions to ensure success. Two key aspects of the department transformation efforts will be examined: 1) how the department transformation plan serves and engages students and are sustainable as the department grows and 2) the impact of the project activities on student persistence and scientific identity, particularly in the field sciences. This project will lead to higher student participation in research, so that students are better prepared for and more likely to seek out life and environmental science careers. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and increase capacity to implement innovations that improve STEM teaching and learning at HSIs. 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.

NIGMS - National Institute of General Medical Sciences

Project Summary Over two thirds of Americans take prescription medications, but manufacturing bottlenecks contribute to rising drug shortages, which restrict patient’s access to life-saving medications. Engineered enzymes can increase the resilience of pharmaceutical manufacturing, but the engineering process is bottlenecked by slow traditional methods for evaluating enzyme performance. This proposal focuses on the systematic development of chemical biosensors that accelerate the engineering of enzymes for robust pharmaceutical manufacturing. Specifically, we will use bacterial transcription factors (TF) as biosensors for chemical measurement, which can transduce enzyme-catalyzed product molecules into programmable gene expression outputs that enables enzyme screening >10,000-fold faster than traditional methods. Although identifying TFs with the specificity needed for enzyme screening is currently a slow ad hoc process, a parallel assay recently implemented at the National Institute of Standards and Technology (NIST) using automation equipment enables the simultaneous measurement of >50,000 TF biosensors that can power a data-driven methodology. This research effort focuses on developing bench-scale parallel reporter assays to facilitate the deployment of TFs for drug manufacturing innovation via three key activities: TF discovery, TF engineering, and TF application. These three pillars directly address two core issues limiting the utility of TFs for drug manufacturing. First, the time needed to develop a TF deployable for enzyme engineering is slow (addressed in Aims 1 & 2). Second, TFs have only been used in qualitative screens for enzyme activity (addressed in Aim 3). Aim 1 focuses on discovering drug-responsive TF scaffolds by developing parallel assays to measure native interactions between poly-specific multidrug regulators and pharmaceuticals. Aim 2 will focus on engineering highly specific TF biosensors by collectively assessing the ability of library design methods, computational methods (in collaboration with Dr. Debora Marks), and TF evolvability to yield highly specific TFs. Aim 3 focuses on developing an assay termed “deep enantioselectivity scanning”, which uses a TF-enabled parallel assay to simultaneously quantify the enantioselectivity of >10,000 enzyme variants. Results from this high-throughput assay will be cross-validated with liquid chromatography. All parallel assays will be developed at Harvard in collaboration with NIST, and under the mentorship of Drs. Pamela Silver and Michael Springer. This work aims to bolster pharmaceutical manufacturing innovation by establishing bench-scale parallel assays to rapidly deploy TF-based biosensors for accelerated enzyme engineering. Beyond supporting NIGMS’s mission to generate novel research tools that benefit public health, completing this research alongside my training plans in writing and communication will greatly support my long-term career goal of leading a research group that leverages quantitative and evolutionary biology to engineer sustainable biotechnologies.

