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At least 1,207 records · Page 67

Analysis of Selected Legacy 85 Kr Samples

Legacy samples composed of 85 Kr encapsulated in solid zeolite 5A material and five small metal tubes containing a mixture of the zeolite combined with a glass matrix resulting from hot isostatic pressing have been preserved. The samples were a result of krypton R&D encapsulation efforts in the late 1970s performed at the Idaho Chemical Processing Plant. These samples were shipped to Oak Ridge National Laboratory (ORNL) in mid-FY 2014. Upon receipt the outer shipping package was opened, and the inner package, removed and placed in a radiological hood. The individual capsules were double bagged as they were removed from the inner shipping pig and placed into individual glass sample bottles for further analysis. The five capsules were then x-ray imaged. Capsules 1 and 4 appear intact and to contain an amorphous mass within the capsules. Capsule 2 clearly shows the saw marks on the capsule and a quantity of loose pellet or bead-like material remaining in the capsule. Capsule 3 shows similar bead-like material within the intact capsule. Capsule 5 had been opened at an undetermined time in the past. The end of this capsule appears to have been cut off, and there are additional saw marks on the side of the capsule. X-ray tomography allowed the capsules to be viewed along the three axes. Of most interest was determining whether there was any residual material in the closed end of Capsule 5. The images confirmed the presence of residual material within this capsule. The material appears to be compacted but still retains some of the bead-like morphology. Based on the nondestructive analysis (NDA) results, a proposed path forward was formulated to advance this effort toward the original goals of understanding the effects of extended storage on the waste form and package. Based on the initial NDA and the fact that there are at least two breached samples, it was proposed that exploratory tests be conducted with the breached specimens before opening the three intact capsules. Portions of these would be analyzed to determine the fraction of krypton/xenon remaining in the matrix and the amount of rubidium remaining in the matrix. The inner surface of the breached capsules would be examined for corrosion. The materials contained in Capsules 2 and 5 have been examined. There appears to be a relatively uniform distribution of Kr and Rb throughout the pellets examined. The chemical composition of the pellets appears to be consistent with 5A molecular sieves. The material contained within Capsule 5 showed ~1 at. % lead. The origin of the Pb is currently indeterminate. X-ray diffraction analysis shows a significant shift from the 5A structure, most likely due to the Kr encapsulation / sintering process that occurred when the samples were made. The capsule walls were also examined and showed extensive corrosion throughout. Elemental mapping of the capsule material appeared consistent with carbon steel, while the weld material appeared consistent with a stainless steel. The interior surface of the capsule appeared to have a layer of material containing Al, Si, and Ca similar to the 5A molecular sieve. Analysis for Rb within the corrosion sites was inconclusive.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Engineering Ralstonia eutropha for Production of Isobutanol (IBT) Motor Fuel from Carbon Dioxide, Hydrogen, and Oxygen Project Final Report

