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At least 253 records · Page 14

A Landing Pad System for Multicopy Gene Integration in Issatchenkia orientalis

The robust nature of the non-conventional yeast Issatchenkia orientalis allows it to grow under highly acidic conditions and therefore, has gained increasing interest in producing organic acids using a variety of carbon sources. Recently, the development of a genetic toolbox for I. orientalis, including an episomal plasmid, characterization of multiple promoters and terminators, and CRISPR-Cas9 tools, has eased the metabolic engineering efforts in I. orientalis. However, multiplex engineering is still hampered by the lack of efficient multicopy integration tools. To facilitate the construction of large, complex metabolic pathways by multiplex CRISPR-Cas9-mediated genome editing, we developed a bioinformatics pipeline to identify and prioritize genome-wide intergenic loci and characterized 47 gRNAs located in 21 intergenic regions. These loci are screened for guide RNA cutting efficiency, integration efficiency of a gene cassette, the resulting cellular fitness, and GFP expression level. We further developed a landing pad system using components from these well-characterized loci, which can aid in the integration of multiple genes using single guide RNA and multiple repair templates of the user’s choice. We have demonstrated the use of the landing pad for simultaneous integrations of 2, 3, 4, or 5 genes to the target loci with efficiencies greater than 80%. As a proof of concept, we showed how the production of 5-aminolevulinic acid can be improved by integrating five copies of genes at multiple sites in one step. We have further demonstrated the efficiency of this tool by constructing a metabolic pathway for succinic acid production by integrating five gene expression cassettes using a single guide RNA along with five different repair templates, leading to the production of 9 g/L of succinic acid in batch fermentations. This study demonstrates the effectiveness of a single gRNA-mediated CRISPR platform to build complex metabolic pathways in a non-conventional yeast. This landing pad system will be a valuable tool for the metabolic engineering of I. orientalis.

Fatma, Zia↗

Long-Term field testing of the accuracy and HVAC energy savings potential of occupancy presence sensors in A Single-Family home

The energy-saving potential of occupancy-centric smart thermostats has been extensively explored in simulations but lacked field testing for energy savings quantification and sensor performance assessment in real buildings. This paper presents a long-term field study conducted in a single-family home in Texas, U.S. to evaluate the performance of occupancy-centric controls (OCC) of HVAC (heating, ventilation, and air-conditioning) system in terms of energy savings, sensor accuracy, and impact on electric peak demand. The test site was equipped with a commercial off-the-shelf (COTS) smart thermostat and multiple occupancy presence sensors for OCC implementation. Additionally, a sub-metering system was installed to monitor electricity consumption of various end-use equipment, including the HVAC system. A supplementary device was installed to track the ground-truth occupancy for the accuracy evaluation of the occupancy presence sensor. Scenarios of baseline and OCC controls were alternated weekly over the 20-month testing period. The results indicated an effective OCC execution, as evidenced by indoor temperature profiles. During the 2023 cooling season, OCC achieved total energy savings of 1,958 kWh, corresponding to a 17.6% energy savings ratio. Under certain conditions, daily HVAC energy savings reached as high as 17 kWh, with a savings ratio of 35%. Sensor performance showed an overall accuracy of 83.8%, a False Positive Rate (FPR) of 12.8%, and a False Negative Rate (FNR) of 47.4%. A key limitation was the sensor’s inability to detect stationary occupants during sleep, leading to a midnight FNR of nearly 100% and significantly compromising thermal comfort. Additionally, the implementation of OCC resulted in extended periods of high electricity demand on summer afternoons, affecting occupant’s thermal comfort and posing potential challenges to community-level grid operations if OCC were widely adopted. Furthermore, this study addresses a critical research gap by empirically investigating energy-saving potential and occupancy sensor performance in residential buildings. Through a comprehensive field-testing study, the research examines the interrelationship between sensor accuracy, energy savings, and thermal comfort, an area that has received limited attention in the current literature.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Building confidence in models for complex barrier systems for radionuclides

The modeling and simulation of the Cement-clay Interaction-Diffusion field (CI-D) experiment at the Mont Terri site in Switzerland presented here demonstrates that it is possible to capture the multiscale physical and chemical features of natural and engineered barrier systems for radionuclides. The simulations are successfully carried out with the newly developed CrunchODiTi high-performance computing software that accounts for multiple continua, including a continuum representing the electrical double layer (EDL) developed along negatively charged clay particles in clay rock. The simulation also accounts for both the complex three-dimensional (3D) geometry, expected as the norm in a geological waste repository, and the anisotropy of the geological formation. In addition, the high resolution of the model makes it possible to include "skin effects" developed at the interface between highly reactive materials, in this case between the high pH cement and the circumneutral but electrostatic Opalinus Clay. The successful history matching with the field experiment demonstrates that the distinct geochemical and physical properties of the cement and the Opalinus Clay in the CI-D experiment can be accounted for. Such analyses are essential for developing a defensible safety case for the underground storage of radioactive waste.