New NY Broadband 15-16 Capital

Deposit Tel NY BB Phase II Capital

New NY Broadband 15-16 Capital

Deposit Telephone Underserved Broadband Capital

New NY Broadband 15-16 Capital

Deposit Telephone Unserved Broadband Capital

Office of Public Safety Administration

NEW HEADER

NIGMS - National Institute of General Medical Sciences

PROJECT SUMMARY/ABSTRACT The pharmaceutical and agrochemical industries rely heavily on the stereoselective preparation of chiral molecules because opposite enantiomers often demonstrate disparate activities. Though numerous approaches exist to obtain enantiomerically enriched material, these methods typically require the synthesis of specialized starting materials/reagents. The catalytic deracemization of racemic material is an attractive alternative, as racemic synthesis is often straightforward and enantioinduction can be achieved by a catalytic rather than stoichiometric process. In recent years, photocatalysis has emerged as a strategy for driving systems out of equilibrium and accomplishing deracemization reactions. However, despite the prevalence of the α-carbonyl stereocenter in peptidomimetics, natural products, and pharmaceuticals, the catalytic deracemization of this scaffold has not been achieved in a general sense; this may be in part due to the challenges associated with generating a reactive intermediate at the acidic α-position under mild conditions, coupled with the lack of nucleophilic HAA reagents. This proposal seeks to unlock a new reactivity platform within the field of stereochemical editing and utilize it to enable deracemization of α-carbonyl stereocenters. Leveraging the Wendlandt group’s expertise in asymmetric catalysis, we will investigate stereoselective hydrogen atom abstraction (HAA) using chiral amine-borane catalysts and develop a deracemization protocol for the conversion of racemic starting materials into high-value enantioenriched products. Prior literature has established proof of concept for kinetic resolution of α-carbonyl stereocenters with these reagents, albeit with modest selectivity outcomes; however, their extension to deracemization has not yet been investigated or accomplished. We seek to leverage these chiral amine-boryl radicals and photoredox catalysis for the development of a novel method for the deracemization of α-carbonyl stereocenters, with a particular focus on biologically active motifs such as β2- and γ2- amino acids. Ultimately, we seek to establish amine-boranes as a modern reagent class for selective HAA of acidic C–H bonds and gain a deeper understanding of the factors affecting enantioselectivity of HAA with amine-boryl radical species. We will accomplish these goals through synthesis of novel catalysts and evaluation of their reactivity via spectroscopic studies. Research will be carried out at MIT, an institution that excels in synthetic chemistry. I will receive training in asymmetric catalysis from Prof. Alison Wendlandt, a trailblazer in the stereochemical editing field, training in photophysics from Prof. Schlau-Cohen, an expert in ultrafast spectroscopy, as well as training in organoboron chemistry through informal interactions with Prof. Robert Gilliard and his research group at MIT. The proposed research is highly complementary to my doctoral training in the data science-driven study of pharmaceutically relevant reactions, enabling me to expand my skillset to include asymmetric catalysis, photophysics, and main group catalysis.

Tolland

Derainage Construction & Design #2152

NIAMS - National Institute of Arthritis and Musculoskeletal and Skin Diseases

Fibromyalgia (FM) is a chronic debilitating painful condition, affects millions of people in the U.S. alone, and is often refractory to the current treatment. The etiology of FM is multifactorial in which deranged gut homeostasis has been strongly implicated. Up to 70% of FM patients exhibit signs of deranged gut homeostasis, highlighting a key gastrointestinal component in the pathogenesis of FM. To date, the molecular link between deranged gut homeostasis and FM is poorly understood. The gut brush border enzyme intestinal alkaline phosphatase (IAP), encoded by Akp3 gene in mice and Alpi gene in humans, is a critical regulator of gut homeostasis. We and others have reported that knockout of Akp3 (Akp3-/-, IAP deficiency) in mice disrupts gut homeostasis with increased gut and systemic inflammation markers. Our preliminary data demonstrate that a) Akp3-/- mice recapitulated FM- like phenotypes including i) hypersensitivity to mechanical and thermal stimulation, ii) spontaneous pain behavior, and iii) FM-related comorbid behaviors including depression and anxiety; b) administration of exogenous recombinant IAP reversed IAP deficiency and improved FM-like phenotypes in Akp3-/- mice; c) macrophages and transient receptor potential vanilloid 1 (TrpV1) expression were increased in the dorsal root ganglion (DRG) of Akp3-/- mice; and d) IAP levels were reduced in stool samples of FM patients as compared to healthy subjects. These findings suggest that IAP could be a key molecule link between deranged gut homeostasis and the pathogenesis of FM. We propose that deficiency of Akp3-encoded IAP would lead to FM-like phenotypes through macrophage-mediated sensitization of TrpV1 positive (TrpV1+) nociceptors in the DRG. In Aim 1, we will test the hypothesis that IAP deficiency induces macrophage infiltration into the DRG and FM-like phenotypes. We will examine i) macrophage infiltration into the DRG using flow cytometry, immunostaining, and two-photon imaging with an innovative in vivo DRG window technique to correlate with FM-like phenotypes; ii) the effect of reversing IAP deficiency with exogenous recombinant IAP on macrophage infiltration into the DRG and FM-like phenotypes; and iii) the relationship between IAP deficiency-induced deranged gut homeostasis and DRG macrophage infiltration. In Aim 2, we will test the hypothesis that macrophage infiltration into the DRG plays a critical role in FM-like phenotypes. Genetic and pharmacological approaches will be used to i) deplete systemic vs. DRG macrophages; ii) inhibit monocyte/macrophage trafficking; and iii) suppress inflammatory macrophages. In Aim 3, we will test the hypothesis that TrpV1+ nociceptors in the DRG are sensitized via macrophage- nociceptor interactions in mice with FM-like phenotypes. We will i) inhibit TrpV1 genetically (TrpV1DTR) or pharmacologically and ii) examine a macrophage-mediated signaling in sensitization of TrpV1+ nociceptors using an innovative DRG calcium imaging platform, TrpV1::ChR2 mice, and patch clamp recording. This project will provide insights into a novel molecular mechanism of FM pathogenesis and help transform the current treatment limited to managing FM symptoms to mechanism-based therapy for FM patients with deranged gut homeostasis.

