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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Automated Clean Chemistry for Bulk Analysis of Environmental Swipe Samples – Final Report

Sample preparation methods for mass spectrometry are being automated using commercial-off-the-shelf (COTS) equipment to shorten lengthy and costly manual chemical purification procedures. This development addresses a serious need in the International Atomic Energy Agency’s (IAEA) Network of Analytical Laboratories (NWAL) to increase efficiency in the Bulk Analysis of Environmental Samples for Safeguards program with a method that allows unattended, overnight operation. In collaboration with Elemental Scientific Inc. (ESI), the prepFAST-MC2 was designed based on COTS equipment. It was modified for uranium/plutonium separations using renewable columns packed with Eichrom TEVA® and UTEVA® resins, with a chemical separation method based on the Oak Ridge National Laboratory (ORNL) NWAL chemical procedure. Initial verification of individual columns yielded small elution volumes with consistent elution profiles and good recovery. Combined column calibration demonstrated ample separation without crosscontamination of the eluent. Automated packing and unpacking of the built-in columns initially showed >15% deviation in resin loading by weight, which can lead to inconsistent separations. Optimization of the packing and unpacking methods led to a reduction in the variability of the packed resin to less than 5% daily. Based on the initial experience at ORNL with the prepFAST-MC2, a second-generation model, the prepFAST-SR, was built by ESI. The newly designed prepFAST-SR has several upgrades compared with the original prepFAST-MC2. The upgrades largely addressed issues with the reliability of unpacking the Eichrom columns and with ventilation to ensure adequate removal of acid vapors. Both systems are currently installed in the Ultra-Trace Forensics Science Center at ORNL. Separations of mixed uranium and plutonium samples containing certified reference materials were analyzed by multi-collector inductively coupled plasma mass spectrometry and yielded good results. Current efforts have demonstrated a wider applicability of the prepFAST system. Near-quantitative removal of metal interferences was achieved with the system in both uranium and plutonium separated fractions. Successful system validation was completed with several archived samples. Isotopic results from archived samples and certified reference materials were well within data quality limits for the IAEA NWAL. Additional COTS equipment has been evaluated for its potential to aid the prepFAST-SR system in reducing the time allotments and cleanroom infrastructure requirements for accurate separations. Overall, these efforts help ensure continued efficient and effective operation of the NWAL. Comparison of the amount of personnel time necessary for successful manual vs. automated chemical separations showed a significant decrease in hands-on time from 9.8 hours to 35 minutes for seven samples, respectively. This documented time savings and reduced labor translates to a significant cost savings per sample. Overall, the system will enable faster sample reporting times at reduced cost by limiting personnel hours dedicated to the chemical separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2000

Performance of an Optimized Eta Model Code on the Cray T3E and a Network of PCs

In the year 2001, NASA will launch the satellite TRIANA that will be the first Earth observing mission to provide a continuous, full disk view of the sunlit Earth. As a part of the HPCC Program at NASA GSFC, we have started a project whose objectives are to develop and implement a 3D cloud data assimilation system, by combining TRIANA measurements with model simulation, and to produce accurate statistics of global cloud coverage as an important element of the Earth's climate. For simulation of the atmosphere within this project we are using the NCEP/NOAA operational Eta model. In order to compare TRIANA and the Eta model data on approximately the same grid without significant downscaling, the Eta model will be integrated at a resolution of about 15 km. The integration domain (from -70 to +70 deg in latitude and 150 deg in longitude) will cover most of the sunlit Earth disc and will continuously rotate around the globe following TRIANA. The cloud data assimilation is supposed to run and produce 3D clouds on a near real-time basis. Such a numerical setup and integration design is very ambitious and computationally demanding. Thus, though the Eta model code has been very carefully developed and its computational efficiency has been systematically polished during the years of operational implementation at NCEP, the current MPI version may still have problems with memory and efficiency for the TRIANA simulations. Within this work, we optimize a parallel version of the Eta model code on a Cray T3E and a network of PCs (theHIVE) in order to improve its overall efficiency. Our optimization procedure consists of introducing dynamically allocated arrays to reduce the size of static memory, and optimizing on a single processor by splitting loops to limit the number of streams. All the presented results are derived using an integration domain centered at the equator, with a size of 60 x 60 deg, and with horizontal resolutions of 1/2 and 1/3 deg, respectively. In accompanying charts we report the elapsed time, the speedup and the Mflops as a function of the number of processors for the non-optimized version of the code on the T3E and theHIVE. The large amount of communication required for model integration explains its poor performance on theHIVE. Our initial implementation of the dynamic memory allocation has contributed to about 12% reduction of memory but has introduced a 3% overhead in computing time. This overhead was removed by performing loop splitting in some of the high demanding subroutines. When the Eta code is fully optimized in order to meet the memory requirement for TRIANA simulations, a non-negligeable overhead may appear that may seriously affect the efficiency of the code. To alleviate this problem, we are considering implementation of a new algorithm for the horizontal advection that is computationally less expensive, and also a new approach for marching in time.