Sarsenbayev, Dauren↗

A control-inspired approach for energy transition planning under uncertainty

As the global carbon footprint continues to grow, many countries are implementing carbon emission reduction policies which have incentivized the expansion of low-carbon and renewable technologies. However, the speed and scale of deployment falls short of that needed to meet climate goals. Energy system models serve as key tools for guiding investment decisions and helping policymakers evaluate the effects of various policies on the development of an energy system. This study focuses on the energy system of the United States and builds upon prior work by incorporating more geographic granularity to account for the trade of commodities and addresses transmission congestion through electricity price adjustments. Furthermore, real-world characteristics, such as delays in constructing new liquid fuel production and electricity generation facilities, are integrated using a sequential decision-making approach that better reflects how decisions can be updated as uncertainties unfold. Results demonstrate that stochastic programming combined with sequential decision-making produces energy transition pathways that are robust to multiple uncertain futures. Additionally, considering real-world characteristics significantly impacts the deployment of renewable technologies and the ability to meet carbon emission reduction goals while also reliably meeting demand. These findings highlight the importance of accounting for uncertainty and real-world characteristics to avoid overly optimistic projections in energy system planning.

energy systems↗

A landing pad system for multicopy gene integration in Issatchenkia orientalis

The robust nature of the non-conventional yeast Issatchenkia orientalis allows it to grow under highly acidic conditions and therefore, has gained increasing interest in producing organic acids using a variety of carbon sources. Recently, the development of a genetic toolbox for I. orientalis, including an episomal plasmid, characterization of multiple promoters and terminators, and CRISPR-Cas9 tools, has eased the metabolic engineering efforts in I. orientalis. However, multiplex engineering is still hampered by the lack of efficient multicopy integration tools. To facilitate the construction of large, complex metabolic pathways by multiplex CRISPR-Cas9-mediated genome editing, we developed a bioinformatics pipeline to identify and prioritize genome-wide intergenic loci and characterized 47 gRNAs located in 21 intergenic regions. These loci are screened for guide RNA cutting efficiency, integration efficiency of a gene cassette, the resulting cellular fitness, and GFP expression level. We further developed a landing pad system using components from these well-characterized loci, which can aid in the integration of multiple genes using single guide RNA and multiple repair templates of the user’s choice. We have demonstrated the use of the landing pad for simultaneous integrations of 2, 3, 4, or 5 genes to the target loci with efficiencies greater than 80%. As a proof of concept, we showed how the production of 5-aminolevulinic acid can be improved by integrating five copies of genes at multiple sites in one step. We have further demonstrated the efficiency of this tool by constructing a metabolic pathway for succinic acid production by integrating five gene expression cassettes using a single guide RNA along with five different repair templates, leading to the production of 9 g/L of succinic acid in batch fermentations. Furthermore, this study demonstrates the effectiveness of a single gRNA-mediated CRISPR platform to build complex metabolic pathways in a non-conventional yeast. This landing pad system will be a valuable tool for the metabolic engineering of I. orientalis.

59 BASIC BIOLOGICAL SCIENCES↗

Building Model Calibration: Validation of GridLAB-D Thermal Dynamics Modeling

This report investigates how well GridLAB-D’s house model characterizes the thermal dynamics of buildings given the overpredicted diurnal electric load swing observed in the Distribution System Operation with Transactive (DSO+T) study. This study seeks to validate GridLAB-D’s house model by calibrating it to data from the well-instrumented Pacific Northwest National Laboratory Lab Homes in Richland, WA. The datasets chosen included multiple pre-cooling and pre-heating testing periods where the indoor air temperature was allowed to float over a multi-hour length of time to mimic diurnal behavior. The multi-season calibrations were evaluated by comparing the heating/cooling electric power, indoor air temperature, and the rise/decay time during temperature float periods with Lab Homes data. The default GridLAB-D assumptions for latent load fraction, air heat capacity, mass heat capacity, window-to-wall-ratio, overall envelope conductance (assumed as NORMAL thermal integrity level), and solar heat gain coefficient were compared with the calibrated model to confirm when the default assumptions were adequate and the impact of calibration on the accuracy of modeling the thermal dynamics of homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Innovative Advanced Hydrogen Mobile Fueler (Final Technical Report)