Transportation Agency

DERBY CHRYSLER, DODGE, JEEP,INC.

Dermatology Education Foundation

Dermatology Education Foundation is an active grantmaking foundation based in San Jose, CA. Focus: health. Contact the foundation directly for current funding opportunities.

City of Richmond

Pop Ups Unlimited

NSF

The computing ecosystem continues to grow at a breakneck pace and consumes a substantial portion of the world’s electricity. Artificial Intelligence's (AI) recent successes have further exacerbated this computing-driven surge in energy demand. As a result, there is a growing need to integrate various energy sources in the energy grid. However, volatility of some energy sources creates new challenges for the power grid operators, who must continuously balance electricity supply and demand. Achieving the energy efficient data centers would not only help stabilize the power grid but also ensure that AI’s rapid growth remains supported. This project aims to realize that vision by integrating AI data centers into emerging smart grid programs. To this end, the project will develop a data center control framework to regulate data center power consumption with power grid and carbon constraints, all while providing necessary performance guarantees to data center users. By doing so, the project will help stabilize the grid and provide electricity cost incentives for data centers. This project aims to improve fundamental knowledge in AI data center management and optimization. While there is a rich body of research in large-scale computing system management and recent advancements in computing demand response, the state-of-the-practice is substantially lagging due to science and engineering challenges. To enable AI data centers to perform “flexible computing", this project will innovate in the following three directions: (1) designing AI data center planning and runtime optimization policies that provide performance or quality-of-service guarantees to user jobs while following dynamic power signals, (2) building an optimization framework where multiple data centers interact with grid operators and with each other so as to improve a global social cost metric, and (3) addressing key challenges in cyber-infrastructure implementation so that the designed server and data-center level policies are impactful in real-world scenarios. The project will provide validation of ideas through experiments on servers and simulations, and via deployment of prototype implementations on real-world clusters. 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.

NSF

This project aims to repurpose old smartphones as sustainable, battery-free alternatives to conventional Internet of Things (IoT) sensors, creating a long-lived platform for environmental monitoring. With most smartphones replaced every 2–3 years and billions of IoT devices in use globally, the environmental and economic costs of short device lifespans are substantial. This project addresses these concerns by integrating repurposed smartphones into real-world monitoring networks for tree phenotyping and river dynamics. Equipped with biocompatible, energy-harvesting phone cases, these smartphones operate without batteries or manual maintenance. This work promotes the progress of science by extending the utility of existing devices, reducing infrastructure costs, and supporting environmental science through scalable, real-time data collection. The project also supports graduate and undergraduate research and encourages the reuse of computing resources in sustainable applications. The project develops models, algorithms, hardware platforms, and foundational methods for creating an ultra-long-lived, maintenance-free remote sensing platform for environmental applications. It focuses on transforming old smartphones into reusable, battery-free sensors equipped with custom-designed, energy-harvesting phone cases. These systems operate reliably under intermittent power conditions using capacitor-based energy storage rather than conventional batteries. The research includes the development of battery-free computing techniques, energy-aware scheduling strategies, and domain adaptation algorithms to ensure robust performance across a wide range of smartphone models and environmental conditions. The system supports continuous monitoring of tree canopies and river systems, with sensing tasks such as image capture and data logging. Evaluation is conducted through iterative hardware-software co-design and extensive field testing in diverse geographic regions. The resulting platform contributes to ecological monitoring, embedded computing, and the broader understanding of sustainable sensing in resource-constrained environments. 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.

