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At least 487 records · Page 27

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

High-Energy Solid-State Lithium Batteries with Organic Cathode Materials (Final Report)

Organic materials made from abundant elements via low-energy processes are emerging as sustainable and low-cost alternatives to transition metal oxides as the electrode materials for high- energy batteries in the wake of supply chain and environmental issues associated with critical materials during the transition to clean energy. Organic insertion materials (OIMs) offer material- level energy comparable to transition metal oxides, but they have durability difficulties owing to dissolving in common liquid electrolytes. Combining ceramic-based solid electrolytes with organic electrode materials is one intriguing solution. The goal of this project is to design and synthesize high-energy OIMs, to understand the chemical dynamics and mechanical properties at the OIM-sulfide interface during electrochemical cycling, and to develop methods for constructing the optimum cathode microstructure, which will lead to improved electrochemical performance. The project team has accomplished the following over the last four years: (a) demonstrating that the mechanical softness of organic electrode materials is uniquely beneficial in suppressing crack formation at the electrode-electrolyte interface during cell operation; (b) understanding the interaction between cathode microstructure and the mechanical properties of individual components; and (c) establishing predictive control of cathode microstructure by tuning the mechanical properties of solid electrolytes and OIMs; (d) determining the chemical combability of sulfide electrolyte with high-energy OIMs and finally (f) laying out a road map toward a specific energy of 500 Wh kg -1 for solid-state lithium batteries. 14 publications resulted from this project.

25 ENERGY STORAGE↗

CRADA Number NFE-19-07859 with Purist, Inc. (CRADA Final Report)

Cooperative Research and Development Agreement (CRADA) NFE-19-07859 between Oak Ridge National Laboratory (ORNL) and Purist Inc. (Purist) focused on developing a technology for production of high purity radioisotopes using small-scale underutilized research nuclear reactors. Purist is developing a novel production mechanism that will produce, and efficiently isolate radioisotopes with high specific activity at small-scale research reactors. The goal of this technology is to enable underutilized smaller scale reactors, typically not capable of producing medical grade radioisotopes, to be utilized as a production supply source. Such radioisotope production facilities will complement production efforts of the few larger production facilities to reduce and prevent risk in the medical isotope supply chain. The work done under this CRADA explored target development, to maximize isotope production and separation using Purist’s technology to ultimately obtain a radioisotope product with high specific activity for use in medical applications. Furthermore, under this CRADA post production, capture, concentration and encapsulation of the radioisotope product was studied by developing post irradiation midi to microscale processes to capture, store and release the separated radioisotopes from large volumes of the capture matrix after production, via automated High-Pressure Ion Chromatography (HPIC) and microfluidic purification/separation systems. This will enable concentration of the radioisotope product obtained into small volumes, which will aid in packaging and transporting the final radioisotope product to users.

07 ISOTOPE AND RADIATION SOURCES↗

Low-Temperature Plasma-Based Metrology of Lithium-Ion Battery Electrode Materials (CRADA Final Report)

As part of the Cyclotron Road program, SirenOpt Inc. evaluated its low-temperature plasma-based metrology sensor prototype for measuring multiple critical properties of lithium-ion battery electrode materials in parallel and in real-time. Cost-effective, minimal-waste manufacturing of high-performance battery electrode materials will be vital for achieving society’s net-zero carbon emission goals. Because existing electrode metrology sensors cannot operate within most sections of manufacturing lines, manufacturers often complete hundreds of processing steps before they can test their products and detect problems. When manufacturers perform these offline tests, they typically only test a small portion of the manufactured products. Current electrode manufacturing thus often yields many low-quality products, or off-spec products that must be thrown away all together. For example, at least 6% of the total lithium-ion battery manufacturing cost (i.e., over $250 million/year for the average gigafactory) is devoted to processing defective electrodes that are not scrapped until performance tests are failed during late-stage quality control checks. Electrode variability also leads manufacturers to build extra cells into battery packs to reduce the risk of poor performance. For example, many electric vehicle (EV) manufacturers include up to 10% more cells than needed, which substantially increases the cost and weight of the final EV product. The SirenOpt sensor can potentially enable early detection of poorly manufactured electrodes and allow them to be removed earlier from manufacturing lines, which can save battery manufacturers (hundreds of) millions of dollars per year. The sensor can further be used to improve product quality by accelerating R&D and process optimization, improving quality control, and enabling real-time process control. Overall, a real-time, in-situ metrology strategy can create unprecedented opportunities for implementation of smart manufacturing practices and advanced quality and process control solutions to realize higher battery electrode throughput and performance.