The US Department of Energy (DOE) funded a project to design, develop, deploy and analyze the economic viability of an innovative Advanced Hydrogen Mobile Fueler (AHMF). As part of the design activity the project team defined specifications based upon vehicle requirements and compliance with specific fueling performance criteria. The AHMF was originally designed to fuel 10-20 fuel cell vehicles (FCV) per day, consistent with the requirements of the H70 fueling category. The AHMF is able to operate without remote power connections, is modular for easy transport and deployment, and can provide expanded daily capacity and multi-day operations using delivered gaseous hydrogen. Toward the end of the project, due to request from the hydrogen industry and some necessary modifications of the AHMF, the system is now modified to fuel heavy duty vehicles. The project was conducted over two primary phases, each including several key tasks, subtasks, and project milestones. Phase 1 involved the design, development, and construction of the AHMF, moving from a conceptual design through to completion of assembly and testing. In addition to reviewing several different approaches, the team chose to take a conventional station design and modify it for mobile fueling. There were several innovative components included in the design. The high pressure storage was the first to achieve a US Department of Energy (DOE) Special Permit (SP 20391) to transport high pressure hydrogen (95 MPa) in a composite cylinder. The second novel system was a liquid nitrogen (LIN) cooling system with a compact heat exchanger. Without this change, the cooling system would not be able to fit into the AHMF. Phase 2 demonstrated the AHMF by fueling fuel cell buses at a fleet in Pomona, CA. The site was chosen because a temporary fueling solution was required while a fixed station was being installed. The existing permits for the fixed station and non-public access also was a determining factor. Over two months, the buses were fueled 320 times with over 5000 kg of hydrogen from tube trailers. Existing shore power was used, and the average electrical efficiency was 0.13 kWh/kg. The average liquid nitrogen (LIN) consumption was 90.68 scf/kg. The fueling and consumption data was provided to the National Renewable Energy Laboratory (NREL) for analysis. An economic analysis was performed and will be provided in a separate report. The project was successful, but not without challenges and lessons learned. The DOT special permit led the way for the use of high pressure, composite cylinders and is being by multiple other systems and applications. The pandemic along with time for the DOT special permit approval delayed the project for years. The team also believes that hydrogen mobile fueling has a use for the industry, especially during this upcoming phase of expansion. However, it does have its limitations due to high cost to build and operate, and the same permitting challenges as a fixed station. A fully capable system at the speeds and pressures of the AHMF may not be necessary for most applications and would help reduce the cost and increase storage capacity. The on-board generator can be easily replaced with shore power or the wide range of power generation solutions in the marketplace. One of the major results of the project was the development of new code language in National Fire Protection Agency (NFPA) 2 and the International Fire Code (IFC) for on-demand mobile fueling. This will provide guidance for Authorities Having Jurisdiction (AHJ) and user on how to permit temporary fueling sites across the nation.

08 HYDROGEN↗

Making a Water Data System Responsive to Information Needs of Decision Makers

Evidence-based environmental management requires data that are sufficient, accessible, useful and used. A mismatch between data, data systems, and data needs for decision making can result in inefficient and inequitable capital investments, resource allocations, environmental protection, hazard mitigation, and quality of life. In this paper, we examine the relationship between data and decision making in environmental management, with a focus on water management. We focus on the concept of decision-driven data systems —data systems that incorporate an assessment of decision-makers' data needs into their design. The aim of the research was to examine the process of translating data into effective decision making by engaging stakeholders in the development of a water data system. Using California's legislative mandate for state agencies to integrate existing water and other environmental data as a case study, we developed and applied a participatory approach to inform data-system design and identify unmet data needs. Using workshops and focused stakeholder meetings, we developed 20 diverse use cases to assess data sources, availability, characteristics, gaps, and other attributes of data used for representative decisions. Federal and state agencies made up about 90% of the data sources, and could readily adapt to a federated data system, our recommended model for the state. The remaining 10% of more-specialized data, central to important decisions across multiple use cases, would require additional investment or incentives to achieve data consistency, interoperability, and compatibility with a federated system. Based on this assessment, we propose a typology of different types of data limitations and gaps described by stakeholders. We also propose technical, governance, and stakeholder engagement evaluation criteria to guide planning and building environmental data systems. Data-system governance involving both producers and users of data was seen as essential to achieving workable standards, stable funding, convenient data availability, resilience to institutional change, and long-term buy-in by stakeholders. Our work provides a replicable lesson for using decision-maker and stakeholder engagement to shape the design of an environmental data system, and inform a technical design that addresses both user and producer needs.

