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At least 523 records · Page 29

Towards more accurate sound field verification using directional acoustic filtering

Attributing omnidirectional sound levels to a specific source in the ocean can be challenging when there are multiple competing sources of sound such as boats, or biological activity. Here, we present a method to directionally filter acoustic measurements based on vector measurements of acoustic pressure and particle velocity. The directional discrimination is applied to estimate sound energy from two marine energy sources: sound generated during the decommissioning of an oil platform and those from an operating tidal energy converter. The application of a directional mask leads to distinctly different spectra and some differences in energy, relative to the unmasked scenarios.

Barosin, Emily (ORCID:0009000765495939)↗

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗

Fluidized-Bed Gasification of Coal-Biomass-Plastics for Hydrogen Production

Coal is one of the most abundant fossil energy resources in the United States and in the world. The recoverable reserves in the United States are estimated to be about 252 billion tons – more than 350 years of supply at current rates of usage. However, the share of coal in total primary energy consumption in the US has been declining over the years. The decline of coal is mainly attributed to cheap natural gas and precipitous declines in the cost of electricity production from renewable technologies such as wind and solar. Coal can potentially be used if it is coupled with carbon-neutral feedstock such as biomass-agricultural residues, forest biomass, and forest residues. Co-gasification of coal and biomass can become a negative carbon emission technology if the carbon dioxide (CO 2 ) is captured and sequestered. Although the biomass gasification process has a lot of similarities to coal gasification, the large-scale adaptation of power production sourced from biomass has not come to fruition. The main reason is that the power production from biomass is still expensive when compared with natural gas or coal power technologies. To address the feedstock cost, one approach is to use low-cost feedstocks, such as municipal solid wastes (MSW) or plastics, for gasification. Gasification involves the partial oxidation of coal and/or biomass feedstocks to produce a combustible fuel called synthesis gas (syngas) which is composed of carbon monoxide (CO), hydrogen (H 2 ), CO 2 , methane (CH 4 ), nitrogen (N 2 ), water (H 2 O), and other compounds that might be considered as contaminants. Raw syngas from gasification must go through multiple steps to produce high-purity hydrogen. The specific steps depend upon the quality (gas composition, contaminants, and their concentration) and condition (pressure and temperature) of syngas. The long-term goal of the project was to utilize coal and plastics together with biomass to produce energy and fuels using a gasification platform while reducing greenhouse gas emissions. The main objective of this research was to examine gasification performance in a laboratory-scale fluidized-bed gasifier for hydrogen production. The specific objectives of the research were to: (i) study coal-plastic-biomass mixture flowability for consistent feeding in the gasifier; (ii) understand the gasification behavior of the mixture in steam and oxygen environments; (iii) perform thermal property characterization of ash and slag from the mixture feedstock and refractory-ash interface of the mixture under gasification conditions; and (iv) develop process models to determine the technology needed for syngas cleanup and contaminants. The study found that there was no apparent segregation when biomass, coal, and waste plastics were mixed together during feeding. Although there were differences in hydrogen production when individual feedstock were fed, the hydrogen concentration remained almost constant with various blends. Therefore, blending waste plastics with biomass and coal, which are all abundant, is a better approach for energy production. Results of the techno-economic analysis suggested that integration of advanced gasification (GTI’s R-GAS™) and syngas cleanup and conditioning technologies (RTI’s WDP and AFWGS) for clean hydrogen production resulted in substantial benefits, including significant capital cost and operating cost reductions. Advanced technologies resulted in 16% reduction in the hydrogen production cost (COH) from 2.94 $\$$/kg to 2.47 $\$$/g, with further scope for optimization and cost reduction. These advanced technologies also result in lower emissions, and improved energy efficiency.