This research project is a collaboration between the Sinskey laboratory at MIT and the Worden laboratory at Michigan State University. The goal of the project is to produce Isobutanol (IBT), a branched-chain alcohol that can serve as a drop-in transportation fuel, through the engineered microbial biosynthesis of Carbon Dioxide, Hydrogen, and Oxygen using a novel bioreactor. This final technical report presents the findings of both the biological engineering work at MIT that extended the native branched-chain amino acid pathway of the wild type Ralstonia eutropha H16 to perform this biosynthesis, as well as the unique design, modeling, and construction of a bioreactor for incompatible gasses at Michigan State that enabled the operational testing of the complete system. This 105 page technical report summarizing the three years of research includes 72 figures and 11 tables of findings. Ralstonia eutropha (also known as Cupriavidus necator) is a Gram-negative, facultatively chemolithoautotrophic bacteria. It has been the principle organism used for the study of polyhydroxybutyrate (PHB) polymer biosynthesis. The wild-type Ralstonia eutropha H16 produces PHB as an intracellular carbon storage material while under nutrient stress in the presence of excess carbon. Under this stress, it can accumulate approximately 80 % of its cell dry weight (CDW) as this intracellular polymer. With the restoration of the required nutrients, the cells are then able to catabolize this polymer. If extracted from the cell, this PHB polymer can be processed into biodegradable and biocompatible plastics, however for this research, it is the efficient metabolic pathway channeling the captured carbon that is of interest. R. eutropha is further unique in that it contains two carbon-fixation Calvin–Benson–Bassham cycle operons, two oxygen-tolerant hydrogenases, and several formate dehydrogenases. It has also been much studied for its ability in the presence of oxygen, to fix carbon dioxide into complex cellular molecules using the energy from hydrogen. In this research project, engineered strains of R. eutropha redirected the excess carbon from PHB storage into the production of isobutanol and 3-methyl-1-butanol (branched-chain higher alcohols). These branched-chain higher alcohols can be used directly as substitutes for fossil-based fuels and are seen as alternative biofuels to ethanol and biodiesel. Importantly, these alcohols have approximately 98 % of the energy content of gasoline, 17 % higher than the current gasoline additive ethanol, without impacting corn market production for feed or food. Unlike ethanol, these branched-chain alcohols have low vapor pressure, hygroscopicity, and water solubility, which make them readily compatible with the existing pipelines, gasoline pumps, and engines in our transportation infrastructure. While the use of alternative energies from solar, wind, geothermal, and hydroelectric has spread for stationary power applications, these energy sources cannot be effectively or efficiently employed in current or future transportation systems. With the ongoing concerns of fossil fuel availability and price stability over the long term, alternative biofuels like branched-chain higher alcohols hold promise as a suitable transportation fuel in the future. We showed in our research that various mutant strains of R. eutropha with isobutyraldehyde dehydrogenase activity, in combination with the overexpression of plasmid-borne, native branched-chain amino acid biosynthesis pathway genes and the overexpression of heterologous ketoisovalerate decarboxylase gene, would produce isobutanol and 3-methyl-1-butanol when initiated during nitrogen or phosphorus limitation. Early on, we isolated one mutant R. eutropha strain which produced over 180 mg/L branched-chain alcohols in flask culture while being more tolerant of isobutanol toxicity. After the targeted elimination of genes encoding several potential carbon sinks (ilvE, bkdAB, and aceE), the production titer of the improved to 270 mg/L isobutanol and 40 mg/L 3-methyl-1-butanol. Semicontinuous flask cultivation supplied the cells with sufficient nutrients while minimizing the toxicity caused by isobutanol. Under this cultivation, the R. eutropha mutant grew and produced more than 14 g/L branched-chain alcohols over the duration of 50 days. These results demonstrate that R. eutropha carbon flux can be redirected from PHB to branched-chain alcohols and that engineered R. eutropha can be cultivated over prolonged periods of time for product biosynthesis. While this bioengineering work was being done at the Sinskey laboratory at MIT, the researchers at the Worden laboratory at Michigan