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At least 469 records · Page 26

Carbon dioxide (CO2) flux, amplicon sequencing and liquid chromatography–mass spectrometry (LC-MS) data for pyrogenic organic matter (PYOM) amended soil incubations in lab, Madison, WI, 2021-22

This dataset comprises soil-pyrogenic organic matter (PyOM) incubation experiments conducted in a laboratory setting. The focus was on measuring carbon dioxide (CO2) flux emitted in the headspace of incubation jars over a one-month period. The aim was to estimate carbon mineralization from two different carbon fractions in PyOM, as well as carbon mineralization from soil organic carbon (SOC). Bacterial and fungal community profiles were tracked at various time points during the incubation to observe changes in the overall community and specific responders to PyOM. LC-MS analysis of soil samples was also performed to monitor changes in the soil's chemical composition.The provided dataset includes processed CO2 flux measurements obtained from the Picarro-multiplexer measurement setup for each sample incubation jar. This data is available in the "CO2Flux.csv" file. Additionally, the dataset includes CO2 flux data partitioned to estimate mean carbon mineralization from the two PyOM carbon fractions, bulk PyOM, and SOC. The cumulative carbon mineralization data is provided in "cml_respired.csv," while the rate of carbon mineralization data is in "rate_respired.csv." The file "cml_respired_lastcyc.csv" contains cumulative carbon mineralization data for the PyOM carbon fractions, bulk PyOM, and SOC throughout the entire incubation period.For the LC-MS analysis, the raw data can be found in the "20220721_NZ_PeakHeights_FinalAnalysis.csv" file, while sample metadata is provided in "20220721_NZpilot_Metadata.csv". Processed LC-MS data is available in the file "20220721_NZ_FINAL_msdat_sub3.csv". Lastly, the dataset includes the relative abundance data for bacterial genera that exhibited a significant positive response to the addition of PyOM produced at 350 degrees Celsius, which can be found in "resp_genera_350.csv".

54 ENVIRONMENTAL SCIENCES↗

Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics (Blodgett, CA)

This dataset contains data on daily soil temperature, moisture and flux, and soil carbon stock and root biomass across a soil profile down to 100 cm depth at Blodgett Forest Research Station, CA, USA. These data were generated to determine if modeling of an experimental soil warming of 4C showed increased soil CO2 emissions and changes in bulk soil carbon stocks with depth consistent with field observations, as part of the study: Riley et al. (2025) Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics in Journal of Advances in Modeling Earth Systems. This research was performed within the framework of the TES Belowground Biogeochemistry SFA project, in particular association with a 1 m-deep experimental soil heating experiment at the University of California Blodgett Forest Research Station, California (120 ° 39′40′′W; 38 ° 54′43′′N). Continuous data were collected at the plot level, and bulk soil carbon and root biomass were sampled once a year from each plot from 0-100 cm, in 10 cm intervals. Measurements relevant to the current study include soil temperature and soil volumetric water content measured continuously at multiple depths in the top meter; fine root biomass and SOC stocks measured from annual soil cores. Soil flux was continuously monitored using a LI-8100 Automated CO2 Flux System in conjunction with the LI-8150 Multiplexer (Licor, Nebraska, USA). Soil flux was determined using SoilFluxPro software, with flux values showing an R² fit of less than 0.9 being excluded from the analysis. Data were collected from each paired plot (1-3): one control (C) and one heated (H).