Kouatchou, Jules↗
NASA NTRS2014

Chapter 11: City-Wide Collaborations for Urban Climate Education

Although cities cover only 2 percent of the Earth's surface, more than 50 percent of the world's people live in urban environments, collectively consuming 75 percent of the Earth's resources. Because of their population densities, reliance on infrastructure, and role as centers of industry, cities will be greatly impacted by, and will play a large role in, the reduction or exacerbation of climate change. However, although urban dwellers are becoming more aware of the need to reduce their carbon usage and to implement adaptation strategies, education efforts on these strategies have not been comprehensive. To meet the needs of an informed and engaged urban population, a more systemic, multiplatform and coordinated approach is necessary. The Climate and Urban Systems Partnership (CUSP) is designed to explore and address this challenge. Spanning four cities-Philadelphia, New York, Pittsburgh, and Washington, DC-the project is a partnership between the Franklin Institute, the Columbia University Center for Climate Systems Research, the University of Pittsburgh Learning Research and Development Center, Carnegie Museum of Natural History, New York Hall of Science, and the Marian Koshland Science Museum of the National Academy of Sciences. The partnership is developing a comprehensive, interdisciplinary network to educate urban residents about climate science and the urban impacts of climate change.

Climate change↗
NASA NTRS2023

Marin County Wildland Fires: Examining Fuel Load and Land Cover Change to Inform Fire Prevention and Suppression Decisions in Marin County, CA

Heightened occurrence of severe wildfires in the Western United States is increasing the need to better understand regions of high potential wildfire severity and develop methodologies for identifying the best locations for fuels reduction and active wildfire suppression, especially in populated regions such as Marin County, California. Marin County, located in the San Francisco Bay Area, has had significant development in the wildland-urban interface and periods of highly wildfire-prone conditions. The NASA DEVELOP team collaborated with Fire Foundry (a Marin-based fire service workforce development program) and the Marin County Fire Department to develop models to assist with fire management. Using data from Sentinel-2A, PlanetScope, ECOSTRESS, a county-wide LiDAR mapping effort, Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI), our team developed a number of input data layers for three different models to evaluate wildfire severity. One model performed a suitability analysis with weights based on scientific literature; another model utilized a U-Net Convolutional Neural Network trained on previous fires in Marin and neighboring Sonoma County to predict the difference normalized burn severity; and the third inputted data layers into the FlamMap tool that outputs risk categories. We compared model outputs and performed a weighted overlay analysis to identify specific locations where a fireline could be constructed to interrupt the progress of an active fire. These tools will assist partners in preparing for and managing active wildfire situations.