25 ENERGY STORAGE↗

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗

Development and implementation of high-throughput proteomic and metabolomics assays by using advanced chromatographic and mass spectrometric systems (CRADA Final Report)

The mission of this CRADA with Agilent was to couple powerful MS platforms (QQQ, IM-QTOFMS) with Agilent’s novel Ultra-High-Performance Liquid Chromatography (UHPLC) fast metabolomic workflows and perform ABF Machine Learning (ML) to generated datasets. Agilent transferred UHPLC methods to PNNL and LBNL and methods were implemented and demonstrated in both labs, achieving total acquisition times of < 10 min. Metabolites analyzed using Agilent’s shared methods included metabolites from central carbon metabolism, common across hosts, and metabolites unique to engineered strains. Standards were acquired in an UHPLC-Drift Tube Ion Mobility Mass Spectrometer (DTIMS) system for the first time within the context of ABF and methods were optimized based on Agilent’s protocols. Samples from ABF hosts Pseudomonas putida, Aspergillus pseudoterreus, Aspergillus niger and Rhodosporidium toruloides were analyzed using the UHPLC-DTIMS platform for a total of 276 runs. A data analysis workflow compatible with the Experimental Data Depot (EDD) and completely shareable was developed for the acquired UHPLC-DTIMS data. Samples were analyzed using a Data Independent Acquisition Approach (DIA), which for most of the standards provided more transitions therefore increasing detection confidence. Using the data acquired by PNNL, LBNL, and Agilent’s specifications from previous ML projects, SNL applied an ensemble ML strategy to pick the best performing model for automated LC-method selection. Finally, with the contribution of the participant labs and Agilent, SNL developed an Automated Method Selection (AMS) software tool to predict the best liquid chromatography method for analysis of any new molecules of interest. Samples with novel pathways and new metabolite targets of interest are generated at a high pace in the ABF. Overall, the project advanced rapid metabolomics by combining liquid chromatography, ion mobility spectrometry, and data-independent mass spectrometry with machine learning. This multidimensional approach uses retention time, collision cross-section, precursor mass, and fragment-ion information to distinguish chemically similar metabolites that can be difficult to resolve using conventional liquid- or gas-chromatography methods. The resulting workflow also provided automated metabolite-identification error estimates, addressing a recognized need for statistical confidence measures in metabolomics.

Petzold, Christopher [Lawrence Berkeley National L↗

Fire, dust, air and water: Improving aerosol biogeochemistry interactions in ACME. Final report

Aerosol-biogeochemistry interactions will have important consequences for human health, ecosystem services, and climate feedbacks over the next several decades. In this proposal we seek to link how human activities on land, including direct industrial emissions and landscape fires, impact the atmosphere and the biogeochemistry of the ocean and land. Our overall goal was to complement existing work at DOE labs to improve the capability and performance of the E3SM model in short-term, high-resolution projections of climate. Projections of ocean uptake of anthropogenic carbon are highly dependent on the details of the ocean physical and biogeochemistry parameterizations. Potentially equally important are the estimates of increases in iron and soluble nitrogen deposition in aerosols to the open ocean, but there are substantial uncertainties in these feedbacks. The E3SM land model simulates natural and anthropogenic fires, but improvement is needed to more accurately simulate fire responses to climate variability as well as fire contributions to terrestrial climate feedbacks. This proposal addressed four of the six priorities within the ACME/E3SM call by improving the representation of fire, industrial combustion sources, and desert dust and adding iron and soluble iron to the atmospheric chemistry (1). Our work focused on improving ocean biogeochemistry and the response of the oceans to anthropogenic atmospheric iron and nitrogen (3). We also improved the representation of land disturbance on fires and fire mediated carbon cycle feedbacks in the land model (4). Finally we had planned to couple the land, atmosphere and ocean biogeochemical systems (6) and explore how this coupling changes the feedbacks in the climate system. Our work under this proposal was separated into the following 5 tasks: i) improve representation of fire dynamics in both boreal and tropical ecosystems, ii) improve estimates of industrial emissions of iron and phosphorus, iii) improve representation of atmospheric iron, phosphorus and nitrogen transport, chemistry and deposition, iv) improve representation of iron, phosphorus and nitrogen deposition impacts on ocean biogeochemistry, and v) couple emissions into atmosphere, to deposition onto land and ocean biogeochemistry. For all 5 tasks, we conducted offline experiments of the historical period to enable comparison with available aerosol and land surface observations. We had planned to conduct fully coupled simulations, however, these will be conducted as part of the coupling in version 3 and 4 of the E3SM model, and thus have not been completed.