54 ENVIRONMENTAL SCIENCES↗

TRANSENSOR: Transformer Real-time Assessment INtelligent System with Embedded Network of Sensors and Optical Readout. Final Report

Utilities across the world are wrestling with evolving market dynamics, population growth and climate change. Distributed Energy Resources (DERs) such as solar photovoltaics, distributed generators and energy storage systems are becoming important parts of the U.S. energy mix. These factors are driving an increasing need for low-cost grid asset monitoring. Aside from being costly, traditional utility monitoring systems are not sufficiently robust and do not provide real-time visibility into the condition of grid assets such as transformers. Lack of accurate real-time measurements on performance has resulted in the use of lagging indicators, such as oil sample analysis. To address this need, an innovative embedded optical sensing technology, Transformer Real-time Assessment Intelligent System (TRANSENSOR) was developed, validated and demonstrated in this project. To date, TRANSENSOR has focused on transformers but is extendable to other grid assets. In addition to the technology being embedded into new transformers during manufacturing, a retrofit configuration that can be installed on existing transformers in the field was also developed. It is anticipated that the ability to retrofit existing transformers will help accelerate adoption of the underlying TRANSENSOR technology. Phase 1 of the project focused on laboratory development and qualification of the technology. Following iterations and exploration of relevant optical sensing modalities and multiplexed configurations of interest for the transformer environment, an effective candidate configuration was agreed upon, down-selected and custom-designed for embedding into General Electric (GE) network transformers. Two new GE 500 kilovolt ampere (kVA), 27 kilovolt (kV) distribution network transformers were built with embedded fiber-optic (FO) sensors and successfully qualified per industry standards at GE’s Shreveport, Louisiana facility during Phase 1 of the project. Following the successful completion of Phase 1, the team proceeded to Phase 2, which focused on a field demonstration of the technology. Over Phase 2, the first new GE transformer built with embedded fiber-optic sensors was installed in an above-ground cage and connected to the grid at Con Edison’s Astoria facility. A second transformer equipped with TRANSENSOR was installed in an underground vault. Additionally, an older (1982 year model) GE transformer in an above-ground cage was retrofitted with fiber- optic sensors and reconnected to the grid at ConEd’s facility. Analysis of data acquired from the sensors showed interesting correlations with transformer loading. Additionally, key events such as transformer low-voltage network connection, primary-side energizing, and a pressure loss event from an oil sampling were detected by the TRANSENSOR system. Online data processing/feature extraction algorithms for the second transformer in the underground vault detected key features and event alerts that were transmitted through a wireless 4G connection. The remote deployment concept showed promising results with data collection running for a total of 8 months across the three (3) GE transformers instrumented for the Phase 2 field demonstration. This sets the stage well for further development and commercialization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of FRET clusters for CBRN Detection

Advanced sensor capabilities for the simultaneous on-site detection of specific chemical, biological, and radiological/nuclear (CBRN) threats is important to significantly limit the risk of exposure to personnel and allow the rapid collection of essential scientific data and critical evidence. Commercially available sensor capabilities are generally complex, and/or require highly specific and ultra-sensitive methods that are often power demanding or require offsite post-analysis for positive detection, leaving personnel vulnerable. The goal of this project is to develop a portable sensor capable of simultaneously detecting CBRN signatures using a multiplexed Förster Resonance Energy Transfer (FRET) based sensor. FRET sensors are tailorable, specific, and highly dependent on the donor-acceptor distance. In this project, nanoparticles were functionalized with aptamers that were designed for the detection of methylphosphonate, a sarin metabolite. FRET was measured between quantum dot donors and dye and metal nanoparticle acceptors using optical spectroscopy.

61 RADIATION PROTECTION AND DOSIMETRY↗

Multi-Functional Distributed Fiber Sensors for Pipeline Monitoring and Methane Detections. Final Report