Cantor, Alida↗

SCALE Demonstration for Sodium-Cooled Fast Reactor Fuel Cycle Analysis

In support of the US Nuclear Regulatory Commission non-light-water reactor fuel cycle demonstration project, SCALE 6.3.1 capabilities for radionuclide characterization, criticality, and shielding were demonstrated for scenarios in the sodium-cooled fast reactor (SFR) nuclear fuel cycle. Three postulated accident scenarios were selected for analysis in this work. As a basis for all scenarios, irradiated fuel inventories were generated using SCALE/ORIGAMI. To cover multiple SFR design choices, two different types of SFR fuel, uranium/transuranic-loaded and U-based fuels, were considered. For the first scenario, SCALE/MAVRIC was used to calculate the radiation shielding and dose rates inside and outside of the containment building due to a drop of a spent fuel assembly from the fuel-handling system during unloading inside the containment building. For the second scenario, potential critical configurations in an electrofiner were investigated through criticality calculations with SCALE/CSAS. For the third scenario, the activity of the waste salt from an electrorefiner was evaluated using SCALE/ORIGEN. The dose rate produced by the analyzed SFR assemblies is similar to that produced by a typical pressurized water reactor (PWR) fuel assembly with a discharge burnup of 50 GWd/MTU, with the same cooling time of 10 days. The criticality analyses suggested that the different electrorefiner configurations have a large margin to criticality. The activity analysis of the electrofiner waste revealed that shielding and cooling may be required for the waste salt that contains transuranics and fission products produced by the electrorefiner because of the high activity of the waste salt. In general, the application of various capabilities in the SCALE code system for SFR fuel inventory generation, criticality, and shielding was successfully demonstrated for the selected scenarios in the SFR nuclear fuel cycle. Additional analyses can be performed to provide more accurate results when more details of the SFR nuclear fuel cycles are available, for example, the dimension of the electrorefiner and the salt compositions during reprocessing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

PDB-IHM: A System for Deposition, Curation, Validation, and Dissemination of Integrative Structures

Structures of many large biomolecular assemblies are now being determined using integrative approaches. In these approaches, information derived from multiple experimental and computational methods is combined to compute three-dimensional structures of multi-protein complexes and other macromolecular machines. A standalone prototype data resource for integrative structures called PDB-Dev was built, based on recommendations of the Integrative and Hybrid Methods (IHM) Task Force of the Worldwide Protein Data Bank (wwPDB). This effort included developing data standards and software tools for collecting, curating, validating, visualizing, archiving, and disseminating integrative structures that span diverse spatiotemporal scales and conformational states. Mechanisms have been created to validate integrative structures based on the experimental data underpinning them. Building upon this foundational framework, PDB-Dev has been further expanded to handle large dynamic macromolecular systems and integrative structures that combine, for example, experimental restraints with atomic coordinates computed by machine learning algorithms. Data standards and supporting tools have also been extended to capture information about biomolecular dynamics, such as conformational transitions and related kinetic data derived from biophysical methods. Recently, PDB-Dev was unified with the PDB archive and rebranded as PDB-IHM (pdb-ihm.org), further promoting FAIR (Findable, Accessible, Interoperable, and Reusable) principles of data stewardship for integrative structural biology.

IHMCIF↗

Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery

Future scientific discoveries will rely on flexible ecosystems that incorporate modern scientific instruments, high performance computing resources, parallel distributed data storage, and performant networks across multiple, independent facilities. In addition to connecting physical resources, such an ecosystem presents many challenges in logistics and accessibility, especially in orchestrating computations and experiments that span across leadership computing systems and experimental instruments. Past efforts have typically been application-specific or limited to interfaces for computing resources. This paper proposes a general framework for integrating computation resources and instrument operations, addressing challenges in code development/execution, data staging and collection, software stack, control mechanisms, resource authorization and governance, and hardware integration. We also describe a demonstration use case wherein a Bayesian optimization algorithm running on an edge computing resource guides a scanning probe microscope to autonomously and intelligently characterize a material sample. This science edge ecosystem framework will provide a blueprint for federating multi-institutional, disparate resources and orchestrating scientific workflows across them to enable next-generation discoveries.

