California Institute Of Technology

NSF Awards · FY 2025 · 2025-10

New technologies are needed for the U.S. to maintain leadership in the development and manufacture of next generation computer chips. A critical step in the manufacture of computer chips is the deposition of electronic materials, layer by layer, onto a surface, in precise patterns to create a circuit. A particularly precise method is called atomic layer processing, which can deposit a single layer of atoms onto a surface (atomic layer deposition), or remove a single layer of atoms from a surface (atomic layer etching). However, these processes require very high temperatures and do not work for all electronic materials. A bold new idea is to use electrons to enable the deposition or etching processes to work at lower temperatures. In the research funded by this award, atomic layer processing systems will be equipped with special emitters that direct an electron beam to the surface and drive reactions that would not otherwise be possible. Special instruments designed to work inside the atomic layer processing equipment will measure the progress of the reactions in real time, providing fundamental information that can be used to control and improve the process. Once this concept has been demonstrated, the project seeks to make superconducting thin films that can be used as “qubit” chips in quantum computers. The project will also pioneer new ways to train students in use of clean room technology that is central to the semiconductor industry. The training modules will use augmented reality / virtual reality tools to make this training available to students who do not have access to clean room facilities. Atomic layer processing (ALP) is based on self-limiting chemical reactions of gases, plasmas, or molecular precursors at a surface, enabling deposition and etching with monolayer control. This project will advance fundamental understanding of electron-enhanced ALP (EE-ALP), where electrons are used to drive electron-stimulated reactions that would otherwise not occur in the given conditions. Although electron-stimulated chemistry has been studied in other contexts, the chemical mechanisms occurring in the unique self-limiting surface reactions of EE-ALP remain largely unexplored. A key component of our technical approach will be the first use of mid-infrared frequency combs to track the dynamics of interacting chemical species in ALP in real time, allowing a quantitative description of the chemical kinetics to be revealed. The fundamental understanding created by this project will open new process windows and new chemistries for deposition and etching of thin films with atomic precision, which is key to enabling future technologies such as quantum computers. The knowledge will also impact adjacent fields involving molecule-substrate interactions such as heterogeneous catalysis. Anticipated Transformative Impact:Superconducting thin films for quantum computer chips. 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.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract Whereas the piperidine motif is ubiquitous in pharmaceuticals, higher-order N-heterocycles such as quinolizidines and indolizidines are more challenging to prepare. This can limit their incorporation into drug development, despite their prevalence in important biologically active natural products. Dearomatization reactions offer a unique entry into these natural products, rapidly building complexity from accessible aromatic starting materials. Pairing this powerful strategy with stereodefined cyclization cascade reactions enables an orchestrated assembly of the oxidized fused ring structures present in many alkaloid targets. This proposal describes the development of an enantioselective dearomative cyclization to synthesize quinolizidines in one step from pyridine, grounded in the hypothesis that palladium can be used to kinetically trap a reversibly forming acyl chloride to synthesize enantioenriched quinolizidines through a dynamic kinetic resolution. To accelerate the development of this strategy, modern data science techniques will be applied to high-throughput datasets, enabling rapid traversal of the multidimensional and potentially complex optimization landscape. These studies are expected to provide a workflow for the future development of reaction cascades through machine learning, enabling practitioners to develop kinetically complex reaction landscapes that might otherwise seem intractable but provide opportunities to dramatically build molecular and synthetic complexity. This approach will be showcased in an asymmetric synthesis of lycopodine and lycoposerramine H, natural product inhibitors of acetylcholinesterase—a property that is therapeutically relevant for the treatment of neurodegenerative disorders. We expect that the flexible synthetic approach proposed could apply to future diversity-oriented synthesis campaigns around this natural product family towards the development of small molecule neuroprotective drugs, as well as more broadly to the synthesis of stereodefined, bioactive alkaloid skeletons.

NSF Awards · FY 2025 · 2025-09

Fatigue refers to the mechanical failure of materials subjected to repeated cyclic loads. It occurs in all materials including metals and alloys, and is a significant limitation that affects all engineering structures and devices (both structural and functional). It is a common cause of failure (and accidents) in devices including computers, cars, bridges and airplanes, and thus a significant economic, societal and national defense challenge. Unfortunately many fundamental aspects of fatigue remain incompletely understood, even though decades of empirical knowledge have provided (conservative) material specific guidelines for the design of engineering components to avoid fatigue in specific materials. The advent of additive manufacturing and advanced alloys have pushed us beyond this empirical knowledge base. In particular, recent experimental observations suggest situations where additively manufactured metallic alloys have fatigue strength that greatly exceed their conventionally manufactured counterparts, and other situations where they greatly underperform. The investigators will develop a new data-driven approach predicated on the view that the spread of fatigue life can be attributed to particular details of defects and microstructure, and a fundamental understanding of this relationship can lead to new Structural Alloys for Fatigue Endurance (SAFE). The approach is to create an integrated database and knowledge map of material and processing parameters, microstructure, comprehensive mechanical characterization, post-failure analysis and computational experiments on the fatigue behavior of additively manufactured structural alloys. Innovations in methodology including efficient high throughput testing and serial sectioning combined with Electron Backscatter Diffraction (EBSD) to acquire three-dimensional images of microstructure with orientation around individual crack initiation sites, in operando synchrotron observation and accelerated approaches to simulation enable the creation of this database. New methodologies are developed to sample the knowledge map and add new experimental results and simulation until there is a significant area of knowledge where the control parameters predict the quantities of interest. This leads to a deep fundamental understanding of the exact mechanisms and features that initiate, inhibit and accelerate fatigue cracks, and subsequently to the inverse problem of designing new SAFE materials. The approach is developed with a focus on the widely used aerospace alloy Ti-6Al-4V. The team consists of experts in additive manufacturing, texture & characterization, fatigue, computational modeling and the application of machine learning to materials. 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 Awards · FY 2025 · 2025-09