State were working on the design and construction of the required specialty bioreactor for incompatible gasses (BIG) that would allow the safe feeding of microbes on Carbon Dioxide, Hydrogen, and Oxygen without explosive results. The early design and assembly work in year 1 incorporated a novel microbubble generator to maximize the bioavailability of gasses within the system comprised of small scale hollow fiber reactors. The early success of the microbubble generator eliminated the need to investigate potentially toxic surfactants within the system. For operational control, the system design incorporated a Opto22-based control network. The researchers also selected the specific hollow fiber material suitable for the bioreactor application. A variety of commercially available hollow fiber membranes were compared with regard to their pore sizes, cell affinity, and potential interference to cell viability assays. The selected membrane with its spongy layer was then tested for diffusivity of O2 and CO2. The instrumented system was then fully assembled for experimentally measuring the heterotrophic growth rate of immobilized R. eutropha cells. The requisite procedures for inoculation, measurement, and cleaning were established enabling the system performance to be validated under controlled laboratory conditions. In year 2, the researchers completed the Opto22 based cross-platform control network, and the system’s communications across the Sartorius fermentation system and Bruker gas chromatograph was established via open platform communications (OPC) protocol. Using the revised system, measurements were taken of the R.eutropha cell growth rate and substrate mass transfer rate in the hollow fiber membrane. Several IBT recovery strategies were explored and resin adsorption was determined to be optimal solution for lab scale operations. The adsorption capacity of the resin column was then measured and IBT desorption using methanol has been demonstrated. With the growing body of experimental data in hand, mathematical models were constructed to demonstrate and map the cellular kinetics, mass transfer of heterotrophic and autotrophic substrates in the hollow fiber, and the adsorption process in the resin column. A structured kinetic model was constructed to describe the competition between cell mass generation and IBT production. The reactor was then scaled up from single fiber to a membrane area of 180 cm2 and then further to 1 ft2. In Year 3 of the research, the IBT mass transfer across the membrane was characterized within the system with experiments to empirically measure the IBT diffusion coefficient in the BIG spongy layer. Using the refined mathematical models, the researchers are now able to explain the experimental observations and predict bioreactor performance under a wide range of experimental conditions. The Big system is able to demonstrate continuous controlled operations with the integrated IBT recovery system. Both heterotrophic and autotrophic production have been shown during continuous operation with heterotrophic and autotrophic stages. Performance of BIG system has been measured during continuous run with alternating heterotrophic growth on fructose and autotrophic product formation on H2, CO2, and O2. Volumetric productivities of IBT at 325 mg/(L day) and of 3M1B at 50 mg/(L day) were achieved, which were comparable to that achieved under heterotrophic conditions. Using the mathematical model, researchers are able to predict system performance for scaled-up BIG system. The apparent diffusion coefficient of IBT in the spongy layer of XM-50 hollow fiber membranes has been measured at various lumen liquid flow rates. The experiment is simulated in COMSOL to validate the results. The constructed COMSOL model is able to simulate BIG system performance in both batch and continuous mode. Mathematical simulations of the system performance have been run to identify the most crucial operational conditions, identifying the rate-limiting factors in autotrophic production of IBT, and quantitating the rate of IBT catabolism. Investigations of the productivity of the production system have suggested and the modeling of the system has revealed a particular sensitivity to the catabolism of the produced IBT by the engineered R. eutropha. Experiments have been designed and executed to quantify the IBT catabolism of R. eutropha, which open up possibilities for further system improvements through future, targeted bioengineering of the strain. Finally, the researchers at Michigan State performed an economic analysis of the system, based on the collective results, and their findings are presented in full within the report.