As an abundant and cheap fossil energy source, natural gas has become a significant energy supply to support the United States’ economy. However, the large-scale extraction and utilization of natural gas also impose significant challenges on methane leakage. This problem is exacerbated by aging gas utility delivery systems, including interstate high-pressure pipelines, storage, and transmission facilities. This project aims to develop a cost-effective fiber optical sensing method that can perform multi-parameter real-time measurements of natural gas pipelines across long interrogation distances up to 100 km with 1-meter spatial resolution. This sensing tool can evaluate overall pipeline efficiency and reduce methane emissions for mid-stream methane infrastructures. To accomplish this objective, research and development efforts funded by this project have resulted in the following accomplishments: This project successfully has developed new functional sensory polymer materials using Metal-Organic Frameworks (MOFs) that can be coated on optical fiber through the reel-to-reel coating process. Functional polymer-coated optical fibers can perform sensitive methane detection through evanescence wave interaction and strain-based measurements to achieve 1% detection sensitivities. The new sensors fibers support both distributed measurements and multiplexed fiber sensors array for multi-point measurements. This project developed and optimized a new multi-core optical fiber that supports simultaneous and distributed measurements of strain and temperatures with 1-meter spatial resolutions across up to 100-km interrogation distance. This new fiber, combined with sensory polymercoated fiber, could perform both distributed temperature and methane detections. This project developed a new artificial intelligence big data algorithm approach that can effectively analyze high-resolution data harnessed by distributed fiber sensors to protect natural gas pipelines against external threats and detect internal defects induced by corrosion. Working with our industry partner, this project developed new optical fibers that support fiber sensor fabrications through polymer coating after the fibers are drawn. These new fibers eliminate the need for direct sensor fabrication when the fiber is fabricated on a fiber draw tower, which drastically expands fiber sensors' applicability. This research project has significantly advanced the distributed fiber sensing technology. It will dramatically increase the applicability and adaptability of distributed fiber sensors for a wide array of applications in energy, sustainability, and environmental science, including structural health monitoring of natural gas pipelines, oil infrastructures, hydrogen facilities, and environmental monitoring of carbon storage sites, water supply systems, and others.

03 NATURAL GAS↗

Ultra low background time projection alpha particle detector ( Phase II Final Scientific/Technical Report)

When alpha particles are emitted into a gas they create an ionization track of gas ions and electrons. In our commercial UltraLo instrument we apply a voltage between a planar sample and an anode, integrate the anode signal as it collects the electrons, and distinguish between alphas emitted from the sample and elsewhere (anode, sidewalls) by the duration and shape of the resultant signal. The major contributors limiting the instrument’s lower detection limit are cosmic rays that pass through the detector close to the sample and Rn decays that produce charge tracks the originate in the gas and end on the sample. In this work we proposed to identify and reject these events by converting the anode into a multi-pixel array and operating in time projection mode. Cosmic rays would be eliminated by generating charge on many pixels, while charge collection asymmetry would distinguish between sample events (Bragg curve up) and Rn events (Bragg curve down). We therefore proposed to modify an UltraLo by pixilating its anode, developing low noise, low power multiplexed electronics to track each pixel’s signal individually, and develop analysis software to make the required discriminations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Massive, Position-Resolving, High-Energy-Resolution Detector for Non-Accelerator Cosmic and Intensity Frontier Particle Physics

We proposed to take the first steps in the development of a detector that promises energy resolution of tens of eV FWHM combined with robust nuclear-recoil discrimination and high fidelity, mm-precision position reconstruction for applications in non-accelerator particle physics at the Cosmic and Intensity Frontiers. The detector would obtain these excellent resolutions by sensing athermal phonons produced by particle interactions in crystalline, dielectric targets using a sensitive, highly multiplexable superconducting phonon sensor, the kinetic inductance detector (KID). This detector would be applicable to: the search for low-mass particle dark matter candidates with masses below 5~GeV via direct detection of scattering of dark matter particles with terrestrial nuclei; detection of coherent elastic neutrino-nucleus scattering to test for new physics such as a non-standard value of the weak nuclear charge, non-standard neutrino interactions (perhaps driven by a neutrino magnetic moment), or the existence of sterile neutrinos; and, searches for neutrinoless double-beta decay. During the funding period, we demonstrated scaling up of the detector concept from a 22-mm by 22-mm by 1-mm, 1-g prototype with 0.9~keV FWHM energy resolution to a 75-mm diameter by 1-mm, 9-g prototype while improving the inferred energy resolution to 0.7~keV~FWHM. In the process, we solved many problems associated with scaling device fabrication to large wafers and vastly reduced the fraction of the surface occupied by inactive but energy-absorbing metal. We also demonstrated a new technique that substantially simplifies the process of characterizing a new detector. These results provide a good foundation for future work scaling up the design to 4-mm thickness substrates and improving the resolution to reach 0.035~keV~FWHM, yielding a detector with compelling potential for the above applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Integrated Pest Management (IPM) for Early Detection Algal Crop Protection. Final Report