This project builds the next-generation Python Simulations of Chemistry Framework (PySCF) software platform to make electronic structure simulations faster, more robust, and more accessible to computational scientists across many disciplines. The new cyberinfrastructure will enable researchers to better understand the behavior of complex molecules and materials, which plays a crucial role in advancing energy technologies, catalysis, drug discovery, and quantum materials. By harnessing modern computing architectures such as graphics processing units (GPUs) and developing advanced quantum chemistry algorithms, the project will significantly speed up large-scale quantum simulations while reducing computational cost. The project will also produce user-friendly interfaces, manuals, tutorials, and training materials to support education and workforce development in computational science. As an open-source and extensible platform, the PySCF software will catalyze innovation across a broad research community, including chemistry, physics, materials science, artificial intelligence (AI), and quantum information science. First-principles simulations play an essential role in chemistry and materials research, yet the user adoption of more robust electronic structure methods has been hindered by the lack of open-source, high-performance, and user-friendly software infrastructure. The sustained innovation of new quantum chemistry tools is also often hampered by high code complexity and limited extensibility of existing software implementations. This collaborative project addresses these fundamental challenges by advancing the PySCF framework to deliver high-efficiency electronic structure tools and an extensible method development platform. Specifically, this project will develop GPU-accelerated quantum chemistry infrastructure, a low-rank density fitting engine to exploit sparse tensor structures, and a quantum embedding library to enable simulation of complex systems. By incorporating automatic capabilities such as autodifferentiation and designing reusable and modular libraries, this project will substantially lower the barrier for developing quantum chemistry methods and incorporating electronic structure components into AI workflows. Furthermore, a wide selection of cutting-edge stochastic and multireference methods, such as auxiliary-field quantum Monte Carlo and complete active space perturbation theory, will be implemented and integrated with new acceleration techniques. Overall, this project will open new frontiers for accurate and scalable simulations of molecules and materials. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Chemistry in the Directorate for Mathematical and Physical Sciences. 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.

NIH Research Projects · FY 2025 · 2025-09

Abstract Deep-tissue imaging remains a fundamental challenge in biomedical optics due to light scattering, limiting high- resolution optical imaging to depths of approximately 1 mm, also referred to as the optical diffusion limit due to the use of ballistic or quasi-ballistic photons. Photoacoustic tomography (PAT) uniquely circumvents this limitation by using deep penetrating diffuse light to excite photoacoustic waves, which are then detected ultrasonically, leveraging the low scattering of sound in biological tissues to provide high spatial resolution. This proposal aims to push the imaging depth of PAT from the current limit to 6 cm while providing high spatial resolution. Achieving this ambition requires fundamental improvements across the entire imaging chain, from optical excitation to ultrasonic detection and image reconstruction. We propose the following advancements: (1) optimizing SNR by scanning laser pulses with a higher repetition rate to satisfy both ANSI safety limits and incorporating ultrasonic excitation for accurate acoustic speed-of- sound imaging and de-aberration, (2) enhancing ultrasonic detection by maximizing the detection solid angle and packing density (i.e., fill factor) while providing spatial Nyquist sampling with coded masking, (3) refining joint reconstruction augmented by ultrasonic excitation to de-aberrate acoustic blurring and tailoring motion correction to mitigate motion artifacts over extended acquisition times, and (4) performing in vivo imaging of human breasts to validate the proposed technology using contrast-enhanced MRI as the gold standard owing to its shared ability with PAT to image blood vessels. The team has achieved multiple milestones in PAT, including the first in vivo functional PAT, the first 3D pho- toacoustic microscopy with cellular resolution, and the most widely adopted PAT reconstruction method. These foundational contributions have established PAT as the leading high-resolution optical imaging technique in terms of deep-tissue penetration. Despite its success, further technical breakthroughs are required to address the challenges of providing even greater penetration. This proposal introduces a synergistic approach by optimizing laser delivery, ultrasonic detection, acoustic de- aberration, and advanced reconstruction algorithms to achieve a quantum leap in PAT. The proposed innovations will significantly enhance PAT’s diagnostic potential in biomedicine, particularly in breast cancer detection, where deep-tissue visualization is critical for early detection and treatment monitoring. The impact of this research extends to a broad range of biomedical applications. In summary, by systematically improving PAT from excitation to detection and reconstruction, this work will es- tablish the next-generation PAT, capable of transforming clinical imaging. The proposed research aligns with the long-term goal of developing PAT into a widely accessible, non-invasive imaging tool that provides greater imaging depths with high resolution.

NSF Awards · FY 2025 · 2025-09

The majority of rocky planets that have both size and mass measured are much bigger than Earth, and studies suggest that an Earth-like composition may be common among them. However, the interior composition of truly Earth-sized planets remains largely unexplored. This proposal makes use of the newly-commissioned Keck Planet Finder (KPF) spectrograph to precisely measure the masses of 12 Earth-sized exoplanets whose size was already determined by transit measurements. These precise mass measurements are necessary in advance of more detailed characterization efforts. The project personnel will support outreach and educational activities: mentoring opportunities in Hawaii and lecture series in both English and Spanish for the general public in Southern California. Giant impact simulations predict that Earth-sized planets may exhibit greater diversity in their interior composition than super-Earths: they likely experience only a few giant impact collisions, whereas super-Earths undergo dozens. Hit-and-run collisions could make the remnant planet denser. If mass growth is mainly by pebble accretion, interior compositions could be size-independent but depend on the stellar composition. This program will test these hypotheses using one of the most advanced echelle spectrometers ever built: KPF is designed to achieve radial velocity precision of 30 cm/s. Coupled with the 10m Keck telescope, it is the most powerful and efficient system in the Northern Hemisphere for this work. Subsequent to this work, the planets may be suitable for follow-up measurements to characterize their atmospheres or the mineralogy of their bare rock surfaces. 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 Awards · FY 2025 · 2025-09