01 COAL, LIGNITE, AND PEAT↗

Deterministic High-Fidelity Neutronics Simulation of Pebble Bed Reactors Using Pebble Tracking Transport

The pebble tracking transport (PTT) algorithm offers a high-fidelity deterministic approach for neutron transport for pebble bed reactors (PBRs). This approach requires the mesh for the active-core region to consist exclusively of tetrahedral elements, where each node in the pebble-packing region represents a pebble centroid. This paper investigates the application of PTT for full-scale PBRs, considering both the isothermal and the temperature-dependent core conditions. Macroscopic cross sections are generated using Serpent 2 full-core eigenvalue simulations where pebbles are grouped into disjoint subsets using machine learning. To minimize the need for individual cross-section sets for each pebble in the core, K-means clustering is used to group pebbles by temperature and neutronic environment parameters. Here, we compare the multiplication factor and power rate distributions between PTT simulations using the Griffin reactor physics software and reference solutions from Serpent 2. Our analysis shows that a full-core, high-fidelity PTT calculation produces accurate results with minimal local (pebblewise) errors. Additionally, timing results indicate that PTT simulations converge rapidly on modern supercomputing platforms.

Griffin↗

Measuring dynamics of differentially rotating, unmagnetized, free-boundary plasma produced by soft x-ray irradiation

We present results from a new experiment, fielded on the MAGPIE pulsed power generator, producing a rotating, boundary-free plasma with no pre-imposed magnetic field. Angular momentum is introduced to the rotating system by the oblique collision of multiple plasma flows, which are driven by x-ray ablation of solid targets using the soft x-rays emitted from the implosion of wire array z-pinches. This produces a hydrodynamically stable plasma which undergoes ~2-3 rotations over the duration of the experiment, significantly more than previous pulsed-power platforms. Estimating the angular frequency from the electron density profile in the inner part of the rotating plasma shows that it has a quasi-Keplerian rotation profile. The system also allows for the addition of a controllable magnetic field. This, combined with the sufficiently large Reynolds (~10 5 ) and magnetic Reynolds (~10) numbers, will enable investigation of the effect of magnetic field on the structure and stability of the rotating plasma.

Physics - Plasma physics↗

Exploring the physics of cesium lead halide perovskite quantum dots via Bayesian inference of the photoluminescence spectra in automated experiment

The unique optoelectronic properties of metal halide perovskite quantum dots (QDs) make them promising candidates for applications in light-emitting diodes (LEDs), scintillators, and other photonic devices. The automated micropipetting synthesis platform equipped with an optical reader enables the opportunity for high throughput synthesis and photoluminescent (PL) characterization of metal halide perovskite QDs for the first time. Here, we explore the compositional dependence of the PL behavior and stability of the combinatorial library of cesium lead halide (CsPbX 3 ) perovskites QDs via the automated platform. To study the stability of synthesized QDs in the binary and ternary configurations, we study the time-dependent PL properties using previously developed machine learning analysis. Additionally, to systematically explore the PL behavior in the ternary CsPbX 3 QDs system, we introduce the Bayesian inference framework that allows the probabilistic fit of multiple models to the PL data and establishes both optimal model and model parameter robustly. Furthermore, these behaviors can be used as a control parameter for the navigation of the multidimensional compositional spaces in automated synthesis. Furthermore, this analysis shows the nonuniformity of the PL peak behavior in the ternary CsPbX 3 QDs system. Further, the analysis confirms narrow size distribution and good quality of CsPbBr 3 QDs alloyed with low concentrations of iodide and chloride. We note that Bayesian Inference fit parameters can be further used as a control signal for navigation of the chemical spaces in automated synthesis.