NSF

As artificial intelligence (AI) applications become increasingly central to our daily lives, the datacenters that serve these applications are growing rapidly. However, this growth comes with a significant environmental cost. These datacenters rely on computer chips whose design, manufacturing, and operation consume substantial amounts of energy, water, and resources, posing challenges to environmental sustainability. This project addresses this critical challenge by rethinking how we design computer chips that power AI in today’s datacenters. Current chip design methodologies often overlook their full environmental footprint, particularly the water and energy impacts across the chip lifecycle. As AI workloads expand, these factors, especially in chip manufacturing and datacenter cooling, are becoming increasingly important to sustainable computing. This project directly addresses these challenges by introducing three key strategies for a sustainability-aware approach to chip design. First, this project develops new models, tools, and metrics to quantify the environmental footprint of chips throughout their lifecycle - from design and manufacturing to deployment and eventual end-of-life. It includes detailed modeling of water and energy consumption, particularly for chip fabrication and chip cooling. Second, the project introduces a framework for splitting large complex chips into small modular chiplets, and replacing them with reconfigurable chiplets allowing their reuse across multiple different AI applications. This increases their operation lifetime in datacenters reducing wastage and cost. Third, the project builds software to optimize chip floor planning and interconnect design to minimize cooling requirements, fabrication energy and environmental costs. This project supports NSF’s mission to advance American innovation, economic prosperity, and global leadership in emerging technologies. It strengthens U.S. leadership in AI and datacenter infrastructure by developing advanced tools to design more efficient, cost-effective computer chips that power these systems. By reducing unnecessary energy and water use, the project improves operational efficiency and lowers costs which are key priorities for sustainable growth and resilient infrastructure. Additionally, it supports workforce development by engaging K–12 and community college students in applied learning experiences that prepare them for high-demand jobs in AI, semiconductors, and advanced manufacturing. This project aims to develop a framework for designing computing chips for AI datacenters. The overarching goal is to minimize the environmental footprint (EFP), including both carbon footprint (CFP) and water footprint (WFP), across the lifecycle of computing - from design to manufacturing to use. The project is structured around three thrusts: (1) Developing models and metrics for evaluating EFP with a special emphasis of WFP, (2) Disaggregating Systems-on-Chip (SoCs) into chiplet-based SiPs with a focus on integrating Field Programmable Gate Array (FPGA) chiplets, and (3) Physical design of chiplet-based Systems-in-Package (SiPs) considering EFP as a metric of optimization. To support EFP-aware chip design, the project introduces new metrics, such as Performance-per-Unit-EFP, to guide architectural and physical optimizations. The modeling framework will extend beyond traditional CFP-based models by incorporating water usage in both semiconductor fabrication and datacenter cooling. A design-space exploration (DSE) framework will be developed using graph-based partitioning methods to decompose SoCs into SiPs. This DSE process will optimize across multiple objectives, including bandwidth, latency, and power, while minimizing overall EFP. Furthermore, the project will model the EFP impact of physical implementation choices, including placement, routing, and 3D stacking, and integrate these models into traditional place-and-route algorithms to enable EFP-aware physical design. This project pioneers the integration of EFP with tools and methodologies used for the architecture and design of future chips. By incorporating WFP, it expands the scope of current sustainable computing research. The open-source software for SoC disaggregation and EFP-aware physical design will help accelerate the adoption of sustainable design practices in the chip design industry. 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.

