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DOE OSTI2020

Machine learning study of magnetism in uranium-based compounds

Actinide and lanthanide-based materials display exotic properties that originate from the presence of itinerant or localized f electrons and include unconventional superconductivity and magnetism, hidden order, and heavy-fermion behavior. Due to the strongly correlated nature of the 5f electrons, magnetic properties of these compounds depend sensitively on applied magnetic field and pressure, as well as on chemical doping. However, precise connection between the structure and magnetism in actinide-based materials is currently unclear. In this investigation, we established such structure-property links by assembling and mining two datasets that aggregate, respectively, the results of high-throughput density functional theory simulations and experimental measurements for the families of uranium- and neptunium-based binary compounds. Various regression algorithms were utilized to identify correlations among accessible attributes (features or descriptors) of the material systems and predict their cation magnetic moments and general forms of magnetic ordering. Descriptors representing compound structural parameters and cation f-subshell occupation numbers were identified as most important for accurate predictions. The best machine learning model developed employs the random forest regression algorithm. It can predict both spin and orbit moment size with root-mean-square error of 0.17 μ B and 0.19 μ B , respectively. Lastly, the random forest classification algorithm is used to predict the ordering (paramagnetic, ferromagnetic, and antiferromagnetic) of such systems with 76% accuracy.

36 MATERIALS SCIENCE↗

NASA NTRS2011

Origins of Protein Functions in Cells

In modern organisms proteins perform a majority of cellular functions, such as chemical catalysis, energy transduction and transport of material across cell walls. Although great strides have been made towards understanding protein evolution, a meaningful extrapolation from contemporary proteins to their earliest ancestors is virtually impossible. In an alternative approach, the origin of water-soluble proteins was probed through the synthesis and in vitro evolution of very large libraries of random amino acid sequences. In combination with computer modeling and simulations, these experiments allow us to address a number of fundamental questions about the origins of proteins. Can functionality emerge from random sequences of proteins? How did the initial repertoire of functional proteins diversify to facilitate new functions? Did this diversification proceed primarily through drawing novel functionalities from random sequences or through evolution of already existing proto-enzymes? Did protein evolution start from a pool of proteins defined by a frozen accident and other collections of proteins could start a different evolutionary pathway? Although we do not have definitive answers to these questions yet, important clues have been uncovered. In one example (Keefe and Szostak, 2001), novel ATP binding proteins were identified that appear to be unrelated in both sequence and structure to any known ATP binding proteins. One of these proteins was subsequently redesigned computationally to bind GTP through introducing several mutations that introduce targeted structural changes to the protein, improve its binding to guanine and prevent water from accessing the active center. This study facilitates further investigations of individual evolutionary steps that lead to a change of function in primordial proteins. In a second study (Seelig and Szostak, 2007), novel enzymes were generated that can join two pieces of RNA in a reaction for which no natural enzymes are known. Recently it was found that, as in the previous case, the proteins have a structure unknown among modern enzymes. In this case, in vitro evolution started from a small, non-enzymatic protein. A similar selection process initiated from a library of random polypeptides is in progress. These results not only allow for estimating the occurrence of function in random protein assemblies but also provide evidence for the possibility of alternative protein worlds. Extant proteins might simply represent a frozen accident in the world of possible proteins. Alternative collections of proteins, even with similar functions, could originate alternative evolutionary paths.

Seelig, Burchard↗

DOE OSTI2016

TU-AB-BRC-12: Optimized Parallel MonteCarlo Dose Calculations for Secondary MU Checks