54 ENVIRONMENTAL SCIENCES↗

Defining the Minimal Set of Microbial Genes Required for Valorization of Lignin Biomass (Final Report)

Project Goals: Lignin is the second most abundant biopolymer on earth and represents a critically underutilized biomass resource for hydrocarbon feedstocks. Despite substantial effort, there is still no efficient process to convert lignin to useable carbon-based platform chemicals and materials. The goal of this project is identify a minimal set of microbial enzymes necessary for lignin breakdown and sufficient for the synthesis of valuable chemical intermediates from lignin isolated as a byproduct of lignocellulosic ethanol production. These genes will be then used to engineer functional whole cell biocatalysts for tunable lignin metabolism. To date, although a number of enzymes have been associated with lignin degradation, most have been tested in isolation (as individual enzymes) and on drastically different substrates -- often dyes that are not related to lignin. In contrast, lignin utilization in nature likely occurs by microbial consortia with multiple enzymes acting synergistically. We propose to examine two separate stages of lignin breakdown carried out by the microbes that do it best: (1) early breakdown of native polymeric lignin into soluble fragments by a set of sequenced wood-rotting fungal species, and (2) downstream metabolism of these soluble lignin fragments to useful chemical intermediates by a panel of sequenced soil saprophytes. Our approach involves testing sets of genes that will be assayed combinatorially in the context of a heterologous expression host. The resulting engineered strains will be systematically assayed using soluble lignin fragments, synthetic defined polymeric lignin, and finally lignin directly sourced from lignocellulosic processing streams. In addition to resulting in a functional whole cell biocatalyst for lignin utilization, we anticipate that this approach will allow us to address key unanswered questions about lignin metabolism in nature, including: (1) Why does the Trametes versicolor genome contain 25 different class II peroxidases? (2) What is the role of laccases in lignin metabolism? Why do some aggressive lignin degraders have many laccases (e.g. >7 in T. versicolor) while others have none (e.g. P. chrysosporium)? (3) How is peroxide provided in a controlled manner to drive peroxidase activity without causing the enzyme inhibition that is so often observed in vitro? (4) What strategies do microbial lignin degraders use to avoid the problem of repolymerization during active lignin degradation? and (5) Can microbial lignin metabolism be diverted for high level production of defined aromatics? A final critical question is whether combining key minimal sets of enzymes from a wide range of organisms will result in engineered strains capable of highly efficient, streamlined pathways for lignin utilization that can be tuned for a specific carbon output. This effort will leverage DOE investments in microbial genome sequencing, and secure a critical channel for lignin biomass utilization that will also help to render lignocellulosic a viable feedstock for the production of renewable liquid biofuels.

59 BASIC BIOLOGICAL SCIENCES↗

Safeguards by Design Projects (FY2020 Final Report)

This University Engagement project challenged engineering students at universities, that do not have Bachelor degrees in nuclear engineering but do have research reactors and some nuclear engineering coursework, to incorporate Safeguards by Design concepts into their Senior Capstone Design Project. This University Engagement project was part of the U. S. Department of Energy’s (DOE) National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation, Office of International Nuclear Safeguards, Next Generation Safeguards Initiative, Human Capital Development: University Engagement Program. This program exposed university students with Mechanical Engineering majors and Nuclear Engineering minors to the concepts of international nuclear safeguards. FY20, three teams at the University of Rhode Island and one team at the University of Texas - Austin participated in researching, designing, building, and testing projects to support international nuclear safeguards measurements or verification. The projects involved engaging in activities at the university’s research reactors. All the projects engaged students with prototyping a design and/or tool for application at the Universities’ reactor. At the end of the course, most of the students expressed the experience was a positive and they learned more about international nuclear safeguards and applying requirements than they had previously encountered. This school year the projects were further complicated by the COVID-19 pandemic. Both universities cancelled in class room classes, and limited direct student/professor interactions. Furthermore, Los Alamos National Laboratory (LANL) greatly restricted travel, therefore making it impossible to visit the students at the end of the semester for the review of their design projects. The final design and review meeting for the projects happened via the internet. Additionally, while the teams planned to build prototypes this did not happen since there was a social distancing ban on students meeting in person.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Project 18-15263 X-ray Studies of Interfacial Molecular Complexes in ALSEP Back-Extraction (Research Performance Final Report)