36 MATERIALS SCIENCE↗

D and D Research on KM-IT Platform - 20494

The Knowledge Management Information Tool (KM-IT) is a web-based system developed to maintain and preserve the Department of Energy's (DoE's) knowledge base. The system was developed by Florida International University's Applied Research Center (FIU-ARC) with the support of the D and D community including the DOE Office of Environmental Management, and with the collaboration and support of the DoE's Energy Facility Contractors Group (EFCOG) and the former ALARA Centers at Hanford and Savannah. The KM-IT system is a community driven system tailored to serve the technical issues faced by the workforce across the DOE Complex. This KM-IT web-based interactive system is operational and available for use at www.dndkm.org and is currently comprised of the following modules: Web Crawler, Hotline, Technology, Hanford's ALARA Center Reports, Specialist Directory, Lessons Learned, Best Practices, Video/Picture Library, Vendors and Industry News. The Web Crawler dynamically searches through the KM-IT repository as well as the web and displays search results based on the search criteria. The Hotline allows registered users to post questions/problems related to D and D and to receive solutions from a subject-matter specialist. The Technology module serves as repository of D and D technologies and contains technology/ demonstration fact sheets and vendor information. D and D community members can add Lessons Learned, Best Practices, and Pictures/Videos to the D and D repository, after a formal approval process. The Vendor module provides a directory of commercial vendors who provide D and D related technologies, supplies, and services. KM-IT makes an excellent use of the knowledge that exists within the D and D community by allowing D and D project managers around the DOE complex to collaborate by sharing innovative ideas, past experiences, and practices and by maintaining a directory of subject matter specialists. FIU has developed the dedicated module on KM-IT platform to publish D and D research being performed at FIU. This module highlights current EM research efforts and activities in support of D and D being performed at FIU/SRNL associated with fixatives and intumescent products. FIU will expand this module to include the recent and current D and D research being performed across multiple DOE EM sites, national labs and universities. FIU will collaborate with SRNL, INL, ANL and other universities to explore and publish D and D research activities on KM-IT. As a result, the user community will have a centralized location to review new D and D related research across the DOE EM complex. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Adorym: a multi-platform generic X-ray image reconstruction framework based on automatic differentiation

We describe and demonstrate an optimization-based X-ray image reconstruction framework called Adorym. Our framework provides a generic forward model, allowing one code framework to be used for a wide range of imaging methods ranging from near-field holography to fly-scan ptychographic tomography. By using automatic differentiation for optimization, Adorym has the flexibility to refine experimental parameters including probe positions, multiple hologram alignment, and object tilts. It is written with strong support for parallel processing, allowing large datasets to be processed on high-performance computing systems. We demonstrate its use on several experimental datasets to show improved image quality through parameter refinement.

36 MATERIALS SCIENCE↗

Rethinking radiation effects in materials science using the plasma-focused ion beam

This work demonstrates the viability of using a plasma-focused ion beam (PFIB) as a new platform to carry out radiation effects studies in solids. While materials subjected to irradiation in either nuclear reactors or energetic particle accelerators experience limitations with respect to inaccuracies in both flux measurements and lack of precise control of irradiation areas, we demonstrate a new irradiation technique that allows the exposure of a single specimen in multiple areas, at multiple doses, and in site-specific dependencies - all with flux variations on the order of only 1%. This versatile technique also allows materials to be exposed to significantly higher irradiation dose rates than conventional accelerators. To validate the new methodology, we selected the classical example of ion-beam-induced amorphization of pure single-crystal Si. By pioneering the use of the PFIB for radiation effects studies in materials science, we were able to exploit, in both micro- and nanometer-sized detail, the differences in electron image contrast arising from crystalline versus amorphous solid-state phases in classical semiconductors subjected to irradiation, thus providing new insights on amorphization mechanisms. This methodology opens new research frontiers at the fringe of materials science with promising applications beyond the scope of materials at extremes such as in nanopatterning, nanodevices and nanoarchitectonics.

36 MATERIALS SCIENCE↗

Dynamics of phage-host interactions in Bacteroides fragilis resolved by single-cell transcriptomics

The interactions between lytic phages and their hosts are typically studied in bulk culture, which obscures cell-cell differences in infection susceptibility or expression of protective factors. Here, we use bacterial single-cell RNA sequencing to profile the transcriptomes of ~50,000 cells from cultures of a human pathobiont, Bacteroides fragilis, infected with a lytic bacteriophage. From a single sampling, we quantified the asynchronous progression of phage infection in individual bacterial cells and reconstructed the infection timeline, characterizing both host and phage transcriptomic changes as infection unfolded. Further, we discovered phenotypic subpopulations of bacteria that remained uninfected. Each cell’s vulnerability to phage infection was influenced by expression of multiple genetic loci, most prominently phase-variable capsular polysaccharide (CPS) biosynthesis pathways and an operon predicted to encode fimbrial genes. These findings uncovered genome-wide phase variation and stochasticity that enable bacterial survival and re-growth without acquiring additional mutations. Overall, we establish bacterial single-cell RNA sequencing as a powerful platform for investigating the dynamics of host-phage interactions and revealing the roles of phase variation and stochasticity in bacterial defenses.