Purpose: Secondary MU checks are an important tool used during a physics review of a treatment plan. Commercial software packages offer varying degrees of theoretical dose calculation accuracy, depending on the modality involved. Dose calculations of VMAT plans are especially prone to error due to the large approximations involved. Monte Carlo (MC) methods are not commonly used due to their long run times. We investigated two methods to increase the computational efficiency of MC dose simulations with the BEAMnrc code. Distributed computing resources, along with optimized code compilation, will allow for accurate and efficient VMAT dose calculations. Methods: The BEAMnrc package was installed on a high performance computing cluster accessible to our clinic. MATLAB and PYTHON scripts were developed to convert a clinical VMAT DICOM plan into BEAMnrc input files. The BEAMnrc installation was optimized by running the VMAT simulations through profiling tools which indicated the behavior of the constituent routines in the code, e.g. the bremsstrahlung splitting routine, and the specified random number generator. This information aided in determining the most efficient compiling parallel configuration for the specific CPU’s available on our cluster, resulting in the fastest VMAT simulation times. Our method was evaluated with calculations involving 10{sup 8} – 10{sup 9} particle histories which are sufficient to verify patient dose using VMAT. Results: Parallelization allowed the calculation of patient dose on the order of 10 – 15 hours with 100 parallel jobs. Due to the compiler optimization process, further speed increases of 23% were achieved when compared with the open-source compiler BEAMnrc packages. Conclusion: Analysis of the BEAMnrc code allowed us to optimize the compiler configuration for VMAT dose calculations. In future work, the optimized MC code, in conjunction with the parallel processing capabilities of BEAMnrc, will be applied to provide accurate and efficient secondary MU checks.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

National serosurvey and risk mapping reveal widespread distribution of Coxiella burnetii in Kenya

Coxiella burnetii, the causative agent of Q fever, is an emerging pathogen that has the potential to cause severe chronic infections in animals and humans worldwide. The detrimental impact on public health is projected to be higher in the low- and middle-income countries given their lower capacity to sustain effective surveillance and response measures. We implemented a national serosurvey of cattle in Kenya to map the spatial distribution of the pathogen. The study used serum samples that were collected from randomly selected cattle in different ago-ecological zones across the country. These samples were screened for the pathogen using PrioCHECK Ruminant Q Fever AB Plate ELISA kit. The laboratory findings were analyzed using INLA package to identify risk factors for C. burnetii exposure from herd- and animal-level factors, area, and bioclimatic datasets accessed from online databases. A total of 6,593 cattle were recruited for the study; of these, 7.9% (95% CI; 7.2–8.5) were seropositive. Outputs from the multivariable analysis revealed that the animal age and some of the geographical variables including wind speed, area under shrubs and “petric calcisols” type of soil were significantly associated with C. burnetii seropositivity. Being a calf, weaner or subadult was associated with lower odds of exposure compared to being an adult by 0.24 (credibility interval: 2.5% and 97.5%), 0.41 (0.30–0.55) and 0.51 (0.38–0.69), respectively. In addition, a unit increase in the wind speed increased the odds of C. burnetii seropositivity by 1.27 (1.05–1.52) while an increase on the land area under shrubs was associated with lower odds of exposure (0.67 [0.47–0.69]). The effect of petric calcisols was non-linear; an increase of the land area with this soil type was associated with an exponential increase in C. burnetii seropositivity. This study provides new data on C. burnetii seroprevalence, information of its risk factors and a prevalence map that can be used for C. burnetii risk surveillance and control. The identification of environmental risk factors for C. burnetii exposure, and the increasing awareness of the zoonotic potential of the pathogen, calls for the need to enhance the existing collaborations for the surveillance and control of C. burnetii in line with the One Health framework. The evidence generated on the potential role of environmental factors can also be used to design nature-based interventions, such as replacement of vegetation in denuded areas, to reduce potential for the aerosolization of the pathogen. Livestock vaccination in the hotspots would also reduce animal infections and hence the contamination of the environment.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Individual pore and interconnection size analysis of macroporous ceramic scaffolds using high-resolution X-ray tomography