During large-scale, outdoor algal biomass growth, production strain(s) are subject to attack by pathogens, predators, and non-productive competitors, compromising the biomass yield. The project team at UCSD developed and demonstrated the effectiveness of Volatile Organic Compound, VOC, analysis via mass spectrometry (MS) as an early detection system for the presence of production algal ponds infection. The MS detection can then trigger high-resolution melt analysis (HRMA) and enhanced quantitative PCR (qPCR) to identify predatory or pathogenic species precisely. This study gathered the foundational data informing how wholly automated systems monitor the health of production ponds. By detecting the presence of low molecular weight VOCs in the air space above ponds, the instrument was able to mimic “sniffing” the health of the algae pond. This early warning system will be free growers from time-consuming and costly regular surveillance of ponds with the current techniques, such as qPCR and flow-cam assays, which are slower, less sensitive, and not easily fully automated, resulting in increased production efficiency through the reduction of crop loss. This project demonstrated that Chemical Ionization Mass Spectrometry, CIMS, could serve as a real-time monitor of ponds health tracking up to 100 different VOCs simultaneously for continuous periods up to 60 days without interruption, signaling infection within an algal crop 24 to 36 hours prior to techniques such as qPCR and microscopy. While mass spectrometry is an expensive tool, this simple VOC sampling system proved not only to be sensitive and robust but could to multiplexed to monitor several ponds, lowering the overall cost serially. This technology demonstrated a reduction in biomass production cost by approximately 50% compared to growers not employing any detection methodology.

09 BIOMASS FUELS↗

The MegaMapper: A Stage-5 Spectroscopic Instrument Concept for the Study of Inflation and Dark Energy

In this white paper, we present the MegaMapper concept. The MegaMapper is a proposed ground-based experiment to measure Inflation parameters and Dark Energy from galaxy redshifts at $2 < z < 5$. In order to achieve path-breaking results with a mid-scale investment, the MegaMapper combines existing technologies for critical path elements and pushes innovative development in other design areas. To this aim, we envision a 6.5-m Magellan-like telescope, with a newly designed wide field, coupled with DESI spectrographs, and small-pitch robots to achieve multiplexing of at least 26,000. This will match the expected achievable target density in the redshift range of interest and provide a 10x capability over the existing state-of the art, without a 10x increase in project budget.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA). Final report

The goal of the Stahl lab is to use a combination of isotopic, genomic, and activity-based analyses in the field, of selected field isolates, and defined synthetic communities to identify sources and sinks of different nitrogen species in the field, focusing on the FRC at the ORNL. The most general research objective is to characterize variants in the pathway for denitrification among field isolates and synthetic microbial assemblies as a foundation for predicting the biotic and abiotic controls of nitrogen and carbon transformations in the field. Specifically, we have focused on characterizing environmental controls of nitrous oxide emissions, an important greenhouse gas and ozone depleting molecule. Studies have mapped the flux of nitrous oxide and controlling genetic elements within the FRC subsurface, indicating the importance of different enzyme variants in nitrous oxide production and consumption in controlling surface emissions. We have developed methods to quantify and catalog the isotopic signatures imparted on nitrous oxide by different nitrous oxide reductase variants in isolated organisms and model synthetic communities. We have developed methods to quantify and catalog the nitrous oxide affinity of field relevant isolates and their biomass yield when respiring nitrous oxide on different carbon substrates. We continue to expand the collection of field-relevant microbial isolates within ENIGMA by focused enrichment and isolation from field material. These objectives have been facilitated by the development of new technologies, including: 1) the development of a multiplexed automated optical density measurement system for quantifying growth kinetics of microorganisms dependent on gaseous substrates in monoculture or gas exchange in synthetic communities and 2) the development of a microcalorimetric analysis format to quantify the impact of environmental stress on microbial maintenance energy. Since field relevant processes are mediated by assemblies of organisms interacting with each other and their local environment, we have also collaborated with other ENIGMA investigators on the assembly and characterization of synthetic communities. These studies have evaluated the role of organisms lacking a complete pathway for denitrification in the control of field processes, measuring process rates of assemblies of organisms that individually lack the full denitrification pathway but mediate the complete denitrification when growing together. These efforts have so far resulted in the publication of 18 peer reviewed papers ranging from ecological and physiological drivers of pathway optimization to field-scale process characterization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of a Radiation-Tolerant Front End Digitizer