Bacteria↗

Multi-domain automated patterning of DNA-functionalized hydrogels

DNA-functionalized hydrogels are capable of sensing oligonucleotides, proteins, and small molecules, and specific DNA sequences sensed in the hydrogels’ environment can induce changes in these hydrogels’ shape and fluorescence. Fabricating DNA-functionalized hydrogel architectures with multiple domains could make it possible to sense multiple molecules and undergo more complicated macroscopic changes, such as changing fluorescence or changing the shapes of regions of the hydrogel architecture. However, automatically fabricating multi-domain DNA-functionalized hydrogel architectures, capable of enabling the construction of hydrogel architectures with tens to hundreds of different domains, presents a significant challenge. We describe a platform for fabricating multi-domain DNA-functionalized hydrogels automatically at the micron scale, where reaction and diffusion processes can be coupled to program material behavior. Using this platform, the hydrogels’ material properties, such as shape and fluorescence, can be programmed, and the fabricated hydrogels can sense their environment. DNA-functionalized hydrogel architectures with domain sizes as small as 10 microns and with up to 4 different types of domains can be automatically fabricated using ink volumes as low as 50 μL. We also demonstrate that hydrogels fabricated using this platform exhibit responses similar to those of DNA-functionalized hydrogels fabricated using other methods by demonstrating that DNA sequences can hybridize within them and that they can undergo DNA sequence-induced shape change.

Rubanov, Moshe (ORCID:0000000180507407)↗

Optimized Carbon Fiber Intermediate Development to Enable High-Volume Manufacturing of Lightweight Automotive Composites

The ongoing pursuit of improved fuel economy and reduced greenhouse gas emissions has resulted in sustained interest for lightweight materials technologies. In this context, carbon fiber composites have captured the imagination of automotive engineers due to the potential to achieve substantial mass reduction when compared to traditional steel construction. That stated, the use of carbon fiber composites in automotive has been limited for the most part to premium supercars and other derivative platforms. In these cases, manufacturing costs are less of an obstacle to implementation, and the performance benefits of carbon fiber have enabled production of structures offering more than 50% weight savings. In practice, translating these low-volume demonstrations onto high-volume vehicle platforms has remained challenging. This can be attributed to several factors, with the absence of suitable high throughput production methodologies being a key impediment. To date, structural, crash critical components have relied upon manufacturing techniques born out of the aerospace industry. This has created a disconnect between automotive production systems that are accustomed to manufacturing multiple parts per minute and the aerospace technologies that have cycle times in the order of hours. Consequently, the focus of this project is the development of manufacturing process technology for carbon fiber composites that can support a mainstream vehicle program at an assumed throughput of 100,000 vehicles per year. In practice, this translates to a part-to-part cycle time of less than 3 minutes. Project participation included contributions from a broad range of academic, industrial and national lab partners. The primary scope of work, being the development of new carbon fiber epoxy compounds that are stable at room temperature and suited to high throughput automated processing. For project management, the work streams were divided into six key areas, with the lead organization in parentheses. • Carbon fiber/epoxy materials formulation development and scale up (Dow) • Simulation of discontinuous near isotropic meso-structure intermediates (Purdue) • Simulation of mechanical performance of compression molded components (Purdue) • Meso-Scale morphological analysis and correlation with structural performance (UTK) • Paint and adhesion durability analysis (MSU) • Demonstrator part design, prototype production, and validation testing (Ford). The primary goal at the commencement of the project was development of a chopped carbon fiber sheet molding compound (SMC) that offered a three times improvement in tensile modulus over a comparable glass-based SMC. In addition to meeting mechanical performance targets, the resin kinetics were modified to achieve a processing cycle time of less than 3 minutes. Other critical-to-quality (CTQ) specifications were also stipulated to account for a broad range of materials and processing characteristics. To achieve the above, staff scientists at Dow Chemical created an extensive series of new epoxy blends for testing and validation. Throughout this development, a key challenge was attaining material performance goals without impacting processing behavior and paintability of finished components. The latter required a new internal mold release system being developed by Dow that was designed to complement the kinetics of the rapid cure epoxy. As a complement to work studies at the industrial partners, the teams from academia executed a series of analytical and experimental studies to investigate potential factors influencing CF-SMC performance. Unit cell models were developed to capture the meso-scale representations of the fiber matrix architecture. Results of this analysis and subsequent morphological investigations led to the design of a novel composite derivative comprising carbon fiber platelets embedded in an epoxy matrix; the platelet size and aspect ratio playing significant role in final composite properties. This approach was a departure from previous research in CF-SMC development whereby bulk filamentization or disassembly of the carbon fiber rovings had been considered the most effective means of achieving both fiber wet through and wet-out. As the course of the academia studies progressed, the aspect ratio of the fiber constituents was further optimized before finalizing material attributes and processing conditions. For the purposes of technology validation, the Ford team led a work stream devoted to the design, fabrication and testing of demonstration components. The carbon fiber SMC material has the potential to displace numerous stampings and castings on an automotive structure but ultimately vehicle closure applications were selected to showcase the abilities of the CF-SMC to achieve both mass reduction and business case for large complex structures. Using target properties established by the Dow staff scientists, the complete closure system for a full-size sedan decklid and a mid-size wagon liftgate were engineered. Prototypes for both applications were fabricated using production representative processing methods to allow for physical testing and performance validation of the CF-SMC structures. Following completion of a testing program that concluded with a FMVSS301 55 mph offset rear crash, the CF-SMC formulation was declared by the Ford team to have met all engineering requirements. To summarize, the joint development activities during this project led to significant technical breakthroughs and achievement of all milestones. The result was the development of a novel, tack-free carbon fiber molding compound that is suited to automated processing. This combined room temperature stability, fast cure kinetics, and internal mold release system facilitates cycle times that are conducive to high-volume production. The VORAFUSE M6400 successfully passed technology validation at Ford and is now eligible for consideration on future production commercial vehicle programs.