08 HYDROGEN↗

Plasma-enhanced chemical vapor deposition of graphene on copper substrates

A plasma enhanced vapor deposition process is used to synthesize graphene from a hydrogen/methane gas mixture on copper samples. The graphene samples were transferred onto SiO{sub 2} substrates and characterized by Raman spectroscopic mapping and atomic force microscope topographical mapping. Analysis of the Raman bands shows that the deposited graphene is clearly SLG and that the sheets are deposited on large areas of several mm{sup 2}. The defect density in the graphene sheets is calculated using Raman measurements and the influence of the process pressure on the defect density is measured. Furthermore the origin of these defects is discussed with respect to the process parameters and hence the plasma environment.

36 MATERIALS SCIENCE↗

Automated Model for Improved Mapping of Country-Scale High-Resolution Coastal Bathymetry

Accurate and up-to-date maps of coastal bathymetry are critical for a variety of sectors from vessel navigation to port construction and are increasingly vital to inform coastal infrastructure management amid accelerating sea-level rise and more frequent and severe storm-surge events. The primary challenges to accurate and efficient bathymetric mapping from optical remote sensing are: accurately modeling light attenuation in both the atmosphere and water column; and inefficient data processing pipelines for highresolution satellite imagery. To address the effects of light attenuation within the water-column we have developed a novel physics-based bathymetry model that accounts for variations in water-column inherent optical properties on a pixel-by-pixel basis in optically-shallow aquatic environments, which represents a major advancement. For applications to satellite imagery, we have developed a software package that automatically applies the robust 6S atmospheric correction algorithm, estimates the bottom depth from the physics-based bathymetry model, which corrects for attenuation by suspended particulate matter and colored dissolved organic matter in the water column on a pixel-by-pixel basis, and leverages highperformance computing for rapid application to region-scale (e.g., CONUS) 2-meter resolution imagery datasets. Our approach is tailored to sensors that collect data at two-meter resolution with high return times for frequent updates. We mapped 591 WorldView satellite images for Florida, North Carolina, and Alaska and validated the maps against LiDAR-derived bathymetry data. Results show median RMSE of 1.75, 1.59, and 2.67 meters, respectively. By combining the strengths of Oak Ridge National Laboratory in high-performance computing and remote-sensing science with the water-column modeling expertise of Scripps Institution of Oceanography we advance the state of bathymetric mapping capability.

54 ENVIRONMENTAL SCIENCES↗

A Multi-Fidelity Gaussian Process Regression Method for Probabilistic Wind Farm Power Curve Estimation

Accurate estimation of the power curve for wind turbines or wind farms is crucial to ensure their efficient operation and management. However, conventional methods for power curve estimation rely either on expensive and infrequent measurements or on low-quality numerical simulations. Moreover, the majority of previous studies on power curve estimation for wind turbines or wind farms focused on deterministic estimation, which provides a point estimate of the relationship between wind speed and power generation. Nevertheless, the deterministic approach fails to consider the inherent uncertainty associated with wind energy production resulting from varying turbine characteristics. This can lead to inaccurate power generation estimation and suboptimal decisions regarding energy management. In this paper, a kernel density estimation (KDE) based Multi-Fidelity Gaussian Process Regression (MFGPR) model is proposed to fuse theoretical power curve data and the ground true measurements to create a mapping of wind speed and wind power. By conducting a case study on an actual wind farm in China, the efficacy of the proposed MFGPR model was demonstrated in characterizing the variability of wind power. The probabilistic MFGPR model was also able to generate confidence intervals that encompassed the measured power, thereby improving the accuracy and confidence in wind power estimation or wind resource assessment. Overall, the proposed MFGPR model offers a reliable approach to integrate high-fidelity ground measurements and theoretical power curve data, resulting in precise wind resource assessment and power estimation.

Gaussian process regression↗

Raptor

Raptor is an efficient Python-based tool for predicting the formation and morphology of stochastic lack of fusion defects in metal AM processes. A major obstacle for the qualification and certification of additively manufactured parts in critical applications continues to be performance variability caused in part by porosity-related defects. High-fidelity process models that could predict these defect features are currently too computationally expensive for component-level analysis. To address this, Raptor employs a high-performance geometric method to model the dynamic melt pool rather than relying on computationally intensive thermal fluid dynamics. This allows Raptor to rapidly identify regions of unmelted material that correspond to lack of fusion pores. The efficiency of this approach significantly reduces the time and resources needed for generating 3D defect predictions, which enables users to conduct large-scale parameter studies and evaluate how process variations affect part quality. The framework offers operational flexibility; users can execute simulations through a simple command line interface or integrate core functions as a library within larger computational workflows. Simulation outputs include 3D porosity maps for visualization and tools for quantitative morphological analysis. These results are suitable for direct comparison with experimental characterization data from methods such as X-ray computed tomography and can be used for statistical process optimization.