High-radiation and high-temperature environments represent notoriously detrimental conditions for electronics. Yet sensors and instrumentation are critically important for the safe operation of nuclear reactors and for the validity of the scientific experiments conducted within them. Traditionally, sensors in such extreme environments operate with few active components, resulting in small signals (mV–V, nA–µA range) that must be transmitted through long cable runs before digitization by sensitive data acquisition systems located in clean, less-harsh environments. Long cables are prone to picking up noise through electromagnetic interference and distortion caused by their parasitic impedances, resulting in signal degradation. The Front End Digitizer (FREND) system described and demonstrated herein seeks to address these issues by enabling the placement of a radiation-resistant analog front end within reactor containment, or other high-radiation environments. FREND will enable early signal pre-amplification, digitization, and optical encoding within the high-radiation field to transmit sensor signals over an optical fiber to the non-nuclear environment of an instrument room. Early signal pre-amplification and digitization maintain signal integrity, whereas optical transmission renders the system blind to induced electromagnetic noise over the long cable runs. This report describes the FREND initial prototype, which can multiplex and optically encode data from up to four sensor inputs, though, in principle, this can be extended to any number of sensor inputs. The end result is an extremely flexible, high-fidelity system.

42 ENGINEERING↗

Design and Fabrication of Quantum Information Processing Devices (Final Report)

The goal of this work is to develop a wideband Josephson Parametric Amplifier (JPA) by the combination of a coplanar impedance transformer and a lumped Josephson Parametric Amplifier. Josephson Parametric Amplifiers take advantage of the nonlinear inductance of Josephson junctions and the nearly lossless superconductor circuits to achieve wave mixing and amplification with only quantum-limited added noise, which makes it a key component in quantum measurements, such as single-shot qubit measurement. However, the current JPAs generally have a relatively high quality factor and small bandwidth (around 50MHz to 100MHz), which limits their ability in measuring signals from a broad spectrum. Therefore, the work planned to use a coplanar impedance transformer to enhance the coupling between JPA and the signals, resulting in a small quality factor and large bandwidth. By decreasing the quality factor of JPA to around 3, one can achieve around 20dB gain within a bandwidth of several hundred MHz. Moreover, the wideband feature allows this device to explore the frequency dependence of the coupling between the JPA and the signals. Because the impedance transformer is based on a coplanar transmission line and requires no modifications of the lumped JPA, it is relatively straightforward to embed it in the current fabrication, package, and testing process for lumped JPA. The impedance transformer can be fabricated by liftoff or etching process with the lumped JPA together, which adds no fabrication complexity. The only difference is the size, which is around 3~5 times larger than lumped JPA. This may make the number of available chips on a single wafer lower. As for the public benefits, the development of this wideband JPA will make it possible to use just a single JPA device for multi-frequency signals, for example, the readout signals of a superconducting qubit chip with multiplexed readout bus. This would greatly decrease the demand for JPAs in quantum measurements.