36 MATERIALS SCIENCE↗

Evaluating the performance of a high resolution SLIM IM module integrated with an Agilent 6560 IM-QTOF MS - CRADA 413 (Final Report)

Developing new technologies that enhance our abilities to identify molecular signatures is important for the health of the public, the environment, and national security. Deploying these novel technologies requires multiple stages of validation and evaluation. This project focused on evaluating a technology developed at PNNL named Structures for Lossless Ion Manipulations (SLIM) in the context of a commercially available ion mobility mass spectrometer instrument from Agilent Technologies. There is a benefit to integrating the recently developed SLIM module into a real-world instrument platform. Data from the combined instrument will provide new standards for characterizing samples using ion mobility. These standards, related to both the drift time of ions and their resulting collisional cross sections (CCS) will be of value in characterizing samples from both humans and environmental samples, such as soil microbiomes. Because no previous instrument has been designed and implemented to simultaneously analyze the same sample in both constant and oscillating drift fields, the project will provide a new research capability that will support research in a wide variety of applications. The evaluation approach included measuring the resolving power, mass range, sensitivity, and accuracy of two SLIM variations (constant and oscillating fields). Although SLIM performed similarly to the commercial instrument in terms of sensitivity, mass range, and accuracy the resolving power of SLIM far exceeded that of the commercially-available instrument. This validation will provide critically useful data to our commercial partners which they can use to reach informed decisions on the advantages of the SLIM technology such as the outstanding performance and the low cost of manufacturing.

42 ENGINEERING↗

Requirements for Cataloging Hanford Geophysical Datasets

Environmental management activities at the Hanford Site produce extensive data about site conditions, contaminants, cleanup, and more. Managing and archiving that data requires a high degree of collaboration among site contractors and a high level of awareness by project managers and staff. Part of that effort is developing a Hanford Environmental Information and Data Index (HEIDI) to organize the data and maximize its value by making it findable and available for reuse. The objective is to catalog the disparate data sets collected to address the evolving needs of planning, executing, and documenting cleanup over several decades up to the present day, including links to active data sources when available. A properly implemented data catalog makes finding environmental datasets related to an area or theme a routine, reliable process, without requiring the searcher to have special knowledge that a data set exists and where it may be stored. In this project, a working group, including the U.S. Department of Energy, the Hanford Site contractors, and Pacific Northwest National Laboratory staff, identified needs and requirements for handling complex site data. Geophysical data was chosen as a test case because it can be large and complex and often involves multiple processing steps to extract the information incorporated into deliverables. The ability to document those steps was one of the requirements identified for the catalog. In addition to developing requirements, other activities included selecting a metadata schema and initial testing with the objective of determining whether the workflow and capabilities of selected data catalog software platforms were sufficient to implement and impose the identified requirements. This initial testing involved running the default catalog instance using the software platform of interest and altering the configuration to achieve each requirement, if possible. Where configuration alone was insufficient, the possibility of modifying the software by changing the code was examined, but not implemented. A follow-on task is planned to reprogram the code as necessary to implement requirements in a prototype catalog.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Scanning Mobility Particle Sizer (SMPS)-Aerodynamic Particle Sizer (APS) Merged Size Distribution (mergedsmpsaps) Value-Added Product Report