Merging supermassive black hole binaries (SMBHBs) are exciting sources for gravitational wave detections with space-based gravitational wave observatories and pulsar timing arrays. Since they will likely be surrounded by a gaseous accretion flow, they can also power multi-messenger transient emission before, during and after merger. This project will investigate a novel accretion regime that could give rise to new electromagnetic detection channels of SMBHBs and their merger. The researchers will investigate the magnetically arrested (MAD) accretion regime of a SMBHB, in which the black holes are embedded in a strong magnetic field regulating the accretion flow and leading to periodic magnetic flux eruptions into the accretion disk. This project will positively contribute to the training of the STEM workforce. The junior personnel on the project will learn analytic and problem-solving techniques, including computational methods and competence with standard quantitative analysis and programming tools, which will enhance their productivity in whatever future endeavors or careers they pursue. These investigations will contribute to our understanding of future multi-messenger gravitational wave events of merging supermassive black hole binaries and their orbital evolution. This includes investigating a novel magnetically arrested (MAD) accretion regime for circumbinary accretion flows onto SMBHBs. In particular, the researchers will determine whether this regime influences the orbital dynamics (and hence the observed merging population) of SMBHB. This project will also perform galactic-scale accretion simulations (from Mpc to pc scales) to demonstrate under which condition a hypermagnetized accretion flow can form, which can support a MAD regime. Finally, they will investigate what type of multi-messenger transients a MAD circumbinary disk regime will give rise to, particularly before during and after merger. As a direct outcome, these studies will provide observable signatures for merging SMBHBs, such as recently proposed ideas on near-infrared flares after merger. 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 Awards · FY 2025 · 2025-09

Black holes swallowing gas produce the brightest, most powerful sources of radiation in the Universe. That energy can dramatically change everything around the black hole, fundamentally reshaping how stars and galaxies form. This project will develop a new generation of models for gas inflow into black holes, with strong magnetic fields that can completely change how these systems behave. Black holes are one of the topics in modern science that most excites the public and stimulates a younger generation to explore scientific careers. This project will engage directly with that effort by training graduate students in science and by producing scientific results that can be communicated to the broader public through talks and movies available on YouTube and used in planetaria and other venues. Our understanding of supermassive black hole growth and accretion, as well as feedback on galaxy formation, is at a transformative juncture. Theoretical models are finally able to connect realistic models of the interstellar medium on galactic scales to the inner black hole accretion disk. This project will support study of a new class of strongly magnetized black hole accretion disks, including their theoretical properties and their connection to observations of the massive black hole ecosystem. Collectively the proposed work will dramatically advance our understanding of black hole growth and the properties of active galactic nuclei. 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.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY: This interdisciplinary established team initiative will provide the neuroscience community with a toolkit of engineered adeno-associated virus (AAV) reagents for cell type-specific transgene expression in non-transgenic rodents and non-human primates (NHP). While existing AAV capsids engineered for enhanced BBB crossing in macaque NHP from us and others vastly outperform AAV9 after intravenous injection, they remain far short of the potency of equivalent tools in rodent. To achieve functional parity, we will leverage our established track-record in AAV capsid engineering paired with mechanistic insight based on blood-brain barrier (BBB) receptor-mediated transcytosis pathways we recently discovered. The resulting NHP capsids will enable brain-wide payload delivery, e.g. for efficient primate cell type-specific enhancer screening, and utilization of existing gene regulatory element strategies for neuronal cell type specificity (Aim 1). Our approach will utilize structure-informed capsid libraries selected in vitro against BBB receptors known to promote strong transcytosis and we will scale up our screening technologies for discovery of additional novel BBB receptors engaged by AAVs identified through mechanism-agnostic directed evolution. We will generate a toolkit of >60 AAV capsids each for direct and systemic delivery, in addition to >30 AAV cargo miRNA target site designs with distinct neuronal cell subtype-specific expression patterns in mouse (Aim 2). Using ‘null’ AAV capsids that require an additional non- natural membrane protein interaction in order to infect cells, we will mine recently announced comprehensive mouse brain cell transcriptomic atlases and employ a custom automation platform for high throughput in vitro AAV engineering against membrane proteins with cell subtype-specific patterns of expression. In parallel, we will use spatial transcriptomics and machine learning to identify and characterize novel post-transcriptional gene regulatory elements. These capsids and miRNA target sites will synergize with and complement enhancer-AAV strategies for neuronal cell type specificity. To ease adoption of these tools, we will establish a rigorous reagent characterization and dissemination pipeline (Aim 3). Identified reagents will be validated in vivo via quantification of cell type potency and specificity with all metadata and data made available through online repositories. Reagents will be adapted for broad dissemination in plasmid and vector formats via an established collaborative network.

NSF Awards · FY 2025 · 2025-09

Gravitational-wave (GW) physics and astronomy have entered a new era: GW transient events detected with the LIGO and Virgo detectors in their first four observing runs (O1, O2, O3, and O4) are frequent. So far, they are all from compact binary coalescing (CBC) systems containing merging black holes and/or neutron stars. The fourth observing run (O4) is planned to continue through November 2025. This is resulting in increased rates of discovery of GWs from compact binary mergers, including the potential for rare and exceptional events with high black hole spins, spin-induced orbital precession, and/or eccentric orbits - all of which give crucial clues to the formation of compact binaries in astrophysical environments. There is the potential for many discoveries of GWs from other astrophysical sources such as GW bursts that are not well modeled by templates derived from General Relativity; indeed, entirely new classes of GW sources may be discovered. These observations will enable a wealth of studies, ranging from fundamental physics to astronomy, astrophysics, and cosmology. The PI's team, working with the LIGO Laboratory and LIGO, Virgo, and KAGRA (LVK) Collaborations, develops methods to confidently identify weak GW signals from astrophysical sources in the noisy detector data and interpret the results in meaningful ways. The project will further develop and employ these methods using data from the LVK O4 run. The team will be deeply involved in the assembly of the fifth and sixth GW Transient Catalog (GWTC-5 and 6) covering the last 2/3 of data from O4, robust analysis of individual events with Bayesian parameter estimation, and identification of exceptional events that may not fit into the overall population of events observed so far. We will work with the LVK to present these results in publications that will be foundational in the fields of GW physics and astronomy. During the period covered by this award, the PI will continue and deepen their efforts towards making their science accessible to a broad range of people and groups, through the following activities: conducting a GW science study group for undergraduates throughout the academic year, including weekly meetings and lectures as well as research project mentorship, with participants from Caltech, Pasadena Community College, and other local colleges and universities; mentoring students in the LIGO Summer Undergraduate Research Fellowship (SURF/REU) program; training undergraduate research students in scientific computing and GW data analysis in GW Open Science Center (GWOSC) Open Data Workshops; and supporting open science through the GW Open Science Center. The project focuses on the identification of rare and exceptional events in the GW Transient Catalog of confidently detected binary black hole (BBH) mergers, which may have significant spin-induced orbital precession and measurable eccentricity in the LIGO-Virgo frequency band. The team will work to extend GW waveform models derived from numerical relativity to include all the relevant physics, including (for the first time) eccentric orbits. The team will apply Bayesian parameter estimation to promising detected events, developing robust methods to identify events with significant precession and/or eccentricity, and explore whether they form a distinct population beyond what has been observed so far. The team will search for BBH events with eccentricity using both modeled waveform templates and "model-informed" GW burst methods, and contribute to the search for BBH and other short-duration GW bursts in O4 data (offline) with burst methods. These activities broaden the discovery space of GW sources and are among the most important and urgent frontiers in GW astrophysics. The goal is to have advanced methods in place and in use for the fifth observing run (O5), planned to begin in early 2028. 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.