Somnath, Suhas↗

Distribution System Research Roadmap; Energy Efficiency and Renewable Energy

The scope of the U.S. Department of Energy's Energy Efficiency and Renewable Energy (EERE) office covers a number of distributed energy resource (DER) technologies, including distributed photovoltaics, smart buildings, wind, water, behind-the-meter-storage, and electric vehicles. The impact of these technologies on the distribution system is often assessed with an individual technology focus. Similarly, different technology offices often leverage different sets of tools, leading to analyses that are not comparable. EERE sought the ability to assess the impact of integrating multiple DER technologies, and to comprehensively address DER integration challenges across the portfolio of EERE technologies. This project built on existing work understanding technical challenges, mapped out the key research questions, assessed relevant capabilities across the national laboratory network, identified key gaps, and produced a research roadmap to inform EERE investment decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Cryogenic Muon Tagging System Integrated with a Superconducting Qubit Device for Radiation-Induced Error Mitigation

Superconducting qubits are highly sensitive to ionizing radiation, which can induce correlated errors and limit scalable fault-tolerant quantum computing. In particular, cosmic-ray muons can deposit energy in the substrate, generating phonon bursts that break Cooper pairs and produce quasiparticles, leading to correlated decoherence events across multiple qubits. We present the development of a cryogenic muon tagging system based on Kinetic Inductance Detectors (KIDs) and its integration with superconducting quantum hardware. Originally developed within the ACE-SuperQ project and validated as a standalone detector, the system demonstrated a muon tagging efficiency of approximately 90% and excellent agreement with Monte Carlo simulations. Building on this validation, the tagging system has been integrated with a multi-qubit superconducting chip operated in a dilution refrigerator. The detector configuration consists of a multi-layer KID stack arranged above and below the quantum device, enabling time-coincident identification of muon-induced events within the same cryogenic environment. The integrated setup has been successfully commissioned, enabling simultaneous operation of the qubit chip and the muon tagging system. A first measurement campaign has been carried out, and preliminary data show time-correlated events between the muon tagging detectors and the qubit readout. A quantitative analysis of radiation-induced effects on qubit performance is currently ongoing. This work represents a step toward the implementation of event-level radiation tagging as a tool for characterizing and potentially mitigating correlated errors in superconducting quantum processors, while establishing a modular platform for future studies at the interface between particle physics and quantum information science.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗

Developing socially and economically generative, resilient PV-energy systems for low- and moderate-income communities: Applications for Puerto Rico (Final Technical Report)

The nexus of energy and poverty is one of the most significant long-term challenges facing the energy and electricity sectors, with negative feedback loops between energy-related costs, risks, and insecurities, on the one hand, and diverse other social and economic insecurities, on the other, helping to undermine health, wellbeing, and resilience in low- and moderate-income communities around the US and the world (Biswas et al. 2022). The transition of energy systems to clean energy alternatives offers a potential opportunity to redesign future energy arrangements in ways that, instead, create beneficial social value for communities, reverses the energy-poverty nexus, and enhances community wellbeing (Biswas et al. 2020; Miller et al. 2018). The promise of clean energy transitions to address the energy-poverty nexus is especially significant when designed using principles of just energy transitions. To leverage just clean energy transitions to accomplish a reversal of the energy-poverty nexus requires improvement in three capabilities: (1) Understanding and mapping the community-scale dynamics and variability of the energy-poverty nexus, which vary considerably from community to community; (2) Evaluating the technical, social, and economic potential for different clean energy system designs to deliver social value to specific communities; and (3) Working collaboratively with communities to imagine and design clean energy systems solutions that meet their needs, fit their capabilities and contexts, and deliver multiple forms of community-desired social value/benefits that help reverse key facets of the energy-poverty nexus. This project developed a portfolio of novel tools, methodological approaches, and collaborative partnerships with four communities in Puerto Rico that further the objective of building these three capabilities.