The pore interconnection size of β-tricalcium phosphate scaffolds plays an essential role in the bone repair process. Although, the μCT technique is widely used in the biomaterial community, it is rarely used to measure the interconnection size because of the lack of algorithms. In addition, discrete nature of the μCT introduces large systematic errors due to the convex geometry of interconnections. We proposed, verified and validated a novel pore-level algorithm to accurately characterize the individual pores and interconnections. Specifically, pores and interconnections were isolated, labeled, and individually analyzed with high accuracy. The technique was verified thoroughly by visually inspecting and verifying over 3474 properties of randomly selected pores. This extensive verification process has passed a one-percent accuracy criterion. Scanning errors inherent in the discretization, which lead to both dummy and significantly overestimated interconnections, have been examined using computer-based simulations and additional high-resolution scanning. Then accurate correction charts were developed and used to reduce the scanning errors. Only after the corrections, both the μCT and SEM-based results converged, and the novel algorithm was validated. Material scientists with access to all geometrical properties of individual pores and interconnections, using the novel algorithm, will have a more-detailed and accurate description of the substitute architecture and a potentially deeper understanding of the link between the geometric and biological interaction. - Highlights: •An algorithm is developed to analyze individually all pores and interconnections. •After pore isolating, the discretization errors in interconnections were corrected. •Dummy interconnections and overestimated sizes were due to thin material walls. •The isolating algorithm was verified through visual inspection (99% accurate). •After correcting for the systematic errors, algorithm was validated successfully.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Serial snapshot crystallography for materials science with SwissFEL

New opportunities for studying (sub)microcrystalline materials with small unit cells, both organic and inorganic, will open up when the X-ray free electron laser (XFEL) presently being constructed in Switzerland (SwissFEL) comes online in 2017. Our synchrotron-based experiments mimicking the 4%-energy-bandpass mode of the SwissFEL beam show that it will be possible to record a diffraction pattern of up to 10 randomly oriented crystals in a single snapshot, to index the resulting reflections, and to extract their intensities reliably. The crystals are destroyed with each XFEL pulse, but by combining snapshots from several sets of crystals, a complete set of data can be assembled, and crystal structures of materials that are difficult to analyze otherwise will become accessible. Even with a single shot, at least a partial analysis of the crystal structure will be possible, and with 10–50 femtosecond pulses, this offers tantalizing possibilities for time-resolved studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Probing the structural and dynamical properties of liquid water with models including non-local electron correlation

Water is a ubiquitous liquid that displays a wide range of anomalous properties and has a delicate structure that challenges experiment and simulation alike. The various intermolecular interactions that play an important role, such as repulsion, polarization, hydrogen bonding, and van der Waals interactions, are often difficult to reproduce faithfully in atomistic models. Here, electronic structure theories including all these interactions at equal footing, which requires the inclusion of non-local electron correlation, are used to describe structure and dynamics of bulk liquid water. Isobaric-isothermal (NpT) ensemble simulations based on the Random Phase Approximation (RPA) yield excellent density (0.994 g/ml) and fair radial distribution functions, while various other density functional approximations produce scattered results (0.8-1.2 g/ml). Molecular dynamics simulation in the microcanonical (NVE) ensemble based on Møller-Plesset perturbation theory (MP2) yields dynamical properties in the condensed phase, namely, the infrared spectrum and diffusion constant. At the MP2 and RPA levels of theory, ice is correctly predicted to float on water, resolving one of the anomalies as resulting from a delicate balance between van der Waals and hydrogen bonding interactions. For several properties, obtaining quantitative agreement with experiment requires correction for nuclear quantum effects (NQEs), highlighting their importance, for structure, dynamics, and electronic properties. A computed NQE shift of 0.6 eV for the band gap and absorption spectrum illustrates the latter. Giving access to both structure and dynamics of condensed phase systems, non-local electron correlation will increasingly be used to study systems where weak interactions are of paramount importance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Severe Gastrointestinal Haemorrhage: Summary of a National Quality of Care Study with Focus on Radiological Services