NIH Research Projects · FY 2025 · 2025-09

Project Summary After nearly four decades since the first crystal structure of a human MHC was published, it is still unclear how exactly T cells engage and become activated by peptide-MHC (pMHC) presented on host cells. T cells are a cornerstone of the immune system, and the interface between T cells and host cells consists of an ensemble of adhesion and signaling proteins known as the “immunological synapse.” Central to this interface are pMHC and its binding partners—the T cell receptor (TCR)-CD3 complex and coreceptor CD4 or CD8. The coreceptors can greatly amplify TCR binding and activation, and a variety of mechanisms such as cooperativity, allostery, and oligomerization have been proposed. Efforts to uncover this mystery through structural studies have resulted in atomic-resolution structures of the individual proteins, allowing for theoretical structural models of pMHCII engaging TCR-CD3 and CD4. However, the theoretical models have failed to explain how CD4 contributes to enhanced TCR binding and signal transduction; therefore, experimentally determined structures of immunological synapse are needed to shed light on this critical component of the immune system. In this proposal, established methods, as well as new developments in engineering enveloped virus-like particles (eVLPs), will be leveraged to determine novel experimental structures of the central components of the immunological synapse. The hypothesis is that the simultaneous binding of full-length TCR-CD3 and CD4 to pMHCII induces biologically relevant structural changes that are not apparent in the current model obtained by superimposing the protein complexes. In order to address this gap, in Aim (1) we will use cryo-electron microscopy (cryo-EM) to determine the structure of pMHCII engaged with full-length TCR-CD3 and CD4. While detergents are necessary to stabilize membrane proteins for cryo-EM, it would be beneficial to visualize and compare the structures in a more native environment. Therefore, Aim (2) will use cryo- EM and cryo-electron tomography (cryo-ET) to determine the structure of membrane-anchored pMHCII engaged to TCR-CD3 and CD4 using enveloped virus-like particles (eVLPs). An endosomal sorting complex required for transport (ESCRT) and ALG-2-interacting protein X (ALIX)- binding region (EABR) motif will be appended to the intracellular tail of each protein, prompting the self-assembly and budding of eVLPs containing pMHCII and separately eVLPs containing TCR-CD3 and CD4. Once initial structures are obtained for each aim, CD4 variants that affect binding affinity or kinase Lck recruitment will be introduced and structurally investigated. These data will reveal how T cells engage pMHCII and will inform future strategies of modulating T cell activation for targeted disease treatment.

NSF Awards · FY 2025 · 2025-09

Mud from the Mississippi River built the vast wetlands of Louisiana. Nearly 2000 sq. miles of these wetlands have become open water since the 1930s, wiping out coastal communities and leaving others vulnerable to natural hazards. Crevasses – cuts in the river levee where water and mud flow into the surrounding wetlands are a proven, economical tool for rebuilding these wetlands. River managers have historically adopted a policy of closing crevasses because these cuts can impact the use of the river as a navigation channel and enhance salinity intrusion when the river is low, threatening drinking water supplies. However, crevasses are expected to become more common in the coming decades, especially in areas where channel bank protection is less intensive. The United States is currently lacking a formal framework to incorporate crevassing as part of river management efforts. This project brings together state and federal resource management agencies, private organizations, environmental advocacy nonprofits, and local universities and technical colleges. The project will create the tools and techniques needed to support effective management decisions and to develop a workforce that is both connected to community needs and capable of contributing to long-term planning and adaptive management of the crevasse system. On the lower Mississippi River, crevasse management is key to sustaining valuable wetlands while enabling the river to meet the needs of communities and commerce. Crevasses are an indispensable component of any resilient future for the Mississippi River Delta, but the crevasse network is most effective when managed as a system rather than individual ad hoc efforts. Systematic management requires a firmer understanding of water and sediment pathways through crevasses, their interactions with the main river channel, and their interactions with each other. Critically, it also requires a conceptual framework that is grounded in both geomorphology and management practice to explain how anthropogenic activities have influenced crevasse performance in the past and how those activities are most effective. This project will develop tools and techniques that can be used to target water and sediment delivery throughout the crevasse network and balance the function of the river for the many stakeholders that rely on it. Furthermore, the project creates a workforce development program to produce practitioners in the local community that can design and monitor crevasses and understand how to balance the relevant environmental and economic interests. 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 Awards · FY 2025 · 2025-09