42 ENGINEERING↗

Quantum Devices for Neutrino and Rare Particle Detection (Final Report)

This report summarizes the technical work completed under the DOE-QuanISED program. This grant allowed the MIT group --and associated groups on the project, including UMass Amherst and Argonne National Laboratory -- to explore the use of superconducting bolometers for the purpose of neutrino and low mass dark matter detection. These low threshold bolometric detection techniques have wide applicability in nuclear and particle physics, including searching for low mass weakly-interacting dark matter; detecting neutrinos via coherent neutrino scattering; searching for axions and nuclear non-proliferation. In addition, we explored how using techniques readily used by the quantum computing community–such as multiplexed microwave resonators and quantum amplifiers—could be used as a low noise readout scheme for an array of superconducting detectors. We briefly summarized the accomplishments under the project, and what future research directions have spawned from this research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High-throughput chemical imaging for optimizing biofuel synthesis using synthetic biology (Final Technical Report)

Fatty acids can be produced biosynthetically in microbes and these compounds can serve as precursors to biodiesels and other high value oleochemicals. However, progress on engineering fatty acid biosynthesis, and biofuel synthesis more generally, has been hindered by current quantification methods that are either indirect or not amenable to high-throughput or single-cell resolution screening. In this project, we assembled an interdisciplinary team with complimentary expertise in synthetic biology and microscopy, metabolic engineering, and chemical imaging to address these challenges. We used chemical imaging to directly measure lipid biosynthesis in Escherichia coli engineered to produce fatty acids, obtaining detailed single-cell resolution measurements. We deployed stimulated Raman scattering (SRS) microscopy in concert with multiplexed genome engineering and gene circuit design strategies from synthetic biology to optimize production of fatty acids. These results provided novel insight into cell-to-cell heterogeneity present in biofuel production strains. In addition, we introduced new chemical imaging methods which are label-free and do not require fluorescent reporters. These efforts were complemented by other studied developing foundational tools for regulation and control, which offer excellent potential for advancing researchers’ ability to rapidly design, build, and test strains for enhanced biofuel synthesis.

09 BIOMASS FUELS↗

Improved Biofuel Production through Discovery and Engineering of Terpene Metabolism in Switchgrass