Remote sensing↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Geochemical Exports to River From the Intrameander Hyporheic Zone Under Transient Hydrologic Conditions: East River Mountainous Watershed, Colorado

To understand how redox processes influence carbon, nitrogen, and iron cycling within the intrameander hyporheic zone, we developed a biotic and abiotic reaction network and incorporated it into the reactive transport simulator PFLOTRAN. Additionally, two-dimensional reactive flow and transport simulations were performed (1) to evaluate how transient hydrological conditions control the lateral redox zonation within an intrameander region of the East River in Colorado and (2) to quantify the impact of a single meander on subsurface exports of carbon and other geochemical species to the river. The meander's overall contribution to the river was quantified by integrating geochemical outfluxes along the outside of the meander bend. The model was able to capture the field-observed trends of dissolved oxygen, nitrate, iron, pH, and total inorganic carbon along a 2-D transect. Consistent with field observations, simulated dissolved oxygen and nitrate decreased along the intrameander flow paths while iron (Fe 2+ ) concentration increased. The simulation results further demonstrated that the reductive potential of the lateral redox zonation was controlled by groundwater velocities resulting from river stage fluctuations, with low-water conditions promoting reducing conditions. The sensitivity analysis results showed that permeability had a more significant impact on biogeochemical zonation compared to the reaction pathways under transient hydrologic conditions. Lastly, the simulation results further indicated that the meander acted as a sink for organic and inorganic carbon as well as iron during the extended baseflow and high-water conditions; however, these geochemical species were released into the river during the falling limb of the hydrograph.

58 GEOSCIENCES↗
DOE OSTI2015

Project ATHENA Creates Surrogate Human Organ Systems

The development of miniature surrogate human organs, coupled with highly sensitive mass spectrometry technologies, could one day revolutionize the way new drugs and toxic agents are studied. “By developing this ‘homo minutus,’ we are stepping beyond the need for animal or Petri dish testing: There are huge benefits in developing drug and toxicity analysis systems that can mimic the response of actual human organs,” said Rashi Iyer, a senior scientist at Los Alamos National Laboratory. ATHENA, the Advanced Tissue-engineered Human Ectypal Network Analyzer project team, is nearing the full integration of four human organ constructs — liver, heart, lung and kidney — each organ component is about the size of a smartphone screen, and the whole ATHENA “body” of interconnected organs will fit neatly on a desk. A new video available on the Los Alamos National Laboratory YouTube channel updates the ATHENA project as it begins to integrate the various organ systems into a single system. Some 40 percent of pharmaceuticals fail their clinical trials and there are thousands of chemicals whose effects on humans are simply unknown. Providing a realistic, cost-effective and rapid screening system such as ATHENA with high-throughput capabilities could provide major benefits to the medical field, screening more accurately and offering a greater chance of clinical trial success. ATHENA is funded by the Defense Threat Reduction Agency (DTRA) and is a collaboration of Los Alamos National Laboratory, Harvard University, Vanderbilt University, Charité Universitätsmedizin, Berlin, Germany, CFD Research Corporation, and the University of California San Francisco.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

The cbb 3 -type cytochrome oxidase assembly factor CcoG is a widely distributed cupric reductase

Copper (Cu)-containing proteins execute essential functions in prokaryotic and eukaryotic cells, but their biogenesis is challenged by high Cu toxicity and the preferential presence of Cu(II) under aerobic conditions, while Cu(I) is the preferred substrate for Cu chaperones and Cu-transport proteins. These proteins form a coordinated network that prevents Cu accumulation, which would lead to toxic effects such as Fenton-like reactions and mismetalation of other metalloproteins. Simultaneously, Cu-transport proteins and Cu chaperones sustain Cu(I) supply for cuproprotein biogenesis and are therefore essential for the biogenesis of Cu-containing proteins. In eukaryotes, Cu(I) is supplied for import and trafficking by cell-surface exposed metalloreductases, but specific cupric reductases have not been identified in bacteria. It was generally assumed that the reducing environment of the bacterial cytoplasm would suffice to provide sufficient Cu(I) for detoxification and cuproprotein synthesis. Here, we identify the proposed cbb 3 -type cytochrome c oxidase ( cbb 3 -Cox) assembly factor CcoG as a cupric reductase that binds Cu via conserved cysteine motifs and contains 2 low-potential [4Fe-4S] clusters required for Cu(II) reduction. Deletion of ccoG or mutation of the cysteine residues results in defective cbb 3 -Cox assembly and Cu sensitivity. Furthermore, anaerobically purified CcoG catalyzes Cu(II) but not Fe(III) reduction in vitro using an artificial electron donor. Thus, CcoG is a bacterial cupric reductase and a founding member of a widespread class of enzymes that generate Cu(I) in the bacterial cytosol by using [4Fe-4S] clusters.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Current state and future direction of computer systems at NASA Langley Research Center