Subraveti, Vamsi [Vanderbilt Univ., Nashville, TN ↗

Mapping Hsp104 interactions using cross‐linking mass spectrometry

Molecular machines from the AAA+ (ATPases Associated with diverse cellular Activity) superfamily of protein disaggregases play important roles in protein folding, disaggregation and DNA processing. Recent cryo-EM structures of AAA+ molecular machines have uncovered nuanced changes in their conformation that underlie their specialized functions. Structural knowledge of these molecular machines in complex with substrates begins to explain their mechanism of activity. Here, we explore how cross-linking mass spectrometry (XL-MS) can be used to interpret changes in conformation induced by ATP in Hsp104 and how a substrate may interact with Hsp104. We applied a panel of cross-linking reagents to produce cross-linking maps of Hsp104 and interpret our data on previously determined X-ray and cryo-EM structures of Hsp104 from a thermophilic yeast, Calcarisporiella thermophila. We developed an analysis pipeline to differentiate between intra-subunit and inter-subunit contacts within the hexameric homo-oligomer. We identify cross-links that break the asymmetry that is present in Hsp104 in an ATP-hydrolysis competent conformation but is absent in an ATP-hydrolysis-defective mutant. Finally, we identify contacts between Hsp104 and a selected protein (proprotein convertase subtilisin/kexin type 9 PCSK9) to reveal contacts on the central channel of Hsp104 across the length of this protein indicating that we might have trapped interactions consistent with its translocation. Our simple and robust XL-MS-based experiments and methods help interpret how these molecular machines change conformation and bind to other proteins even in the context of homo-oligomeric assemblies enabling coupling state-of-the-art modeling approaches with XL-MS.

60 APPLIED LIFE SCIENCES↗

THE HERSCHEL INVENTORY OF THE AGENTS OF GALAXY EVOLUTION IN THE MAGELLANIC CLOUDS, A HERSCHEL OPEN TIME KEY PROGRAM

We present an overview of the HERschel Inventory of The Agents of Galaxy Evolution (HERITAGE) in the Magellanic Clouds project, which is a Herschel Space Observatory open time key program. We mapped the Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC) at 100, 160, 250, 350, and 500 {mu}m with the Spectral and Photometric Imaging Receiver (SPIRE) and Photodetector Array Camera and Spectrometer (PACS) instruments on board Herschel using the SPIRE/PACS parallel mode. The overriding science goal of HERITAGE is to study the life cycle of matter as traced by dust in the LMC and SMC. The far-infrared and submillimeter emission is an effective tracer of the interstellar medium (ISM) dust, the most deeply embedded young stellar objects (YSOs), and the dust ejected by the most massive stars. We describe in detail the data processing, particularly for the PACS data, which required some custom steps because of the large angular extent of a single observational unit and overall the large amount of data to be processed as an ensemble. We report total global fluxes for the LMC and SMC and demonstrate their agreement with measurements by prior missions. The HERITAGE maps of the LMC and SMC are dominated by the ISM dust emission and bear most resemblance to the tracers of ISM gas rather than the stellar content of the galaxies. We describe the point source extraction processing and the criteria used to establish a catalog for each waveband for the HERITAGE program. The 250 {mu}m band is the most sensitive and the source catalogs for this band have {approx}25,000 objects for the LMC and {approx}5500 objects for the SMC. These data enable studies of ISM dust properties, submillimeter excess dust emission, dust-to-gas ratio, Class 0 YSO candidates, dusty massive evolved stars, supernova remnants (including SN1987A), H II regions, and dust evolution in the LMC and SMC. All images and catalogs are delivered to the Herschel Science Center as part of the community support aspects of the project. These HERITAGE images and catalogs provide an excellent basis for future research and follow up with other facilities.

79 ASTRONOMY AND ASTROPHYSICS↗

Revisiting solidification microstructure selection maps in the frame of additive manufacturing

Understanding microstructural development in additive manufacturing under highly non-equilibrium cooling conditions and the consequent effects on mechanical properties of the final component is critical for accelerating industrial adoption of these manufacturing techniques. In this study, simple but effective theoretical solidification models are recalled to evaluate their ability to predict of microstructural features in additive manufacturing applications. As a case study, the resulting solidification microstructure selection maps are created to predict the stable growth modality and the columnar to equiaxed transition (CET) of an Al-10Si-0.5Mg alloy processed via Selective Laser Melting. The potential of this method in microstructural predictions for additively manufactured products, as well as outstanding challenges and limitations, are discussed.