NSF

Data centers play a vital role in modern computing, supporting everything from personal internet use to a wide range of industries. As demand for computing power grows, next-generation data centers must be designed with smarter, more precise integration of technologies to improve processing speed, data handling, and power management. At the same time, data centers are becoming increasingly costly to operate, due to high energy consumption and the use of rare materials—both of which present global sustainability challenges. Emerging technologies, such as chiplets and 2.5D integration, offer new possibilities by closely combining memory, specialized accelerators, and general-purpose processors to achieve significantly higher performance. However, achieving energy-efficient and resource-conscious computing with these new technologies remains a complex challenge. It requires innovative approaches to integrating power delivery and signal integrity alongside computing functions, and combining different materials — such as traditional silicon with advanced components like gallium nitride power electronics and cutting-edge memory technologies. The ECOCHIPLETS project will revolutionize the design of next-generation data centers through novel chiplet and 2.5D integration practices. The project will apply economic concepts such as depreciation to cost and lifetime concerns of systems. This promotes approaches that advance capabilities in newly deployed compute servers. These servers will leverage novel chiplet-based design from the ground up to provide new higher performance and energy efficiency approaches along with often ignored concerns such as thermal, power delivery, and signal integrity, critical for system longevity developed through this project. These results will lead to advances in heterogeneous systems ideal for agile virtual hardware design and heterogeneous integration allowing for collecting data center resources to build virtual or disaggregated resources allowing compute software to match workloads seamlessly to various technologies and heterogeneous chiplets in the same package. This project takes a full stack approach by modeling costs and integrating critical components previously ignored in design and simulation tools, such as power electronics and asynchronous circuits. The result is hardware agility and efficiency with adaptability to new compute algorithms while simultaneously promoting long equipment lifetimes and reducing costs. 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.

Deschutes County

Community Renewable Energy Project

Oregon Department of Energy

Community Energy Resilience Project

Oregon Department of Energy

Community Energy Resilience Project

NSF

Groups are a mathematical formalization of the notion of symmetry, which can also be used to model a wide variety of other phenomena, including the passage of time and the homogeneity of space. The ubiquity of this concept is central to its connection with dynamics, the study of systems that evolve in time and space. These processes can be either deterministic, as in the movement of planets, or stochastic, as in the throwing of dice. The main purpose of this proposal is to study the interplay between dynamics and groups (group actions and dynamics) using the methods of logic, with a particular emphasis on the tools of descriptive set theory. Descriptive set theory precisely studies how complicated it is to define certain subsets, equivalences, and related objects. In particular, it can show whether certain simple classifications of objects exist or are impossible. The principal investigator will focus on understanding the complexity of random walks and their Poisson Boundaries, the possible symmetries and joinings of dynamical systems, and the theory of Borel equivalence relations. Poisson Boundaries capture the notion of asymptotic indistinguishability for random walks. They also classify the space of an important set of functions on groups (the bounded harmonic functions). When the boundary is trivial, this implies that in the long term all random walks look similar. One goal of this project is to make progress in understanding when this triviality occurs. Joinings represent a broad notion of symmetry, more general than morphisms or factor maps, that topological dynamical systems can have. Understanding the joinings of a topological dynamical system to itself provides a rich perspective on the various symmetries that the system can possess. Borel equivalence relations are a formal way to precisely describe whether classification problems are easy or difficult. This project aims to further impact their study, as well as to initiate the exploration of linear algebraic analogues of Borel equivalence relations. Graduate students will be involved in this project. 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.

Deseret Arts Foundation

Deseret Arts Foundation is an active grantmaking foundation based in N Salt Lake, UT. Focus: arts. Contact the foundation directly for current funding opportunities.

Desert Cancer Foundation

Desert Cancer Foundation is an active grantmaking foundation based in Palm Desert, CA. Focus: health. Contact the foundation directly for current funding opportunities.

Desert Community Foundation

Desert Community Foundation is an active grantmaking foundation based in Palm Desert, CA. Focus: philanthropy. Contact the foundation directly for current funding opportunities.