Computer systems have advanced at a rate unmatched by any other area of technology. As performance has dramatically increased there has been an equally dramatic reduction in cost. This constant cost performance improvement has precipitated the pervasiveness of computer systems into virtually all areas of technology. This improvement is due primarily to advances in microelectronics. Most people are now convinced that the new generation of supercomputers will be built using a large number (possibly thousands) of high performance microprocessors. Although the spectacular improvements in computer systems have come about because of these hardware advances, there has also been a steady improvement in software techniques. In an effort to understand how these hardware and software advances will effect research at NASA LaRC, the Computer Systems Technical Committee drafted this white paper to examine the current state and possible future directions of computer systems at the Center. This paper discusses selected important areas of computer systems including real-time systems, embedded systems, high performance computing, distributed computing networks, data acquisition systems, artificial intelligence, and visualization.

Rogers, James L.↗
DOE OSTI2014

Comparison of Optimal Thermodynamic Models of the Tricarboxylic Acid Cycle from Heterotrophs, Cyanobacteria, and Green Sulfur Bacteria

We have applied a new stochastic simulation approach to predict the metabolite levels, energy flow, and material flux in the different oxidative TCA cycles found in E. coli and Synechococcus sp. PCC 7002, and in the reductive TCA cycle typical of chemolithoautotrophs and phototrophic green sulfur bacteria such as Chlorobaculum tepidum. The simulation approach is based on equations of state and employs an assumption similar to that used in transition state theory. The ability to evaluate the thermodynamics of metabolic pathways allows one to understand the relationship between coupling of energy and material gradients in the environment and the selforganization of stable biological systems, and it is shown that each cycle operates in the direction expected due to its environmental niche. The simulations predict changes in metabolite levels and flux in response to changes in cofactor concentrations that would be hard to predict without an elaborate model based on the law of mass action. In fact, we show that a thermodynamically unfavorable reaction can still have flux in the forward direction when it is part of a reaction network. The ability to predict metabolite levels, energy flow and material flux should be significant for understanding the dynamics of natural systems and for understanding principles for engineering organisms for production of specialty chemicals, such as biofuels.

Thomas, Dennis G.↗
NASA NTRS1988

A fault injection experiment using the AIRLAB Diagnostic Emulation Facility

The preparation for, conduct of, and results of a simulation based fault injection experiment conducted using the AIRLAB Diagnostic Emulation facilities is described. An objective of this experiment was to determine the effectiveness of the diagnostic self-test sequences used to uncover latent faults in a logic network providing the key fault tolerance features for a flight control computer. Another objective was to develop methods, tools, and techniques for conducting the experiment. More than 1600 faults were injected into a logic gate level model of the Data Communicator/Interstage (C/I). For each fault injected, diagnostic self-test sequences consisting of over 300 test vectors were supplied to the C/I model as inputs. For each test vector within a test sequence, the outputs from the C/I model were compared to the outputs of a fault free C/I. If the outputs differed, the fault was considered detectable for the given test vector. These results were then analyzed to determine the effectiveness of some test sequences. The results established coverage of selt-test diagnostics, identified areas in the C/I logic where the tests did not locate faults, and suggest fault latency reduction opportunities.

Baker, Robert↗
DOE OSTI2024

To What Extent Will Decarbonization Deepen the Conversation Between Industry and the Grid?