The objective of the project was to use synchrotron X-rays to measure the molecular-scale organization of extractants, complexants, buffers, and metal ions at the organic-aqueous (liquid-liquid) interface during solvent back-extraction under conditions relevant to ALSEP (Actinide-Lanthanide Separation Process). The capability of X-ray fluorescence near total reflection (XFNTR) was extended to explore the distribution of Eu(III) between the liquid-liquid interface and bulk organic and aqueous phases which contained extractants HDEHP (bis(2-ethylhexyl) phosphoric acid) and HEHEHP (2-ethylhexyl phosphonic acid mono-2-ethylhexyl ester), the complexant DTPA (diethylene triamine pentaacetic acid), and citric and nitric acids. Although an Am-compatible sample cell was developed, extending x-ray measurements of flat liquid-liquid interfaces to the actinide Am(III) did not prove to be possible within constraints imposed by the Advanced Photon Source. However, preliminary measurements with a drop cell may eventually provide a path forward to investigate Am(III) at a liquid interface. It was also demonstrated that competitive binding that occurs during back-extraction of lanthanide ions to either a phosphoric acid extractant (DHDP, di-hexadecyl phosphate) at the liquid interface or to complexant DTPA in the bulk aqueous phase could be reversibly tuned by X-ray exposure. Separately, X-ray measurements from the liquid-vapor interface explored the role of the aqueous solubility of HDEHP and HEHEHP and their interactions with a range of lanthanides and transition metal ions. Finally, the capability of X-ray absorption spectroscopy (EXAFS) was extended to probe metal ion coordination in lanthanide ion-extractant complexes at the liquid-vapor interface. Complementary to the specific interfacial systems studied during this project, the development of x-ray techniques expands our ability to understand ion ordering at liquid interfaces.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Integrated TBC/EBC for SiC Fiber Reinforced SiC Matrix Composites for Next Generation Gas Turbines (Final Report)

In this ambitious project, a significant challenge preventing widespread use of ceramic matrix composites in hot section components of gas power generating turbines was addressed. Hot section components made from SiC fiber reinforced SiC matrix composites (SiC/SiC composites), have the potential to achieve a combined cycle energy efficiency of above 65%. To achieve this efficiency, the temperature of the combustion gases on the turbine component surface is expected to reach as high as ~1700ºC (3100ºF). However, SiC/SiC composites suffer from volatilization at high temperature under high velocity steam environment – typical in a turbine hot chamber. This integrated collaborative project, between two research groups at Clemson University and a team of engineers and scientists at GE Gas Power, focused on design, fabrication and evaluation of a new graded environmental barrier coating. Using the excellent compositional tailorability of polymer derived ceramics (PDCs), we developed an integrated EBC/BC that smoothly transitions from bottom SiC/SiC bond interface to hermetic sesquioxide (Y 2 O 3 ) top surface. This smooth compositional transition avoided the sharp CTE mismatch at interfaces to greatly reduce the thermal stress. The developed EBC is compatible with and bonds well with the bond coat that GE uses. The top hermetic oxide surface ensures low oxygen transportation and volatilization rates under the high velocity steam environment. The graded microstructure with increasing sesquioxide concentration also decreases the amount of Si and C elements near the top hermetic sesquioxide layer. Coatings made using a process suitable for manufacturing – atmospheric plasma spraying was demonstrated. The microstructure of coatings made using this process were fully characterized. Finally, the performance of these coatings was investigated under the most demanding conditions for this application. Specifically, high temperature, high velocity steam exposure; thermal shock test; and thermal cycling tests. The graded coatings performed exceptionally well in all these tests. Specific suggestions for future development in this area have also been identified. In addition to the excellent technical progress, this project helped initiate a robust collaboration between the research groups at Clemson and GE Gas Power. It also provided a high-quality learning and mentoring opportunity for the three post-doctoral research associates and two UG students at Clemson University who worked on this project. All proposed tasks, sub-tasks were completed, and all milestones achieved.