Purpose of StudyTo identify the remediable factors in the quality of care provided to patients with severe gastrointestinal (GI) bleeding.MethodAll hospital admissions in the first four months of 2013 with ICD10 coding for GI bleeding who received a transfusion of 4 units or more of blood. Up to five cases/hospital randomly selected for structured case note peer review. National availability of GI bleeding services data derived from organisational questionnaire completed by all hospitals.Results4563/29,796 (15.3%) of GI bleeds received 4 or more units of blood with a mortality rate of 20.2% compared to 7.3% without blood transfusion. 30.8% of GI bleeds received a blood transfusion. 32% (60/185) of hospitals admitting acute GI bleeds lacked 24/7 endoscopy. 26% (48/185) had on-site embolisation 24/7 with a further 34% (64/185) accessing embolisation by transfer within a validated formal network. Blood product use was inappropriate in 20% (84/426). Improved management, principally earlier senior gastroenterologist review and/or endoscopy, would have reduced blood product use in 25% (113/457). 14.5% (90/618) had a CT scan which identified the site of bleeding in 32% (29/90). 7.8% (36/459) underwent an Interventional Radiology (IR) procedure but a further 6.3% (21/33) should have had IR. 6% (36/586) underwent surgery with 21/36 for uncontrolled bleeding. In 20/35 IR was not considered despite the majority being suitable for IR. Overall 44% (210/476) received an acceptable standard of care according to peer review.Conclusions26 recommendations were made to improve the quality of care in GI bleeding, with six principle recommendations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

β-decay feeding intensity distributions of 71,73 Ni

This paper presents the β-decay feeding intensity distribution and Gamow-Teller transition strength distribution of 71,73 Ni. These quantities were measured using the technique of total absorption spectroscopy at the National Superconducting Cyclotron Laboratory with the Summing NaI(Tl) detector. These measurements provide sensitive constraints to theoretical models used to predict β-decay properties far from stability for astrophysical applications. Specifically, for the astrophysical r process, the majority of the involved nuclei are not accessible by current facilities, and the nuclear input is mainly provided by theory. Furthermore, the present work reports on two neutron-rich nickel isotopes in the region where the weak r process is expected to be relevant in stellar nucleosynthesis. The experimental results are compared to two theoretical models, namely the shell model and the quasiparticle random-phase approximation, to help further refine theoretical calculations and aid in future r-process studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Understanding the Role of π-Conjugated Polymers as Binders in Enabling Designs for High-Energy/High-Rate Lithium Metal Batteries

Developing lithium-ion batteries with both high specific energy and high-power capability is a challenging task because of the necessity for meeting conflicting design requirements. We show that high-energy and high-rate capability can be achieved by using various π -conjugated p-dopable polymers as binders at the cathode and by lowering the mass fraction of all the inactive components of the cell. We report a lithium-metal battery that can deliver 320 Wh kg −1 at C/2 using a mass-efficient cell design. To this end, three conducting polymers with different ionic and electronic conductivities have been studied; dihexyl-substituted poly(3,4-propylenedioxythiophene) (PProDOT-Hx 2 ), poly(3-hexylthiophene) (P3HT), and a new Random Copolymer (Hex:OE)(80:20) PProDOT. These conducting polymers are compared against a conventional polymer binder, PVDF. We show that under the mass-efficient conditions required for achieving high specific energy and rate capability, the conducting polymers play a crucial role by providing electronic and ionic conductivity, protection against rapid growth of solid electrolyte interphase (SEI), and access to a large electrochemically active surface area. Thus, the use of conducting polymers with appropriate molecular structure as binders opens a viable pathway to maximizing the specific energy and rate capability of lithium-ion battery cathodes.

25 ENERGY STORAGE↗

DOE OSTI2022

Leaf gas exchange raw data, 2015 - 2017, at Manaus, Brazil

This data package contains raw leaf gas exchange data from the NGEE Tropics K34 tower site on a plateau near Manaus, Brazil. Data was collected using sensor and leaf sample measurements. Leaves on a target tree were chosen by accessing a branch near the tower. In some cases, the branch was naturally positioned near the tower and in other cases, a small rope was used to pull the branch closer to the tower for better access to leaves. Mature leaves were targeted in nearly all cases. The gas exchange system was hauled with a climbing rope to the level of the branch on the tower and the sensor head/leaf enclosure was installed near the branch of interest using a magic arm. We measured leaf gas exchange from 5:00 AM to 5:00 PM, randomly cycling through the approximately 20 leaves in the targeted branch(es). Data were collected over two time periods, detailed within the files. The attached data files contain raw data, sensor manuals, and PDFs with detailed methods and procedures separated into multiple folders. Data is in Excel file format. See data references for data package containing related metadata. This dataset replaces the leaf gas exchange data of two retired packages, NGT0019 and NGT0040.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Tunable electron beam pulser for picoseconds stroboscopic microscopy in transmission electron microscopes