Project Objectives - Of the myriad specialized metabolites that plants deploy to adapt to environmental challenges, terpenes form the largest group. In many major crops, unique terpene blends serve as key stress defenses that directly impact plant fitness and yield. In addition, terpenes, such as bisabolene and pinene, are used for producing renewable biofuels. Essential to advancing a broader use of terpenes for biofuel feedstock engineering is a system-wide knowledge of the diverse biosynthetic machinery and defensive potential of often species-specific terpene blends. The proposed project would merge genome-wide enzyme discovery with comparative –omics, protein structural and plant microbiome studies to define the biosynthesis and stress-defensive functions of the switchgrass (Panicum virgatum) terpene network. These insights would be combined with developing and applying non-transgenic genome editing tools to design plants with desirable terpene blends for higher productivity and biofuel production on marginal lands. As a dedicated lignocellulosic feedstock for U.S. biofuel production with high net energy yield, stress tolerance, and available genome resources, switchgrass is well-suited for devising new avenues for biofuel production. Project Description – The diversity of plant terpene defenses is governed by species-specific families of terpene synthase (TPS) and cytochrome P450 monooxygenase (P450) enzymes. Mining of the switchgrass genome (genotype Alamo) identified ~100 TPS and P450 candidate genes, and combinatorial biochemical analysis of synthesized TPSs and P450s revealed more than a dozen enzymes with common and novel activities. In addition, several identified terpene metabolites and the corresponding transcripts were up-regulated in response to abiotic stressors. These findings demonstrate a unique switchgrass terpene network with probable importance to abiotic stress tolerance, thus providing a large chemical portfolio for optimizing crop resistance, yield, and biofuel composition. Leveraging these preliminary data, we propose to generate a genome-wide map of the switchgrass terpene metabolic network through multi-gene co-expression analyses that allow the efficient cross-validation of TPS and P450 functions. Key enzymes would further be applied to structure-function studies via X-ray protein crystallography, homology modeling and site-directed mutagenesis to gain mechanistic insight into the catalytic specificity of switchgrass terpene metabolism and provide gene and amino acid targets for genome editing. In tandem with terpene pathway discovery, system-wide metabolomics, transcriptomics and proteomics studies in switchgrass accessions of contrasting drought tolerance would define the role of switchgrass terpene metabolism in conferring abiotic stress resilience. Metabolic changes would be assessed in a combined approach of targeted (terpenes) and untargeted metabolite profiling using a high-resolution LC-MS/MS approach, differential gene expression analyses through multiplexed Illumina RNA sequencing, and quantitative analysis of high-priority pathway enzymes using multiple reaction monitoring (MRM). Drawing on these insights, knock-down/out mutants of stress-associated pathway nodes would be generated by optimizing transient virus-induced gene silencing (VIGS) and CRISPR/Cas9 systems under control of the Tobacco Rattle Virus (TRV). The resulting mutant lines would then be analyzed for stress susceptibility and the impact on the root microbiome to define gene functions in planta. Knowledge of terpene pathways, enzyme mechanisms and bioactivities would be applied to enhance switchgrass stress resilience and to tailor-make terpene blends for biofuel production. Here, TRV-enabled CRISPR/Cas9 genome editing, including allele-specific knock-out of redundant genes, engineering of enzyme specificity via structure-guided point mutations, and overexpression of terpene genes relevant to stress-protection or biofuel production, would be used to increase metabolic flux toward desired pathways. Broader Impacts - Integrating the system-wide discovery, mechanistic analysis and non-transgenic genome engineering of the switchgrass terpene network aligns the required steps to unlock the chemical potential of this important metabolite class to generate crops that are more resistant to stress and provide advanced biofuel production in light of rising climate pressures as foreseeable challenges for bioenergy crop cultivation. The proposed project would further offer interdisciplinary student training through active involvement in the project and integration of research concepts and outcomes into newly-developed graduate and undergraduate courses on Plant Biotechnology.

09 BIOMASS FUELS↗

NucD-25 Nuclear Diagnostics Development: NIS capability, Maximizing gamma ray dynamic range, (n,γ) measurements for carbon ρR [Slides]

The LANL Neutron Imaging team is preparing for NIS upgrades and novel capabilities with the advent of consistently higher yields at NIF. Novel scintillators, solid-state detectors, multiplexed imaging detectors, upgraded data acquisition systems, and camera testing are all areas in need of experimental study to further develop imaging capabilities and dynamic range at NIF.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

FRET Based Biosensors for CBRN Threat Detection

Biosensors are devices used to detect the presence/concentration of a biological analyte. Biosensors consist of three parts: 1) a component that recognizes the analyte and produces a signal, 2) a signal transducer, and 3) a reader device. A multiplexed biosensor combines different biosensors for increased detection capabilities.

Demers, Steven M.↗

Seeing in with X-rays: 4D Strain and Thermometry Measurements for Thermal-Mechanical Testing

Understanding temperature-dependent material decomposition and structural deformation induced by combined thermal-mechanical environments is critical for safety qualification of hardware under accident scenarios. Seeing in with X-rays elucidated the physics necessary to develop X-ray strain and thermometry diagnostics for use in optically opaque environments. Two parallel thermometry schemes were explored: X-ray fluorescence and X-ray diffraction of inorganic doped ceramics– colloquially known as thermographic phosphors. Two parallel surface strain techniques–Path-Integrated Digital Image Correlation and Frequency Multiplexed Digital Image Correlation–were demonstrated. Finally, preliminary demonstration of time-resolved digital volume correlation was performed by taking advantage of limited view reconstruction techniques. Additionally, research into blended ceramic-metal coatings was critical to generating intrinsic thermographic patterns for the future combination of X-ray strain and thermometry measurements.

36 MATERIALS SCIENCE↗