03 NATURAL GAS↗

Peatland hydrology across scale: a probabilistic framework for confronting variability, heterogeneity, and uncertainty (Final Report)

Our project aimed to guide the representations of peatland hydrology and water-carbon feedbacks within Earth System Models, by improving process understanding and developing parsimonious models that elucidate the effects of hydroclimatic variability and spatial heterogeneity. Our research questions centered on the three key drivers of peatland hydrology: (1) seasonal and interannual hydroclimatic fluctuations, (2) spatial heterogeneity of peatland microtopography, and (3) hydrological connectivity across landscape units within a peatland watershed. Our analyses and model testing used existing long-term datasets within the Marcell Experimental Forest (MEF), with new data collected whenever necessary. To date, we have demonstrated the strong influence of water table elevations on the temperature sensitivity of CH 4 emissions, using a newly developed eddy covariance dataset spanning eleven years at MEF. Specifically, higher water tables dampen the increase in CH 4 emissions in the spring as well as their decrease in the fall, resulting in hysteresis. These results imply that any hydroclimatological changes in peatlands that shift seasonal water availability from winter to summer will increase annual CH 4 emissions, even if soil temperature remains unchanged. To further investigate water table elevation change within the peatland microtopography, we installed automated water table gauges across four bog-forest transects (the “lagg”) in two peatland watersheds at MEF, which are hotspots of intense biogeochemical activity. These measurements will give us new information about the extent of lagg expansion and contraction during snowmelt and high intensity rainfall events, as well as the directionality of water and nutrient flow into the bog from the surrounding forests. Finally, we investigated the hydrological connectivity across the peatland watershed complex during early spring – a critical period where water table is elevated from snowmelt – using extended hydrological records from MEF (e.g., snow and frost depths, water table elevations, streamflow). The importance of thermal and wintertime processes within the Energy Exascale Earth System Model (E3SM) was determined through sensitivity analyses. Results from data analyses show that (i) streamflow has decreased over decades likely due to increased evapotranspiration rates (despite no detectable trends in precipitation), (ii) spring streamflow generation is controlled by a sequence of fill-and-spill pathways from the snowpack to the stream through peatland water stores, and (iii) frost depth is a key explanatory variable for the timing and magnitude of streamflow. These results suggest that frost plays an important role in connecting surface water storage in peatlands to stream outlets, and that the hydrological connectivity across the peatland watershed complex can mediate the sensitivity of hydrological responses to climate variations.

54 ENVIRONMENTAL SCIENCES↗

Efficient, Compact, and Smooth Variable Propulsion Motor (Final Report)

In this project, a new architecture of highly efficient hydraulic motor was developed for the propulsion of off-highway vehicles. The motor uses an adjustable linkage driving a cam to vary the displacement of the piston, resulting in a Variable Displacement Linkage Motor (VDLM). The motor uses low friction rolling element bearings to significantly reduce mechanical friction, especially in the demanding low-speed high-torque conditions experienced by off-highway vehicles. The VDLM has high torque capabilities for its size due to the radial piston packaging and use of a multi-lobe cam. A VDLM is very smooth due to the ability to tune the torque ripple through the design of the cam profile. The project was divided into three periods. During the first period, a dynamic model was constructed of the motor to predict the performance of the motor and the vehicle. During the second period, a single-cylinder learning prototype was designed, built, and tested to validate the models constructed in the first period. In the third period, a multi-cylinder prototype motor was optimized, designed, fabricated, and tested. The motor demonstrated excellent mechanical efficiency (above 92.5% across the range of displacements), but the experimentally measure volumetric efficiency was lower than expected due to higher leakage rates created by the poor tolerance control on the prototype. To validate the dynamic models developed in the first period and better understand design trade-offs. In the third period a multi-cylinder concept demonstration prototype will be designed, fabricated, and tested. The final prototype will be tested on a motor dynamometer and will be utilized in hardware-in-the-loop testing to demonstrate its efficiency and performance impacts on the overall drive train. The experimental results were used in a drive train simulation of a compact track loader operating through a drive cycle. Using the VDLM in a hydrostatic circuit yielded 17.1% reduction in fuel consumption and 36.5% reduction in a series hybrid transmission.