Aerosol particles influence the Earth’s radiation balance directly by absorbing and scattering light and indirectly by influencing cloud formation, properties, and lifetimes. Measurements of aerosol particle optical properties, mass loading, size distributions, microphysical properties, cloud formation properties, and chemical composition are important for understanding the aerosol life cycle and for validating earth system models that predict these quantities. The Atmospheric Radiation Measurement (ARM) user facility’s Aerosol Observing System (AOS) is a highly instrumented platform designed to house instruments that measure many of these aerosol properties in situ. Currently, ARM operates at least four different instruments that measure a portion of the ambient aerosol size distribution. Most users are interested in the entire size distribution or a portion of the size distribution that extends across the measurement range of multiple instruments. However, merging these distributions is not trivial as the instruments employ different measurement principals and, in most cases, report data as a function of different representations of the aerosol diameter.

54 ENVIRONMENTAL SCIENCES↗

Microbiome engineering for sustainable agriculture: using synthetic biology to enhance nitrogen metabolism in plant-associated microbes

Plants benefit from symbiotic relationships with their microbiomes. Modifying these microbiomes to further promote plant growth and improve stress tolerance in crops is a promising strategy. However, such efforts have had limited success, perhaps because the original microbiomes quickly re-establish. Since the complex biological networks involved are little understood, progress through conventional means is time-consuming. Synthetic biology, with its practical successes in multiple industries, could speed up this research considerably. Some fascinating candidates for production by synthetic microbiomes are organic nitrogen metabolites and related pyridoxal-5'-phosphate-dependent enzymes, which have pivotal roles in microbe-microbe and plant-microbe interactions. This review summarizes recent studies of these metabolites and enzymes and discusses prospective synthetic biology platforms for sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗

Efficiently Measuring 𝑑-Wave Pairing and Beyond in Quantum Gas Microscopes

Understanding the mechanism of high-temperature superconductivity is among the most important problems in physics, one for which quantum simulation can provide new insights. However, it remains challenging to characterize superconductivity in existing cold-atom quantum simulation platforms. Here, in this work, we introduce a protocol for measuring a broad class of observables in fermionic quantum gas microscopes, including long-range superconducting pairing correlations (after a repulsive-to-attractive mapping). The protocol only requires global controls followed by site-resolved particle number measurements—capabilities that have been already demonstrated in multiple experiments—and is designed by analyzing the Hilbert space of fermions on two sites. The protocol is sample-efficient and we further optimize our pulses for robustness to experimental imperfections such as lattice inhomogeneity. Our Letter introduces a general tool for manipulating quantum states on optical lattices, enhancing their ability to tackle problems such as high-temperature superconductivity.

Hubbard model↗

Advanced Health Information Technology Analytic Framework and Application to Hazard Detection

Health Information Technology (HIT) aims to improve healthcare outcomes by organizing and analyzing various health-related data. With data accumulating at a staggering rate, the importance of real-time analytics has been increasing dramatically, shifting the focus of informatics from batch processing to streaming analytics. HIT is also facing unprecedented challenges in adapting to this new requirement and leveraging advanced IT technologies. This paper introduces a HIT data and compute platform that supports multi-granularity real-time analytics from heterogeneous data sources. The paper first identifies functional requirements and proposes a framework that satisfies the requirements using state-of-the-art big data technologies including Apache Kafka, Spark Structured Streaming Engine, and Delta Lake. To demonstrate its capability to support data analytics in multiple time granularities analytics, a statistical process control-based hazard detection algorithm has been implemented on top of the framework to detect unexpected hazards from order cancellation data of the Department of US Veterans Affairs (VA) in near real-time.

Kumar, Mohit↗