36 MATERIALS SCIENCE↗

Ligand placement based on prior structures: the guided ligand-replacement method

A new module, Guided Ligand Replacement (GLR), has been developed in Phenix to increase the ease and success rate of ligand placement when prior protein-ligand complexes are available. The process of iterative structure-based drug design involves the X-ray crystal structure determination of upwards of 100 ligands with the same general scaffold (i.e. chemotype) complexed with very similar, if not identical, protein targets. In conjunction with insights from computational models and assays, this collection of crystal structures is analyzed to improve potency, to achieve better selectivity and to reduce liabilities such as absorption, distribution, metabolism, excretion and toxicology. Current methods for modeling ligands into electron-density maps typically do not utilize information on how similar ligands bound in related structures. Even if the electron density is of sufficient quality and resolution to allow de novo placement, the process can take considerable time as the size, complexity and torsional degrees of freedom of the ligands increase. A new module, Guided Ligand Replacement (GLR), was developed in Phenix to increase the ease and success rate of ligand placement when prior protein–ligand complexes are available. At the heart of GLR is an algorithm based on graph theory that associates atoms in the target ligand with analogous atoms in the reference ligand. Based on this correspondence, a set of coordinates is generated for the target ligand. GLR is especially useful in two situations: (i) modeling a series of large, flexible, complicated or macrocyclic ligands in successive structures and (ii) modeling ligands as part of a refinement pipeline that can automatically select a reference structure. Even in those cases for which no reference structure is available, if there are multiple copies of the bound ligand per asymmetric unit GLR offers an efficient way to complete the model after the first ligand has been placed. In all of these applications, GLR leverages prior knowledge from earlier structures to facilitate ligand placement in the current structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The RNAi machinery controls distinct responses to environmental signals in the basal fungus Mucor circinelloides

Here, RNA interference (RNAi) is a conserved mechanism of genome defence that can also have a role in the regulation of endogenous functions through endogenous small RNAs (esRNAs). In fungi, knowledge of the functions regulated by esRNAs has been hampered by lack of clear phenotypes in most mutants affected in the RNAi machinery. Mutants of Mucor circinelloides affected in RNAi genes show defects in physiological and developmental processes, thus making Mucor an outstanding fungal model for studying endogenous functions regulated by RNAi. Some classes of Mucor esRNAs map to exons (ex-siRNAs) and regulate expression of the genes from which they derive. To have a broad picture of genes regulated by the silencing machinery during vegetative growth, we have sequenced and compared the mRNA profiles of mutants in the main RNAi genes by using RNA-seq. In addition, we have achieved a more complete phenotypic characterization of silencing mutants Deletion of any main RNAi gene provoked a deep impact in mRNA accumulation at exponential and stationary growth. Genes showing increased mRNA levels, as expected for direct ex-siRNAs targets, but also genes with decreased expression were detected, suggesting that, most probably, the initial ex-siRNA targets regulate the expression of other genes, which can be up- or down-regulated. Expression of 50% of the genes was dependent on more than one RNAi gene in agreement with the existence of several classes of ex-siRNAs produced by different combinations of RNAi proteins. These combinations of proteins have also been involved in the regulation of different cellular processes. Besides genes regulated by the canonical RNAi pathway, this analysis identified processes, such as growth at low pH and sexual interaction that are regulated by a dicer -independent non-canonical RNAi pathway. In conclusion, this work shows that the RNAi pathways play a relevant role in the regulation of a significant number of endogenous genes in M. circinelloides during exponential and stationary growth phases and opens up an important avenue for in-depth study of genes involved in the regulation of physiological and developmental processes in this fungal model.