99 GENERAL AND MISCELLANEOUS↗

Accelerating Biomimetic Solar - Energy Harvesting: Mapping the Interaction Landscape of Plasmonic-Excitonic Hybrid Nanosystems (Final Report)

In general, excitonic and plasmonic nanoscale materials in close proximity show high potential for significant breakthroughs in energy related materials research. The interactions between these two kinds of materials result in coupled optical transitions (plexcitons), distinct from those of both the individual exciton and plasmon as well as from those of the sum of their constituents (synergistic effects). By linking together materials-research and physical-research approaches, this project contributes to a concerted approach on nanomaterials energy research. The project’s overall goal is to accelerate the development of well-defined plexcitonic model systems consisting of carefully engineered plasmonic and excitonic nanomaterial— essential for both gaining a fundamental understanding of plexcitonic nanomaterials and the development of novel design principles for biomimetic solar energy harvesting. During the 3-year project period and the terminal renewal with limited support for a 12-month period, we successfully synthesized and characterized (1) a robust excitonic nanomaterial and (2) a library of plasmonic nanoparticles as well as developed (3) a microfluidic platform for homogenous nanosynthesis as summarized below: (1) Robust Excitonic Nanomaterial. Supramolecular assemblies are Nature’s most successful material system for solar energy harvesting. However, photovoltaic devices based on artificial supramolecular assemblies continue to be stymied by disappointing efficiencies and poor stability. The conceptual failure may lie in current solar cell architectures, which rely on solidifying supramolecular assemblies as an ensemble into a solid matrix, neglecting the intrinsic fragility of the assemblies’ internal structure, thus disrupting or even destroying their delicate optoelectronic properties, that is, delicate Frenkel excitonic properties. Supramolecular assemblies may finally serve as usable light harvesting material systems for solar energy conversion technologies, only if they meet the following criteria: (a) Stability, that is, the fragile structure including its delicate Frenkel excitonic character needs to be stable, (b) Robustness, that is, resistant against elevated and fluctuating temperatures, and (c) Viability for device integration, that is, capable of being immobilized onto solid substrates. Here, by developing a nanocomposite via a tunable, cage-like scaffold design, we successfully provided stable supramolecular nanocomposites, that inhabit robust Frenkel excitons despite harming environmental conditions such as extreme heat stress. (2) Library of Plasmonic Nanoparticles. Naturally, current models describing plasmonic hybrid quantum states—plasmonic hybridizations—parallel those developed for molecular orbitals, equating individual plasmonic nanostructures with “atoms” and the plasmonic nanoassemblies with “molecules.” In analogy to organic synthesis, a suitably robust fabrication method would allow for “atom-like” manipulation of “molecule-like” plasmonic nanoassemblies; of high value for next-generation energy nanotechnologies. Despite this frequent comparison, current plasmonic nanoassembly fabrication methods favor top-down templating over wet-chemical synthesis, however, achieving precise control over nanostructure’s geometry and surface characteristics remain an art and a scientific challenge. The conceptual failure may lie in the current wet-chemical synthesis paradigm, as it relies on the accessibility of a multi-dimensional synthesis parameter space through limited, rather one-dimensional synthesis procedures by employing step-by-step approaches. Solution-based nanoarchitectonics for rational design of precisely built plasmonic nanoassemblies via solution-based fabrication may finally be possible only if multi-dimensional syntheses approaches are available that allow for comprehensive control over the plasmonic nanomaterials’ (a) Structural Properties and (b) Surface Properties. Here, by developing an innovative multidimensional 1,3-propanediol based polyol synthesis, we successfully provided control over the plasmonic building-block’s geometry (size and shape) together with its surface characteristics. Our results present a critical step toward the vision of a “periodic table-like” system for plasmonic materials based on straightforward wet-chemical syntheses for energy nanotechnologies. Developing deliberate modifications on this synthesis, we generated a library of plasmonic nanostructures covering the vast parameter space—opening the door for fundamental investigation of plexcitonic model systems. (3) Microfluidic Platform for Homogenous Nanosynthesis. Control over structural properties of plexcitonic nanocomposites remains a challenge due to current limitations in nanosynthesis techniques. Slight variations in nanostructure’s geometry impact their optoelectronic properties, demanding precise synthesis beyond the capabilities of solution-based (batch) synthesis processes. In contrast, the small, confined liquid volumes used in microfluidics—a reaction technique where the manipulation of fluids takes place in channels with dimensions of tens of micrometers—allows for homogenous synthesis conditions, providing excellent control of the reaction and, as a result, of the materials’ geopmetry and composition. However, thus far, the majority of plexcitonic systems has been developed via batch synthesis. Here, by successfully developing a two-channel microreactor, our microfluidic-supported synthesis approach combines the advantages of both microfluidics and batch platforms, allowing for precise spatio-temporal control over all synthesis parameters opening the possibility for homogenous nanosythnesis of well-defined plexcitonic model systems.