One of the most important problems in astrophysics today is understanding what physical processes occur in galaxies as they form and age. To resolve this problem, scientists are studying the low-density gas around galaxies, which is sometimes called a galaxy's atmosphere. New space telescopes are being designed to observe the faint light of these atmospheres. However, these efforts require theoretical models to help decipher what these observations mean. In this program, the investigators will write software to generate simulated observations of galaxies and their atmospheres from theoretical models. This software will be applied to several different galaxy simulations to make predictions for next-generation telescopes. Additionally, this proposal will sustain and build on the innovative public education program at Caltech Astro, which produces more than 50 science outreach events with over 20,000 attendees annually. This program is designed with both standard outreach events and activities to explicitly engage people in original settings like national parks. This program will focus on better understanding the gas in and around galaxies known as the circumgalactic medium (CGM). The proposal team will develop and release an open-source software tool for generating synthetic observations of the CGM in both line emission and absorption in the ultraviolet, optical, and infrared. It will account for collisional ionization and local photoionizing sources, incorporating stellar populations and active galactic nuclei. This tool will be applied to state-of-the-art hydrodynamical simulations of galaxy evolution, such as FIRE, Tempest, and IllustrisTNG to produce synthetic observational data products including quasar and down-the-barrel spectroscopy, emission maps, and integrated field unit datacubes. This program includes, among its many outreach activities, public astronomy lecture series with associated guided stargazing, “Astronomy on Tap” events featuring local researchers presenting science to public audiences at a local pub, dark sky festivals featuring telescope viewing and science presentations hosted in collaboration with numerous national parks (e.g., Death Valley, Sequoia, Great Basin, and Grand Canyon). 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 Awards · FY 2025 · 2025-09

The investigator studies one of the most important and long-standing open problems in mathematics: whether smooth initial conditions in the three-dimensional (3D) incompressible Navier-Stokes equations can lead to a finite-time singularity. The Navier-Stokes equations describe the motion of fluids and are fundamental to science and engineering, with applications ranging from weather forecasting and ocean modeling to aircraft design and pipe flow. Despite their widespread use, key theoretical questions remain unanswered—most notably, the global regularity and uniqueness of solutions in three space dimensions. This question is one of the seven Clay Millennium Prize Problems. The proposed research aims to develop a new mathematical and computational approach to uncover possible mechanisms that lead to singularity formation in the 3D Navier-Stokes equations. This work is significant because understanding how such singularities form could provide new insight into turbulence, which plays a central role in many physical systems. The broader impacts include the interdisciplinary training of graduate students in mathematical analysis, modeling, and large-scale simulation. This research directly supports NSF’s mission to promote the progress of science and advance national welfare. The investigator develops a novel approach to study the potential finite-time singularity in the 3D incompressible Navier-Stokes equations with smooth initial data of finite energy. The project begins by analyzing a generalized version of the equations in a space of fractional dimension slightly above three. In this setting, the space dimension is treated as a tunable parameter that helps eliminate scaling instability and reveals the formation of an asymptotically self-similar blowup solution. The investigator then considers the vanishing viscosity limit as the space dimension approaches three. The numerical evidence suggests that the potential singularity is not of exactly self-similar, but rather of Type II with logarithmic corrections. Using a novel two-scale dynamic rescaling formulation and a derived leading-order reduced two-dimensional system, the investigator aims to identify and eliminate unstable modes in the solution. This will allow the construction of a stable singularity profile and potentially enable a computer-assisted proof of finite-time blowup in a generalized Navier-Stokes system. The successful execution of this research could provide a pathway toward resolving the Clay Millennium Problem and advance the theoretical understanding of turbulence. Graduate students involved in the project will gain valuable experience in rigorous partial differential equation analysis and high-performance numerical computation. 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 Awards · FY 2025 · 2025-09

The PI and graduate students will make precise measurements of the basic properties of free neutrons to improve our understanding of the fundamental forces in nature. Neutrons, trapped in atomic nuclei along with protons, make up about one-half of the observable matter in the Universe. The group will participate in the UCNtau+ (Ultra-Cold Neutron Lifetime) experiment which hopes to make the most precise measurement of the lifetime of the free neutron. This will improve our understanding of the weak nuclear force that plays an important role in understanding the Big Bang at the beginning of the universe as well as nuclear energy generation in the sun and stars. Participation in these experiments by graduate students helps provide the nation with a highly trained workforce in Nuclear Science and Technology, with applications in medicine, new technology, national defense as well as basic science. The PI and graduate students will use novel techniques to perform precision measurements with trapped spin-polarized Ultra-Cold Neutrons (UCN). For the UCNtau+ experiment, which uses a bath-tub size array of permanent magnets to levitate the neutrons and prevent them from being absorbed by material walls, the PI and students will work on data-taking and data-analysis. Participation in this experiment allows graduate students to learn low-temperature cryogenic techniques and quantum control of neutron spins while also helping to provide the nation with a highly trained workforce in Nuclear Science and Technology, with applications in medicine, quantum control, national defense as well as basic science. 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 Awards · FY 2025 · 2025-09

Healthy soil microbiome is essential for productive agriculture, influencing plant nutrition, growth, and resilience. This project seeks to understand the molecular and ecological principles that govern soil microbiome composition and function, with the goal of developing strategies to reintroduce and maintain beneficial microbes in agricultural systems. The insights gained from this study will enable precision engineering of native and synthetic microbial communities that improve nutrient uptake and drought tolerance in crops and promote sustainable agriculture. Educational activities will bring microbiome science to the broader community through workshops, public events, and student-led programming, helping train the next generation of scientists while addressing the US national priorities in food security. This research combines microbial ecology, synthetic biology, and plant-microbe interaction studies to investigate how carbon metabolism shapes microbial community structure and function in soil. Despite the importance of soil microbial communities, the mechanisms governing their assembly, stability, and persistence remain poorly understood. Using a well-defined synthetic microbial community, the project will identify carbon substrate preferences among plant-beneficial bacteria, engineer bacterial strains to enhance nutrient solubilization and plant drought resilience, and develop novel biocontainment strategies using selective carbon auxotrophy. By integrating high-throughput phenotyping, metagenomics, and microbial engineering, this work will generate new tools and knowledge for precision microbiome engineering in agriculture, with broad relevance to other ecosystems and biotechnological applications. 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 Awards · FY 2025 · 2025-09