For two decades, time-resolved transmission electron microscopes (TEM) have relied on pulsed-laser photoemission to generate electron bunches to explore sub-microsecond to sub-picosecond dynamics. Despite the vast successes of photoemission time-resolved TEMs, laser-based systems are inherently complex, thus tend not to be turn-key. In this paper, we report on the successful retrofit of a commercial 200 keV TEM, without an external laser, capable of producing continuously tunable pulsed electron beams with repetition rates from 0.1 GHz up to 12 GHz and a tunable bunch length from tens of nanoseconds down to 10 ps. This innovation enables temporal access into previously inaccessible regimes: i.e., high repetition rate stroboscopic experiments. Combination of a pair of RF-driven traveling wave stripline elements, quadrupole magnets, and a variable beam aperture enables operation of the instrument in (1) continuous waveform (CW) mode as though the instrument was never modified (i.e. convention TEM operation mode, where the electrons from the emission cathode randomly arrive at the sample without resolvable time information), (2) stroboscopic (pump-probe) mode, and (3) pulsed beam mode for dose rate sensitive materials. In order to analyze the effect of a pulsed beam on image quality, we examined Au nanoparticles using bright field, high-resolution TEM imaging and selected area diffraction in both continuous and pulsed-beam mode. Furthermore, in comparison of conventional TEMs, the add-on beam pulser enables the observation of ultrafast dynamic behavior in materials that are reversible under synchronized excitation.

36 MATERIALS SCIENCE↗

DOE OSTI2025

The impact of curation errors in the PDBBind Database on machine learning predictions of protein–protein binding affinity

The PDBBind database has been widely utilized for the computational prediction of protein–protein binding affinities. While the accuracy of the PDBBind-curated equilibrium dissociation constants (K D ) has been reported for the protein–ligand subset of the PDBBind database, the curation accuracy has not been reported for the protein–protein subset. Here, we present a detailed manual analysis for the subset of PDBBind records with PubMed Central Open Access primary publications and find that ~19% of these records had K D values that were not supported by their primary publications. The impact of these putative curation errors on the machine learning-based prediction of K D from experimental protein–protein 3D structures was evaluated and correcting the curation errors improved the Pearson correlation coefficient between measured and random forest-predicted log 10 (K D ) values by ~8 percentage points. This finding underscores the importance of dataset accuracy for computational modelling and highlights the need for more stringent curation processes when extracting information from the scientific literature.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Spin-orbit exciton in a honeycomb lattice magnet CoTiO 3 : Revealing a link between magnetism in d - and f -electron systems

We carried out inelastic neutron scattering to study the spin-orbital (SO) exciton in a single crystal sample of CoTiO 3 as a function of temperature. CoTiO 3 is a honeycomb magnet with dominant XY-type magnetic interaction and an A-type antiferromagnetic order below T N ≈ 38 K. We found that the SO exciton becomes softer, but acquires a larger bandwidth in the paramagnetic phase, compared to that in the magnetically ordered phase. Moreover, an additional mode is only observed in the intermediate temperature range, as the sample is warmed up above the lowest accessible temperature below T N . Such an unusual temperature dependence observed in this material suggests that its ground states (an S eff = 1 2 doublet) and excited states multiplets are strongly coupled, and therefore cannot be treated independently, as often done in a pseudo-spin model. Furthermore, our observations can be explained by a multi-level theory within random phase approximation that explicitly takes into account both the ground and excited multiplets. The success of our theory, which is originally developed to explain temperature dependence of magnetic excitations in the rare-earth magnets, highlight the similarity between the magnetic excitations in rare-earth systems and those in transition metal systems with strong spin orbit coupling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRSDate not supplied