14 SOLAR ENERGY↗

Time-Resolved Spectroscopy of Insulator-Metal Transitions: Exploring Low-Energy Dynamics in Strongly Correlated Systems. Final Report

Transition metal oxides (TMOs) have attracted much attention in recent years. The strong coupling between charge, spin, and orbital degrees of freedom creates novel functional properties. The research at the interplay between ferromagnetism, ferroelectricity and conductivity provides a promising way to the development of future spintronic devices. The interface characterization of multifunctional oxide heterostructures is crucial to understand deeply the magnetic response, spin injection and spin transport. In year one, we characterized optically the magnetic property with the method of magnetization-induced second-harmonic generation (MSHG), which is a sensitive technique to selectively probe the interface where the spatial inversion symmetry is broken. The interface of n-type BaTiO 3 (BTO)/La 0.67 Sr 0.33 MnO 3 (LSMO) forms a Schottky barrier and displays a good diode effect. By applying an external electric field across the sample, we observe the magnetoelectric (ME) coupling effect to modulate the interface magnetization. The voltage dependent magnetic contrast sharply vanishes at positive voltage (applied to LSMO contact) and reveals a ferromagnetic (FM)-to- antiferromagnetic (AFM) transition occurring at the interface, while the magneto-optic Kerr effect (MOKE) indicates that the bulk property is not affected. The strain mediated mechanism and ferroelectric (FE) polarization induced charge medicated mechanism are both discussed, but they do not play an important role in the observed magnetization transition. A new mechanism is proposed - the injected minority spins through strong Hund's interaction with the local magnetic moments at positive voltage weaken the double-exchange interaction of nearby Mn e g electrons, thereby reducing the ferromagnetic (FM) ordering. The dominant superexchange interaction of localized t 2g electrons finally leads to the AFM configuration. By reducing the electron carrier concentration of BTO, a positive voltage shift of the transition is observed. The oxygen richer sample with lower carrier concentration requires a higher voltage to increase the hole doping level of LSMO to induce the interfacial AFM phase. By inserting a thin (1nm) La 0.5 Ca 0.5 MnO 3 layer between BTO and LSMO, the interface magnetic response from LSMO is enhanced. In year two, a non-multiferroic heterostructure SrTiO 3 (STO)/ La 0.5 Ca 0.5 MnO 3 (LCMO)/La 0.67 Sr 0.33 MnO 3 (LSMO) was studied. In this system, the interface FM-AFM transition is observed at negative voltage. The STO layer may act as a hole-donating layer, which induces the hole transfer to LSMO making it overdoped, while the LCMO interlayer at the 0.5 hole doping level displays complicated CE type AFM phase. Thus the AFM phase is dominant at the interface and electron accumulation is required to induce the FM phase by applying a negative voltage. For oxygen rich sample, the magnetic MSHG loop reappears at high positive voltage (around +2.5 V). At high doping level (x > 0.5), LSMO exhibits A-type AFM order, consisting of AFM superexchange coupling between adjacent layers and intralayer FM double-exchange coupling. The less tensile strain of STO and LSMO due to a smaller lattice mismatch as compared to BTO would result in a weaker interlayer coupling . Thus, interfacial A-type AFM order can occur in STO/LCMO/LSMO heterostructure at high hole doping concentration. The study of ME coupling of multifunctional oxide heterostructures is definitely important to the development and performance of future spintronic devices. The results presented here regarding the interfacial magnetic transition controlled by an external electric field offer some new perspective to study the spin transport of magnetic tunnel junctions.

36 MATERIALS SCIENCE↗

Evolution of Pore Structure and Permeability of Rocks Under Hydrothermal Conditions (Final Report)