Type Ia supernovae are some of the brightest and most important stellar explosions in the universe. They are used to measure cosmic distances and to study the accelerating expansion of the universe, but the exact process by which they explode remains uncertain. One leading theory suggests that these explosions occur when two white dwarfs -- dead stars -- orbit closely and begin to merge until one of them detonates, ejecting its companion at extraordinary speeds. These "hypervelocity" white dwarfs travel fast enough to escape the Milky Way and offer direct clues to how these explosions occur. This project will search for and study these rare, fast-moving white dwarfs using data from the Gaia satellite and large ground-based telescopes. By finding more of these supernova survivors and analyzing their properties, the project will provide new insights into the origins of Type Ia supernovae. It will also support public education through outreach events and new classroom materials based on real astronomical data. Graduate, undergraduate, and high school students will participate in the research, and the results will be shared broadly with the scientific community and the public. The project aims to constrain the progenitor channels of Type Ia supernovae by identifying and characterizing hypervelocity white dwarfs (WDs) that survive thermonuclear explosions. These stellar remnants are the clearest observational evidence for the double-degenerate channel and offer unique constraints on explosion physics, binary evolution, and SN yields. The research program includes a systematic, selection-function-defined search for hypervelocity WDs down to Gaia G = 20.5, spectroscopic classification of ~75 candidates, and high-resolution spectroscopy of confirmed hypervelocity survivors. Surface abundances and stellar parameters will be modeled using TMAP, and evolutionary tracks constructed with MESA. Hydrodynamic simulations with FLASH will model the SN ejecta's impact on the companion and assess whether a secondary detonation is triggered. Population synthesis modeling will be used to infer the birth rate of hypervelocity WDs and quantify the fraction of SNe Ia arising from this channel. The project will leverage SDSS-V and DESI archival spectra to search for additional exotic runaways and will produce public data products and code for community use. 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 Awards · FY 2025 · 2025-09

Much of the Arctic is underlain by perennially frozen ground known as permafrost. Over the last few decades, the Arctic is thawing and destabilizing riverbanks and affecting infrastructure, water quality, and fish habitat. Additionally, a significant portion of the United States' natural resources and national security interests are contained within river corridors in Alaska. Arctic and Subarctic Federal, State, and Tribal governments need advanced knowledge and tools to identify and assess more accurately riverbank erosion vulnerability and risk in order to guide local decision-makers. Phase-1 of this work includes an interdisciplinary team of physical and social scientists, land managers, engineering design firms, stakeholders and land owners at local, tribal and federal levels. This team is well positioned to integrate advanced research techniques with community needs to document and forecast ongoing landscape and river changes, and enable the development of pragmatic solutions to protect investments in infrastructure. This project is poised to make an impact with science that informs public policy; increases partnerships between local community members, academia, industry, non-profit, and government sectors; and develops an American workforce in interdisciplinary applied science. This project will develop new state-of-the-art approaches to critical and immediate environmental threats to communities and infrastructure in Arctic Alaska. Solution strategies include: 1) information-based tools for decision making including river-erosion forecasting tools and watershed monitoring networks; and 2) physical solutions to changing rivers including community scale infrastructure to mitigate erosion and siltation and watershed scale solutions. The project will leverage recent advances in Earth science including satellite imagery and novel sub-pixel and machine-learning techniques for change detection, theoretical advances in permafrost erosion and mud transport prediction, low-cost sensor networks for autonomous monitoring of water quality, high-throughput microbial sequencing-as-sensing techniques, and collaborative cyberinfrastructure for watershed monitoring. Solutions will be used to forecast river erosion to protect important infrastructure, increase the ability to mitigate physical risk once identified, and manage water quality for human health and aquatic life. The modeling tools can be broadcast into the future, aiding in decision making that will minimize long-term damage and 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.

NIH Research Projects · FY 2025 · 2025-09

Proposal Summary The neural crest is an embryonic cell population which gives rise to varied derivates along the developing vertebrate body axis. Neural crest from the cranial region forms the craniofacial skeleton, while subunits of the adjacent vagal neural crest form parts of cardiac mesenchyme and the enteric nervous system. The physical boundaries between these regions have been established via quail-chick grafting experiments which demonstrate that, prior to neural crest emigration from the neural tube, the fates of each region are non- interchangeable. Few previous studies have assessed gene regulation differences by subregion to explain this phenomenon, and even fewer have looked at single-cell resolution or at premigratory stages. We aim to address this gap in knowledge by using high-resolution modern techniques to interrogate the subtle differences in gene expression and regulation between the cranial, cardiac, and enteric subregions of the premigratory neural crest in the head and neck. We hypothesize that slight modifications in gene expression programs between these neighboring populations may be amplified in order to bias each subpopulation to a unique, non-interchangeable fate. Ultimately, this work will aid in our understanding of the mechanisms which establish fate boundaries between neural crest subpopulations of varying axial levels, leading to the loss of ectomesenchymal potential in more posterior regions of the body. Aim 1: Transcriptional profiling of premigratory head and neck neural crest. Previous work to address the transcriptional state of neural crest in the head and neck has typically taken a bulk-sequencing approach, worked at migratory stages, or pooled cells from multiple axial levels. Here, we propose using a plate-based single-cell RNA sequencing method on premigratory neural crest cells at cranial versus cardiac versus enteric axial levels. We will identify transcription factors which are differentially expressed in the neural crest between these levels and assess their role in regulating cell fates from our regions of interest. Aim 2: Determine transcriptional regulation controlling boundary setting in premigratory head and neck neural crest. Previous studies on regulatory circuits within the premigratory neural crest have primarily focused on cranial neural crest. We aim to understand the differences in transcriptional regulation before emigration which establish different fate potentials. We will perform ATAC-sequencing on premigratory neural crest cells from the cardiac and enteric regions to compare with published premigratory cranial crest data. We will identify putative enhancers for transcription factors of interest and computationally identify their regulatory inputs to assess differences in gene regulatory circuits across axial levels.