Decarbonization - the transition away from un-mitigated fossil fuel combustion throughout the economy - requires big changes from both power and process systems. On the power system side, those changes are expected to include large increases in variable generation, e.g., from wind and solar, which has near-zero marginal costs and at large shares can produce infrequent but consequential energy droughts. On the process systems side, industries are investigating their options for direct and indirect electrification, the latter exemplified by replacing fossil fuel inputs with zero-carbon, energy-carrying chemicals like hydrogen and ammonia produced via electrochemical processes. The economic features of these changes within the larger context of power and process systems suggest that their realization could be accompanied by a paradigm shift in how industrial facilities interact with the grid. For example, the dominant type of demand participation in power markets could change from today's focus on load reductions at peak times to a new focus on shifting electricity use, enabled in part by large-scale product storage, to take advantage of renewable energy that would otherwise be curtailed and to avoid consumption during high-price energy droughts. This talk will describe these and other possible design and operational approaches from grid and industrial economic perspectives, culminating in an enumeration of open problems that lie at the interface of today and tomorrow's power and process systems.

co-design↗
DOE OSTI2014

Roles of Sensory Nerves in the Regulation of Radiation-Induced Structural and Functional Changes in the Heart

Purpose: Radiation-induced heart disease (RIHD) is a chronic severe side effect of radiation therapy of intrathoracic and chest wall tumors. The heart contains a dense network of sensory neurons that not only are involved in monitoring of cardiac events such as ischemia and reperfusion but also play a role in cardiac tissue homeostasis, preconditioning, and repair. The purpose of this study was to examine the role of sensory nerves in RIHD. Methods and Materials: Male Sprague-Dawley rats were administered capsaicin to permanently ablate sensory nerves, 2 weeks before local image-guided heart x-ray irradiation with a single dose of 21 Gy. During the 6 months of follow-up, heart function was assessed with high-resolution echocardiography. At 6 months after irradiation, cardiac structural and molecular changes were examined with histology, immunohistochemistry, and Western blot analysis. Results: Capsaicin pretreatment blunted the effects of radiation on myocardial fibrosis and mast cell infiltration and activity. By contrast, capsaicin pretreatment caused a small but significant reduction in cardiac output 6 months after irradiation. Capsaicin did not alter the effects of radiation on cardiac macrophage number or indicators of autophagy and apoptosis. Conclusions: These results suggest that sensory nerves, although they play a predominantly protective role in radiation-induced cardiac function changes, may eventually enhance radiation-induced myocardial fibrosis and mast cell activity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1992

Approximation methods for stochastic petri nets

Stochastic Marked Graphs are a concurrent decision free formalism provided with a powerful synchronization mechanism generalizing conventional Fork Join Queueing Networks. In some particular cases the analysis of the throughput can be done analytically. Otherwise the analysis suffers from the classical state explosion problem. Embedded in the divide and conquer paradigm, approximation techniques are introduced for the analysis of stochastic marked graphs and Macroplace/Macrotransition-nets (MPMT-nets), a new subclass introduced herein. MPMT-nets are a subclass of Petri nets that allow limited choice, concurrency and sharing of resources. The modeling power of MPMT is much larger than that of marked graphs, e.g., MPMT-nets can model manufacturing flow lines with unreliable machines and dataflow graphs where choice and synchronization occur. The basic idea leads to the notion of a cut to split the original net system into two subnets. The cuts lead to two aggregated net systems where one of the subnets is reduced to a single transition. A further reduction leads to a basic skeleton. The generalization of the idea leads to multiple cuts, where single cuts can be applied recursively leading to a hierarchical decomposition. Based on the decomposition, a response time approximation technique for the performance analysis is introduced. Also, delay equivalence, which has previously been introduced in the context of marked graphs by Woodside et al., Marie's method and flow equivalent aggregation are applied to the aggregated net systems. The experimental results show that response time approximation converges quickly and shows reasonable accuracy in most cases. The convergence of Marie's method and flow equivalent aggregation are applied to the aggregated net systems. The experimental results show that response time approximation converges quickly and shows reasonable accuracy in most cases. The convergence of Marie's is slower, but the accuracy is generally better. Delay equivalence often fails to converge, while flow equivalent aggregation can lead to potentially bad results if a strong dependence of the mean completion time on the interarrival process exists.