The physical and transport properties of porous rocks can be altered by a variety of diagenetic, metamorphic, and tectonic processes, and the changes that result are of critical importance to such industrial applications as resource recovery, carbon dioxide sequestration, and waste isolation in geologic formations. The associated interrelationships between rocks, pore fluids and deformation are also key to understanding many natural processes, including dynamic metamorphism, fault mechanics, fault stability and pressure solution creep. In this project, we investigated the changes of permeability and pore geometry owing to inelastic deformation by solution-transfer, brittle fracturing and dislocation creep. In particular, we studied the coupling between pore fluids and deformation in fluid-filled quartz, calcite, mudstones and ultramafic rocks and examine the effects of coupled mechanical and chemical processes on the evolution of porosity and permeability under hydrothermal conditions. The investigations used a combination of techniques, that included triaxial laboratory experiments; uniaxial compressive loading with in situ observations of microstructure; permeability under hydrostatic compression; observations of microstructure using optical and electron microscopes, and micro-CT imaging; and numerical calculations. Laboratory experiments were designed to provide mechanical and transport data under conditions that isolate the particular mechanisms responsible for the changes. The data obtained were used to quantify changes in surface roughness, porosity, pore dimensions and their spatial fluctuations. The results of the experiments and data from image analyses were compared to the results of network, finite-difference and other numerical models to verify the validity of experimentally established relations between permeability and other rock properties. A bibliography for the period from 2015-2019 is appended below. New results obtained in the final year and the unfunded extension period are detailed below.

58 GEOSCIENCES↗

Predictive Modeling and Diagnostic Monitoring of Extreme Science Workflows (Final Report)

This proposal addresses a critical issue of performance prediction identified in the report from the ASCR \Computational Modeling of Big Networks (COMBINE)" workshop: "end-to-end performance is not predictable due to a variety of factors. Even when some performance forecasts or predictions can be made, they often cannot explain the reasons why some predictions fail." We will develop new analytical models to predict the end-to-end performance of scientific workflows on DOE computing infrastructures, and use simulations and experimentation to validate and refine these models, as well as to pinpoint the sources of model inaccuracy. We will also use these models to help diagnose application and infrastructure problems, and to adapt the system based on this diagnosis. This section provides background in the areas relevant to the proposed work. RPI’s specific tasks within the Panorama project are as follows: (1) Develop Aspen-Simulation interface for Workflow Model Driven Simulation. (2) Validate manual performance models of two target workflow scenarios with empirical measurement and simulation. (3) Extend ROSS-Aspen API to simulate workflow descriptions when required. (4) Validate Aspen performance models of two target workflow scenarios with automatic performance model empirical measurement and simulation. (5) Design and implement final system to automatically generate Aspen performance models from workflow descriptions (including methods to compensate for limitations of Aspen analytical models). (6) Validate improved Aspen performance models with target workflow on production infrastructure. To date, all the project milestones assigned to us where reached within the best of our abilities over the course of the project performance period. Below describes the key outcome from our collaborative research in a system named, Durango .

97 MATHEMATICS AND COMPUTING↗

Solving the Pulsed-Power Driven Inertial Fusion Energy Standoff Problem (Abbreviated Final Report)

The standoff problem in pulsed-power driven IFE (Inertial Fusion Energy) refers to the problem of electrically connecting a fusion target with the driver in a way that preserves the driver/target interface in the presence of a large fusion energy release (100’s of megajoules to 1000 megajoules). High yield fusion drivers for stockpile stewardship applications have similar concerns, but without the complication of the high repetition rate needed for energy production. All proposed IFE or high yield systems have the challenge of protecting the reactor vessel and driver from the energy release, but pulsed power drivers have the additional challenge of establishing an electrical connection in a way that does not create excessive debris or require costly/massive structures that must be expendable. Fortunately, there are conceptual solutions in the form of very low mass transmission lines, usually in the form of wires or foils, since very little mass is needed to overcome the magnetic forces driving the transmission lines apart or provide a low resistance pathway given the short pulse duration of the driver. Several important aspects of the standoff problem were analyzed in the course of this LDRD project. Conceptual means of introducing the low mass transmission lines into the reactor chamber were proposed, including analysis of methods to retain the power flow gap between the electrodes in the presence of the chamber environment. The energy losses due to ohmic dissipation and magnetic acceleration of the low mass transmission lines were evaluated for candidate driver pulses and different transmission line masses, and the fluence of x-ray and neutron energy on the persistent power flow structures that must survive the pulse of energy were evaluated. Finally, means of rapidly pumping down the chamber were explored as a way to return the system to low pressure following the multi-atmosphere post-pulse pressure rise. The overall conclusion from the analysis is that, while the reactor environment creates stressful conditions for a low mass transmission line standoff system, there are concepts expending 10 kg or less of electrode mass each pulse with the potential to mitigate the stresses and successfully drive fusion targets. Whether such a system could lead to a practical and economical fusion reactor would require extensive research and development beyond the scope of the feasibility study.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