NSF Awards · FY 2025 · 2025-09

Millions of patients each year rely on medical procedures that use sound waves to break apart kidney stones or target diseased tissues without surgery. As these technologies advance, so does the need for greater precision, safety, and adaptability in treatment. This project contributes to the development of digital twins — real-time computer models that simulate how sound waves interact with the body and, based on imaging as the procedures unfold, help guide the process. By enabling more accurate and responsive treatments, such models could significantly improve clinical outcomes and reduce costs in noninvasive medicine. Beyond the immediate medical application, the project addresses a broader national need: the development of fast, reliable computational tools for predicting and controlling complex physical systems in real time. These methods are broadly applicable to technologies that rely on wave-based sensing and actuation, including systems in biotechnology, nondestructive materials testing, environmental monitoring, and national defense. The project will also serve as a multidisciplinary training ground for graduate students working at the intersection of applied mathematics, computation, and engineering. The research aims to develop fast, accurate algorithms that simulate how high-frequency waves, such as shock waves or focused ultrasound, propagate through complex, heterogeneous materials. The key technical challenge is that, in many real-world systems, waves must be tracked over hundreds of wavelengths, making traditional computational methods too slow for real-time use, especially when repeated simulations are needed to account for uncertainty or to estimate unknown parameters. To address this, the project will construct reduced-order models that capture the essential dynamics of wave propagation between source and target, while drastically reducing computational cost. These models will be designed to adapt in real time based on measurements from the system, enabling rapid prediction, control, and decision-making. The algorithms will be validated through comparison with full-scale simulations and, where possible, experimental data from laboratory-scale models of therapeutic ultrasound. The work is expected to lead to new strategies for real-time modeling and control in complex wave-driven systems. 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 Awards · FY 2025 · 2025-08

Current technological developments have given rise to artificial simulations of human language production, in the form of large language models. Simulation, however, does not mean explanation, and a good theoretical understanding of language as a computational system is still an important, and urgently needed, scientific goal. Human language is a highly structured natural phenomenon that shares many of the qualities of physical systems: in particular it can be modelled mathematically with a high degree of precision and prediction power. The principal investigator (PI), in collaboration with Chomsky and Berwick, has developed a novel mathematical model of syntax in human languages, and this project aims at extending this model to capture all aspects of the human faculty of language. There have been various empirical tests attempting to evaluate to what extent artificial systems like large language models capture the intricate aspects of language syntax, and whether or not they resemble language as produced by human brains. Ultimately, a rigorous analysis of such questions requires the development of precise mathematical models of language in humans and in machines and a direct comparison of them through quantitative invariants that can be directly computed, which this proposal aims at developing. Given the current pace of technological development in AI research and the growing use of LLM technology in society, and the fact that rigorous scientific theory is dangerously lagging behind the technological developments, the introduction of more advanced and more powerful mathematical methods in the study of language is very timely and important to the national interests. Recently the PI, in joint work with Noam Chomsky and Robert Berwick, obtained a new mathematical formulation of the Merge structure-building operation of syntax that is key to the Minimalist Model, as a Hopf algebra Markov chain on a combinatorial Hopf algebra of binary rooted trees. This mathematical model shows that syntax is a computational process governed by a rigid algebraic structure, that many empirical assumptions of linguistics can be derived directly from algebraic properties, and that human language has certain optimality properties. The goal of this project is to extend and develop this mathematical model to capture all aspects of syntax, including interfaces with morphology and semantics and to obtain rigorous models of Externalization and syntactic parameters. The project also aims at the development of quantitative mathematical methods for comparing language formation in humans and in artificial systems like large language models and measuring the extent to which the latter can reconstruct the computational process of syntax from its imperfect embedding into data of semantic proximity. 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.

NIH Research Projects · FY 2025 · 2025-08

ABSTRACT The evolution of vertebrates has been significantly shaped by the emergence of the neural crest, a critical innovation believed to have bolstered predatory prowess and fostered the expansion of craniofacial structures. During development of vertebrate embryos, distinct neural crest subpopulations arise along the body axis. While these subpopulations share a basic neural crest gene regulatory network (GRN), superimposed upon this are distinct regional subcircuits that imbue subpopulations with distinct developmental potentials. Indeed, only the cranial neural crest in amniotes possesses the ability to generate ectomesenchymal derivatives like osteoblasts. Recent studies have demonstrated that axial level specific GRN subcircuits play a critical role in enabling neural crest cells to develop specific cell types, with amniotes possessing a cranial-specific circuit capable of reprogramming trunk neural crest cells to form craniofacial cartilage. In our recent research, we discovered that trunk neural crest cells in sturgeons, a primitive group of bony fish, possess the remarkable ability to create bony structures in the postcranial region, suggesting that the ancient neural crest has the ability to contribute to the formation of skeletogenic tissues along the entire neural axis. By utilizing this unique model organism that has dermal bones from head-to-tail, my goal is to undercover the underlying fundamental GRN driving neural crest- derived bone formation. I hypothesize that this basic GRN may have served as a scaffold that became elaborated and increased in complexity during vertebrate evolution, culminating in craniofacial bone formation in mammals. This proposal will determine the presence of genes akin to amniote "cranial-specific" gene regulatory circuit in sturgeon. To investigate this, hybridization chain reaction and CRISPR/Cas9-mediated mutagenesis will be used to examine coexpression and linkages within the GRN subcircuits in migrating neural crest cells and their derivatives. Next, single cell RNA-sequencing and unbiased comparative transcriptomic analysis will be performed on sturgeon neural crest cells at cranial and trunk levels and compared with chick and lamprey datasets to uncover genetic circuits characteristic of sturgeon neural crest subpopulations, particularly those associated with skeletogenesis. Finally, ATAC-seq assays at various axial levels and developmental stages during sturgeon neural crest development will be used to pinpoint potential enhancers and assess alterations in open chromatin patterns based on axial location and developmental timing. Together, the results of these aims will illuminate the mechanisms underlying the origin of new cell types, such as osteoblasts, within the neural crest. In addition to identifying useful targets for therapeutic intervention preventing craniofacial defects, this award will provide me with necessary training as I prepare to begin my independent career. Dr. Marianne Bronner's laboratory at the Caltech and the assembled advisory council offer essential resources, knowledge, and training atmosphere required to effectively pursue the proposed objectives and help me establish an independent research career.