59 BASIC BIOLOGICAL SCIENCES↗

Energetics at the Surface: Direct Optical Mapping of Core and Surface Electronic Structure in CdSe Quantum Dots Using Broadband Electronic Sum Frequency Generation Microspectroscopy

Understanding and controlling the electronic structure of nanomaterials is the key to tailoring their use in a wide range of practical applications. Despite this need, many important electronic states are invisible to conventional optical measurements and are typically identified indirectly based on their inferred impact on luminescence properties. This is especially common and important in the study of nanomaterial surfaces and their associated defects. Surface trap states play a crucial role in photophysical processes yet remain remarkably poorly understood. In this work we demonstrate for the first time that broadband electronic sum frequency generation (eSFG) microspectroscopy can directly map the optically bright and dark states of nanoparticles, including the elusive below gap states. This new approach is applied to model cadmium selenide (CdSe) quantum dots (QDs), where the energies of surface trap states have eluded direct optical characterization for decades. Our eSFG measurements show clear signatures of electronic transitions both above the band gap, which we assign to previously reported one- and two-photon transitions associated with the CdSe core, as well as broad spectral signatures below the band gap that are attributed to surface states. In addition to the core states, this analysis reveals two distinct distributions of below gap states, providing the first direct optical measurement of both shallow and deep surface states on this system. Lastly, chemical modification of the surfaces via oxidation results in the relative increase in the signals originating from the surface states. Overall, our eSFG experiments provide an avenue to directly map the entirety of the QD core and surface electronic structure, which is expected to open up opportunities to study how these materials are grown in situ and how surface states can be controlled to tune functionality.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Space- and Time-Resolved Mapping of Ionic Dynamic and Electroresistive Phenomena in Lateral Devices

A novel scanning probe microscopy (SPM) based technique for probing local ionic and electronic transport and their dynamic behavior on the 10 ms 10 s scale is presented. The time-resolved Kelvin Probe Force Microscopy (tr-KPFM) allows mapping surface potential in both space and time domains, visualizing electronic and ionic charge dynamics and separating underlying processes based on their time responses. Here, tr-KPFM is employed to explore the interplay of the adsorbed surface ions and bulk oxygen vacancies and their role in the resistive switching in the Ca-substituted bismuth ferrite thin film.

Ca-BFO↗

ON-OFF neuromorphic ISING machines using Fowler-Nordheim annealers

We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using a Fowler-Nordheim quantum mechanical tunneling based threshold-annealing process. The core component of NeuroSA consists of a pair of asynchronous ON-OFF neurons, which effectively map classical simulated annealing dynamics onto a network of integrate-and-fire neurons. The threshold of each ON-OFF neuron pair is adaptively adjusted by an FN annealer and the resulting spiking dynamics replicates the optimal escape mechanism and convergence of SA, particularly at low-temperatures. To validate the effectiveness of our neuromorphic Ising machine, we systematically solved benchmark combinatorial optimization problems such as MAX-CUT and Max Independent Set. Across multiple runs, NeuroSA consistently generates distribution of solutions that are concentrated around the state-of-the-art results (within 99%) or surpass the current state-of-the-art solutions for Max Independent Set benchmarks. Furthermore, NeuroSA is able to achieve these superior distributions without any graph-specific hyperparameter tuning. For practical illustration, we present results from an implementation of NeuroSA on the SpiNNaker2 platform, highlighting the feasibility of mapping our proposed architecture onto a standard neuromorphic accelerator platform.