Jungnitz, Hauke Joerg↗
DOE OSTI2024

Pore confinement enhances but surface adhesion reduces bacterial cell-to-cell conjugation

As the habitats of bacteria, soil pore network and surface properties control the distribution, adhesion, and motility of bacteria in soils. These physical processes in turn influence bacterial accesses to nutrients and bacterial interactions. Our understanding on the pore- and surface-mediated bacterial interactions is currently limited. In this research, we evaluated the effects of soil pore confinement and surface adhesion on conjugation-based bacterial interactions. The interaction was measured by plasmid transfer between donor and recipient cells within the population of soil bacterium Pseudomonas putida. We found that the presence of porous sand media led to a net increase in conjugation frequency compared to sand-free liquid control. The increase is attributed to the facilitated effect of pore confinement on the collision of bacteria within pores. In contrast, bacterial adhesion to sand surfaces under elevated ionic strength conditions decreased the conjugation frequency as a result of mobility reduction on the surface. Such collision and adhesion mechanisms jointly drive the conjugation as a function of pore and surface properties of porous media. Finally, these results provide valuable insights into the roles of soil pores and surfaces in regulating horizontal gene transfer, an essential cell-to-cell interaction sustaining key processes of soil ecology and health.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Sub-melt nanosecond pulsed-laser induced densification and strain-field relaxation in single-crystal diamond

Dislocations and polishing-induced defect networks in synthetic diamond introduce local strain fields and broaden Raman features, limiting performance in optical, thermal, and electronic applications. Laser annealing is emerging as a promising approach to repair surface and near-surface defects in diamond without entering the melt regime, yet surface densification, defect-state modification, and associated structural changes have not been well quantified. In this work, we show that sub-melt nanosecond pulsed-laser annealing (PLA) induces near-surface densification and defect-mediated strain relaxation in single-crystal Chemical Vapor Deposition (CVD) diamond. Single- and two-pulse PLA were applied, and structural evolution was quantified using co-registered ISO 25,178 white-light interferometry, depth-resolved Raman spectroscopy, and cross-sectional STEM with geometric phase analysis (GPA). Across a 5 × 6 grid (n = 30), responsive regions exhibit large reductions in local slope (Sdq 45–65%), developed area (Sdr 60–90%), height spread (Sp, Sz 30–65%), void volume (Vv 57–60%), and roughness amplitude (Sa, Sq 48–57%), consistent with densification of ∼4–6.5 nm. Raman profiling shows narrowing of the diamond line and improved spectral uniformity to depths of ∼2–3 μm. Given that the Raman probing depth significantly exceeds the densified layer thickness, this response is interpreted as consistent with long-range strain-field redistribution originating from the near-surface region. STEM-GPA strain maps further support this interpretation, showing smoother strain fields, suppressed hotspots, and redistribution of localized strain concentrations following PLA. These results are consistent with defect-mediated strain relaxation and densification-driven modification of the near-surface energy state. The approach provides a scalable pathway for improving near-surface structural quality in diamond relevant to electronic, photonic, and quantum applications.

Areal surface metrology (ISO 25,178)↗
DOE OSTI2020

Correlation-based network analysis combined with machine learning techniques highlight the role of the GABA shunt in Brachypodium sylvaticum freezing tolerance

Perennial grasses will account for approximately 16 billion gallons of renewable fuels by the year 2022, contributing significantly to carbon and nitrogen sequestration. However, perennial grasses productivity can be limited by severe freezing conditions in some geographical areas, although these risks could decrease with the advance of climate warming, the possibility of unpredictable early cold events cannot be discarded. We conducted a study on the model perennial grass Brachypodium sylvaticum to investigate the molecular mechanisms that contribute to cold and freezing adaption. The study was performed on two different B. sylvaticum accessions, Ain1 and Osl1, typical to warm and cold climates, respectively. Both accessions were grown under controlled conditions with subsequent cold acclimation followed by freezing stress. For each treatment a set of morphological parameters, transcription, metabolite, and lipid profiles were measured. State-of-the-art algorithms were employed to analyze cross-component relationships. Phenotypic analysis revealed higher adaption of Osl1 to freezing stress. Our analysis highlighted the differential regulation of the TCA cycle and the GABA shunt between Ain1 and Osl1. Osl1 adapted to freezing stress by repressing the GABA shunt activity, avoiding the detrimental reduction in fatty acid biosynthesis and the concomitant detrimental effects on membrane integrity.

54 ENVIRONMENTAL SCIENCES↗