14 SOLAR ENERGY↗

Bringing Automated Fault Detection and Diagnostics Tools for HVAC&R Into the Mainstream

Heating, ventilation, and air-conditioning (HVAC) systems consume over 5 quads of energy annually, representing 30% of energy consumption in the U.S. commercial buildings. Additionally, commercial refrigeration (R) systems add about 1 quad to commercial buildings energy consumption. Most HVAC systems operate with one or more faults that result in increased energy consumption. Fault detection and diagnostics (FDD) tools have been developed to address this national issue, and many tools are commercially available. FDD tools have the potential to save considerable energy for an existing commercial rooftop unit (RTU) and refrigeration systems. These devices can be used for both retro commissioning and, when faults are addressed, continuous commissioning. However, there appears to be multiple market barriers for this technology. Although there are efforts to develop FDD tool standards, currently there are no standards and methods to define functions, capabilities, accuracy, and reliability of FDD tools in the field. Moreover, most of the commercial FDD tools have not been verified in the field independently. This paper presents a comprehensive approach for bringing HVAC FDD tools into the mainstream. The approach involves demonstrating ten commercially available FDD tools installed at ten different sites, independent testing and evaluation of the FDD tools, communication with various stakeholders, identifying and assessing market barriers, creating a process evaluation methodology, and assisting utility companies in developing incentive programs. Furthermore, the preliminary baseline results from the case study demonstrate how the use of an independent monitoring system (IMS) can be used for ground-truth in evaluating FDD tools in the field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Efficient sampling of free energy landscapes with functions in Sobolev spaces

Molecular simulations of biological and physical phenomena generally involve sampling complicated, rough energy landscapes characterized by multiple local minima. In this work, we introduce a new family of methods for advanced sampling that draw inspiration from functional representations used in machine learning and approximation theory. As shown here, such representations are particularly well suited for learning free energies using artificial neural networks. As a system evolves through phase space, the proposed methods gradually build a model for the free energy as a function of one or more collective variables, from both the frequency of visits to distinct states and generalized force estimates corresponding to such states. Implementation of the methods is relatively simple and, more importantly, for the representative examples considered in this work, they provide computational efficiency gains of up to several orders of magnitude over other widely used simulation techniques.

Approximation theory↗

Mitigation of birefringence in cavity-based quantum networks using frequency-encoded photons

Atom-cavity systems offer unique advantages for building large-scale distributed quantum computers by providing strong atom-photon coupling while allowing for high-fidelity local operations of atomic qubits. However, in prevalent schemes where the photonic state is encoded in polarization, cavity birefringence introduces an energy splitting of the cavity eigenmodes and alters the polarization states, thus limiting the fidelity of remote entanglement generation. To address this challenge, we propose a scheme that encodes the photonic qubit in the frequency degree-of-freedom. The scheme relies on resonant coupling of multiple transverse cavity modes to different atomic transitions that are well-separated in frequency. We numerically investigate the temporal properties of the photonic wavepacket, two-photon interference visibility, and atom-atom entanglement fidelity under various cavity polarization-mode splittings and find that our scheme is less affected by cavity birefringence. Finally, we propose practical implementations in two trapped ion systems, using the fine structure splitting in the metastable D state of 40 Ca + , and the hyperfine splitting in the ground state of 225 Ra + . Furthermore, our study presents an alternative approach for cavity-based quantum networks that is less sensitive to birefringent effects, and is applicable to a variety of atomic and solid-state emitter-cavity interfaces.

Cavity quantum electrodynamics↗

Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling under uncertainty, and its application to accelerating the discovery of new materials

In this report we summarize the work conducted by PI Perdikaris and his group under this Early Career project DE–SC0019116 during the period of 09/01/2018 – 08/31/2023. The central aim of the work was to introduce a new paradigm for scientific data analysis that can seamlessly synthesize rigorous mathematical modeling with data of variable fidelity (e.g., measurements at multiple scales/resolutions or predictions of variable fidelity models) and multiple modalities (e.g., images, time–series, or scattered measurements). The setting we are interested in involves complex systems that are partially observed and whose dynamical behavior could be hard to model or totally unknown. The inherent uncertainty associated with this setting necessitates a departure from the classical deterministic realm of modeling and scientific computation, and, consequently, our main building blocks can no longer be crisp deterministic numbers and governing laws, but instead we must operate with probabilistic models.

97 MATHEMATICS AND COMPUTING↗