Black Hills Wildfires: Mapping Post-fire Conifer Regeneration using Snow-on Imagery

The 2000 Jasper Fire in the Black Hills of South Dakota was the largest wildfire to date in the region, burning over 83,000 acres of ponderosa pine forest. In collaboration with partners from the United States Forest Service (USFS) Black Hills Experimental Forest, USFS Rocky Mountain Research Station, and United States Geological Survey Geosciences and Environmental Change Science Center, we characterized post-fire forest regeneration within high-severity burn patches. We accomplished this by implementing novel conifer detection techniques using a snow index mask to create a winter, snow-on image composite from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data. We utilized 2015 USFS stem maps of field-observed regeneration plots and ocularly sampled additional reforestation sites planted in 2001–2013. In Google Earth Engine (GEE), the field data and imagery were used to train a Random Forest (RF) model. The RF model classified 2021 conifer regeneration density as low, medium, or high across the high-severity burn area with an overall accuracy of 81.3%. Approximately 45.9% of the high-severity burn had low or no regeneration (0-40 trees per acre) 20 years post-fire. Given our partners' desire to find easily accessible low conifer regeneration zones, we identified 4,079 acres of priority planting sites that were within 1,500 feet of roads, had not been planted previously, and were larger than 50 acres. This method supports the use of snow-on imagery as a successful technique to identify conifer regeneration.

Casey Menick↗

NASA NTRS2022

Black Hills Wildfires: Mapping Post-Fire Conifer Regeneration using Snow-On Imagery

Casey Menick↗

DOE OSTI2021

A New Data Analysis Technique for Determining Mix Parameters from HED Experiments

In designing, analyzing, and understanding high-energy-density (HED) physics experiments, including inertial confinement fusion (ICF) experiments, we must contend with the extension of hydrodynamics to new regimes where additional physics, such as radiation transport and nuclear reactions, become important and coupled to the dynamics. Our most sophisticated models and understanding are based in classical, low-energy physics, since that is what we have the easiest access to creating and diagnosing. To assess our extrapolation of that understanding to the HED regime will require comparable precision in experiments and measurements. This is particularly the important in the case of hydrodynamic turbulence — most experiments are designed with one or two dimensions of symmetry, but at small scales hydrodynamics is generically observed to crumple into a fine structure of apparently random, three-dimensional eddies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Sequence-dependent self-assembly of supramolecular nanofibers in periodic dynamic block copolymers

Block copolymers (BCPs) can spontaneously self-assemble into various nanostructured morphologies which enable their diverse applications in selective membranes, polymer electrolytes, and optoelectronics. To expand the range of nanostructures accessible to block copolymers, we designed dynamic block copolymers (DBCPs) that combine the phase separation of traditional block copolymers with the supramolecular self-assembly of periodic dynamic polymers. We demonstrate that DBCPs synthesized with a periodic block sequence self-assemble into high aspect ratio supramolecular nanofibers with well-ordered PEG and PDMS domains, in contrast to those synthesized with a random sequence which do not form nanofibers but have disordered morphologies. The periodicity of the block sequence ensures regular placement of dynamic bonds along the polymer chain, which enables stacking of the hydrogen bonding units into ordered 1D supramolecular nanofibers and delays the onset of terminal flow by up to 60 °C compared to the random block sequence. The hierarchically assembled supramolecular nanofibers display complex mechanical and thermal phase behavior arising from the interplay between phase separation of the dissimilar polymer backbones and supramolecular interactions between dynamic bonds. Despite identical bulk composition, the periodic DBCPs demonstrate ionic conductivity values over two orders of magnitude higher than their random counterparts due to the formation of well-ordered, interconnected, high aspect ratio ion-transporting PEG domains. In conclusion, these results highlight the potential for DBCPs as an emerging material platform to achieve advanced, self-assembled nanostructured morphologies.

36 MATERIALS SCIENCE↗