NIH Research Projects · FY 2025 · 2025-08

Project Summary/Abstract Understanding the axes that organize the large and diverse space of odor stimuli for efficient encoding and decoding is a core challenge in olfaction. In addition to their physicochemical properties and molecular features, an important property of odorants is how they are organized relative to one another in natural environments. We hypothesize that the statistics of odorant correlations in natural settings, shaped by conserved metabolic and biochemical pathways in behaviorally important odor sources, are important to extracting information about the identity and ethological value of the source. To understand how animal brains accomplish this task, we trace how odors are formatted and encoded at successive stages of neural processing in the olfactory system of the vinegar fly Drosophila melanogaster. We recently discovered that the fly olfactory code is unexpectedly restructured between primary olfactory receptor neurons (ORNs) at the periphery and the mushroom body (MB), a third-order associative olfactory processing region. Specifically, odor relationships encoded in the MB better reflect the relationships of monomolecular volatiles in behaviorally relevant natural sources, compared to their similarity with respect to chemical features, and the converse was true for odor relationships encoded in peripheral ORNs. The goal of this project is to understand the principles and neural mechanisms underlying this restructuring, guided by the hypothesis that this process reflects the progressive reformatting of the olfactory code to encode variables relevant to behavioral significance. To achieve this goal, Aim 1 will test the hypothesis that an important organizing principle for olfactory coding and behavior is the metabolic relationship between odorants, structured by conserved biochemical processes in natural odor sources; Aim 2 will systematically map the transformation of odor representations at each synaptic stage of olfactory processing, thereby elucidating the neural circuit mechanisms that underlie these transformations; and Aim 3 will determine how neural activity and olfactory experience contribute to the structure of olfactory codes in the MB. Our research plan describes how we will achieve these goals by leveraging the well-mapped connectivity of the fly nervous system, the ability to selectively measure and manipulate neural activity in defined neural populations, and the adaptation of geometric approaches, originally developed for understanding human visual perceptual spaces, as a computational framework for mapping how olfactory representational spaces are transformed along the fly olfactory pathway. This project will advance our understanding of the broad and important problem of how sensory systems capture natural stimulus structure and use it to progressively reorganize sensory representations into formats useful for making semantic inferences about objects in the natural world in relation to their behavioral needs.

NSF Awards · FY 2025 · 2025-08

Models of the physical and chemical behavior of partially molten rocks form a key component of scientists' ability to study and understand volcanic systems. Together with field-based studies, experimental analyses, and investigations of prior eruptions, these models are important for advancing our knowledge of potentially hazardous volcanoes in the United States and globally. This project continues development of a flexible, powerful, and easy-to-use suite of modeling software tools used by thousands of Earth scientists: alphaMELTS. This project will expand the scenarios that alphaMELTS can model, increase integration with igneous rock and experimental databases, link to other geochemical modeling tools written in Python, and support users with workflows for increased reproducibility. Online resources and outreach workshops will extend applications of the software in teaching and training. These workshops, both virtual and in-person, will equip scientists from various career stages and experience levels with quantitative tools for modern Earth science research. This project will implement a framework to align alphaMELTS petrologic modeling software and workflows with FAIR principles (findable, accessible, interoperable, and reusable). Planned developments will make alphaMELTS fully open source, easy to install with standard tools, interoperable with associated modeling and visualization tools and databases, callable from many programming and data visualization environments, and fully versioned, logged, and documented. The work will focus on Python-based tools – in particular, via continued development of the PetThermoTools package for beginner-to-intermediate MELTS users, and machine-learning assisted acceleration for high-end users with high-volume throughputs – but also support those who prefer a simpler graphical user interface. A systematic assessment of model performance will guide users towards applications where the software is verifiably accurate. Expanded functionality will include modeling of reverse crystallization and post-entrapment crystallization of melt inclusions, integration with packages like Thermobar and PySulfSat, and a new trace element engine that gives users total control over partition coefficients. This project will increase integration with IEDA2 databases and the VICTOR portal, and engage with users though workshops, online resources, and creation of instructional materials. The core software development team will grow to include two early-career researchers, as well as two graduate student researchers, which will foster the continuity of alphaMELTS services moving forward. 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.

NIH Research Projects · FY 2025 · 2025-08

Fluorescent biosensors and microscopes can measure voltage, calcium, neurotransmitters, and other essential endogenous or exogenous biomarkers. The standard practice is to record the change in biosensor fluorescence intensity over time. The signal can be affected by fluctuations in sensor levels between cells and animals, laser power, imaging position, and other unavoidable experimental factors. Time-resolved fluorescence (TRF) and fluorescence lifetime imaging (FLIM) solve this problem by measuring lifetime instead of intensity. TRF allows well-calibrated measurements of biosensor analyte levels by being resistant to intensity fluctuations. TRF also enables new measurement modalities based on the fluorophore’s local environment, ranging from endogenous fluorescence signals to the near-endless continuum of exogenous FRET and lifetime-based biomarkers. However, portable implementation of lifetime-based approaches is hampered by a pulsed laser’s cost, physical size, power draw, and required domain-specific expertise. The proposal uses integrated photonics to create entangled photon sources that enable highly multiplexed, low-cost, low-power, and portable measurement of TRF/FLIM in a universal package. The Cushing lab has discovered that creating entangled photons with integrated photonics can be used for fluorescence lifetime measurements with both quantum and practical advantages. The advantages include improved tuning range (>500 nm) per source, temporal resolution (< 0.1 ps), a CW-like approach that reduces phototoxicity effects, alignment-free operation through a photonic back end, and <1 cm2 physical size – all powered by the equivalent of a mW laser pointer. Entangled TRF, therefore, appears ideal for portable or wearable, miniaturized TRF and FLIM approaches. The technology can be compared to emerging LED-based miniaturized devices, which lack the ability for high wavelength multiplexing without multiple sources nor the time resolution to distinguish multiple biomarkers and their environmental response. By starting with a CMOS-cost-scalable package using thin film photonics, our innovation will significantly improve health equity by making TRF and FLIM accessible to a broader range of biological and medical researchers. The specific aims of the proposal include 1) optimizing the entangled photon source for excitation- wavelength and temporally multiplexed fluorescence lifetime sensing, 2) extending entangled TRF toward shorter wavelength excitations by transitioning from lithium niobate to lithium tantalate, and 3) integrating on-chip photonic elements for a miniaturized TRF architecture. Collaborators specializing in FLIM and TRF biosensors evaluate each stage of the grant with regard to application, including testing in their labs, to ensure realistic criteria are used in addition to photonic metrics. The proposed research is the first step towards a multiplexed platform that brings TRF and FLIM to broader health applications, including portable medical diagnostics and in-vivo or miniaturized sensors, all using the cost scaling of integrated photonics.