42 ENGINEERING↗

Toward nanoscale molecular mass spectrometry imaging via physically constrained machine learning on co-registered multimodal data

Mass spectrometry imaging (MSI) plays a pivotal role in investigating the chemical nature of complex systems that underly our understanding in biology and medicine. Multiple fields of life science such as proteomics, lipidomics and metabolomics benefit from the ability to simultaneously identify molecules and pinpoint their distribution across a sample. However, achieving the necessary submicron spatial resolution to distinguish chemical differences between individual cells and generating intact molecular spectra is still a challenge with any single imaging approach. Here, we developed an approach that combines two MSI techniques, matrix-assisted laser desorption/ionization (MALDI) and time-of-flight secondary ion mass spectrometry (ToF-SIMS), one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The known relationships between the two MSI channels of information are enforced via a physically constrained machine-learning approach and directly incorporated in the data processing. We demonstrate the robustness of this method by generating intact molecular MALDI-type spectra and chemical maps at ToF-SIMS resolution when imaging mouse brain thin tissue sections. This approach can be readily adopted for other types of bioimaging where physical relationships between methods have to be considered to boost the confidence in the reconstruction product.

97 MATHEMATICS AND COMPUTING↗

ELEMENT DISTRIBUTIONS IN THE CRAB NEBULA

Images of the Crab Nebula have been obtained through custom interference filters that transmit emission from the expanding supernova remnant in He II {lambda}4686, H{beta}, He I {lambda}5876, [O I] {lambda}{lambda}6300, 6364, [N II] {lambda}{lambda}6548, 6583, [S II] {lambda}{lambda}6716, 6731, [S III] {lambda}9069, and [C I] {lambda}{lambda}9823, 9850. We present both raw and flux-calibrated emission-line images. Arrays of 19,440 photoionization models, with extensive input abundance ranges, were matched pixel by pixel to the calibrated data in order to derive corresponding element abundance or mass-fraction distributions for helium, carbon, nitrogen, oxygen, and sulfur. These maps show distinctive structure, and they illustrate regions of gas in which various stages of nucleosynthesis have apparently occurred, including the CNO cycle, helium burning, carbon burning, and oxygen burning. It is hoped that the calibrated observations and chemical abundance distribution maps will be useful for developing a better understanding of the precursor star evolution and the supernova explosive process.

79 ASTRONOMY AND ASTROPHYSICS↗

Simulation of radiation damping in rings, using stepwise ray-tracing methods

The ray-tracing code Zgoubi computes particle trajectories in arbitrary magnetic and/or electric field maps or analytical field models. It includes a built-in fitting procedure, spin tracking many Monte Carlo processes. The accuracy of the integration method makes it an efficient tool for multi-turn tracking in periodic machines. Energy loss by synchrotron radiation, based on Monte Carlo techniques, had been introduced in Zgoubi in the early 2000s for studies regarding the linear collider beam delivery system. However, only recently has this Monte Carlo tool been used for systematic beam dynamics and spin diffusion studies in rings, including eRHIC electron-ion collider project at the Brookhaven National Laboratory. Some beam dynamics aspects of this recent use of Zgoubi capabilities, including considerations of accuracy as well as further benchmarking in the presence of synchrotron radiation in rings, are reported here.

43 PARTICLE ACCELERATORS↗

Contributions to cosmic reionization from dark matter annihilation and decay

Dark matter annihilation or decay could have a significant impact on the ionization and thermal history of the universe. In this paper, we study the potential contribution of dark matter annihilation (s-wave- or p-wave-dominated) or decay to cosmic reionization, via the production of electrons, positrons and photons. We map out the possible perturbations to the ionization and thermal histories of the universe due to dark matter processes, over a broad range of velocity-averaged annihilation cross sections/decay lifetimes and dark matter masses. We have employed recent numerical studies of the efficiency with which annihilation/decay products induce heating and ionization in the intergalactic medium, and in this work extended them down to a redshift of 1 + z = 4 for two different reionization scenarios.We also improve on earlier studies by using the results of detailed structure formation models of dark matter haloes and subhaloes that are consistent with up-to-date N-body simulations, with estimates on the uncertainties that originate from the smallest scales.We find that for dark matter models that are consistent with experimental constraints, a contribution of more than 10% to the ionization fraction at reionization is disallowed for all annihilation scenarios. Such a contribution is possible only for decays into electron/positron pairs, for light dark matter with mass m χ ≲ 100 MeV, and a decay lifetime τ χ ~ 10 24 –10 25 s.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