Search NASA⌕ Search

SEARCH · Search NASA

Results for “Process settings”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25

The Influence of β-decay Rates on r-process Observables

Abstract The rapid neutron capture process ( r -process) is one of the main mechanisms whereby elements heavier than iron are synthesized, and is entirely responsible for the natural production of the actinides. Kilonova emissions are modeled as being largely powered by the radioactive decay of species synthesized via the r -process. Given that the r -process occurs far from nuclear stability, unmeasured beta-decay rates play an essential role in setting the timescale for the r -process. In an effort to better understand the sensitivity of kilonova modeling to different theoretical global beta-decay descriptions, we incorporate these into nucleosynthesis calculations. We compare the results of these calculations and highlight differences in kilonova nuclear energy generation and light-curve predictions, as well as final abundances and their implications for nuclear cosmochronometry. We investigate scenarios where differences in beta-decay rates are responsible for increased nuclear heating on timescales of days that propagates into a significantly increased average bolometric luminosity between 1 and 10 days post-merger. We identify key nuclei, both measured and unmeasured, whose decay rates directly impact nuclear heating generation on timescales responsible for light-curve evolution. We also find that uncertainties in beta-decay rates significantly impact age estimates from cosmochronometry.

79 ASTRONOMY AND ASTROPHYSICS↗

Process Optimization

Process optimization is the discipline of adjusting a process to optimize a specified set of parameters without violating engineering constraints. This article reviews data-driven optimization methods based on genetic algorithms and stochastic models and demonstrates their use in powder-bed fusion and directed energy deposition processes. In the latter case, closed-loop feedback is used to control melt pool temperature and cooling rate in order to achieve desired microstructure.

Sprayberry, Michael↗

Sub-pilot-scale Production of High-Value Products from U.S. Coals

Investigators from the University of Utah, University of Wyoming and Marshall University pursued a program to study the conversion of raw coal to high-value products of carbon fiber and silicon carbide. Team members also developed an initial framework for a data portal that can incorporate laboratory data on coal processing and product quality, and also work with tools for machine learning for data analysis, data visualization and economic assessment. Experimental R&D efforts focused on the conversion of raw coal to coal tar and other byproducts, and the resulting tar intermediates were upgraded to form anisotropic and isotropic pitch materials. These pitch materials were produced from coal using both thermal (pyrolysis) and chemical (mild solvolysis liquefaction) decomposition of raw coal. Four different coals were studied: Utah bituminous coal (Sufco), Wyoming PRB coal (Black Thunder), Illinois bituminous coal (Illinois #6), and West Virginia bituminous coal (Flying Eagle). Both metallurgical-grade coking coals and lower-grade steam coals were investigated, and controlled secondary gas-phase reactions were used during a two-stage pyrolysis process to induce cracking and condensation reactions among the pyrolytic tar species. This approach successfully improved the performance of the lower grade coals for yielding pitch materials, with properties more consistent with a commercial-grade pitch that had previously demonstrated success for quality carbon fiber production. The use of waste plastic materials was also studied, to help improve physical and chemical characteristics of the intermediate tars and final pitch product; in particular, for lowering the pitch softening point to an acceptable level for melt spinning carbon fiber. Mild solvolysis liquefaction was also used as a method for producing pitch for carbon fiber production. As expected, significantly higher pitch yields were obtained using this approach, and waste plastic materials were also successfully used to reduce pitch softening point to an acceptable level. The plastic materials were also utilized to create a solvent for the mild solvolysis process, and this plastic-derived solvent was shown to provide results consistent with more expensive commercial chemical solvents, and could thus avoid the need for costly recovery and recycle of a liquefaction solvent. Additional experimental R&D focused on the production of silicon carbide (β-SiC) from the residual char byproduct from pitch production, and also on the production of carbon fiber from the anisotropic pitch. SiC was successfully synthesized using a mixture of residual char and sandstone at a ratio of 1:1. Reaction temperature and residence time were optimized and yielded a product purity of 81%. For carbon fiber production, the most successful pitch samples were obtained from the mild solvolysis liquefaction approach, combined with the use of a plastic (HDPE)-derived solvent. Fiber properties improved over time as laboratory fiber production methodologies improved, and final yields of carbon fiber were obtained with a diameter of 12.14 ± 1.10 um, Modulus of 173.73 ± 15.25 GPa, and Tensile Strength of 1.04 ± 0.10 GPa. A proof-of-concept Modern Community Research Data Portal (MCRDP) was developed and deployed for coal and coal-derived pitch characterization, with the full support of (i) remote web-based access, (ii) distributed analysis, (iii) interactive visualization and exploration, (iv) shared and long-term data access, (v) advanced query capabilities and (vi) real-time collaboration. The Coal to Products Data Portal “coaltoproducts.org” provides researchers with space to store and share data within a project, tools for analyzing and understanding data for scientific investigation, and the ability to publish data to the broader community for reproducibility. The portal leverages the Material Commons 2.0 (MC) platform developed by the Center for PRedictive Integrated Structural Materials Science (PRISMS) of the University of Michigan, to achieve long-term longevity of data collections and, more importantly, collaborative science. A number of data visualization tools were also assessed and implemented for interrogating the experimental and modeling data. The machine learning portion of this project analyzed datasets from two different coal conversion processes performed on a diverse set of coal samples from both the coal pyrolysis experiments and the solvent liquefaction experiments. The work was initiated by exploring standard regression models on the pyrolysis data, aiming to understand the impact of sample characteristics and processing conditions on key product metrics. Over the course of the project, the focus expanded to include a variety of machine learning tools, delving into both supervised and unsupervised learning methods. Models tested on the pyrolysis data included linear, ridge, lasso, elastic-net, Gaussian process, random forest regression, and AutoSklearn, and the approach was continually refined to enhance predictive accuracy and model interpretability. Similar techniques were applied to the liquefaction data with an additional focus on feature engineering. Along with mesophase content, additional outputs of interest were the pitch yield, softening point, and QI content. Insights derived from these analyses are crucial in determining the factors influencing the quality and yield of coal-derived products. As the work progressed, the research evolved from foundational model comparisons to analyses of random forests, decision paths, and feature importance scores. A thorough market analysis was performed to examine the prospects of coal-based carbon fibers. The best opportunities for coal come from its lower and more stable price relative to petroleum, particularly for subbituminous coals, which is the primary advantage that a coal refinery may have over a petroleum refinery. Before a commercial CTP production facility can be modeled, however, several things need to be understood regarding the nature of the would-be coal refinery. These include the technology to be deployed, the size of facility, the volume(s) of co-product(s), and the waste and emissions profile of the plant. The volume of co-products and waste may be substantial and will require separate market analysis to ensure viability. In the near-term, the importance of coal tar pitch, in the form of carbon pitch, to the aluminum and steel industries is likely to overshadow the alternative use of this material as an input for carbon fiber. The importance of steel and aluminum in building materials, and the need for carbon materials in their manufacturing, will ensure that demand for these products remains for the long run. In addition, carbon fiber may also be the best substitute for steel and aluminum well into the future. While society will eventually be able to shift production of much of its electricity needs to renewables, it will not be able to shift away from fossil fuels for production of high-strength construction and vehicular materials. Demand for carbon fiber is expected to increase quickly, but the volume of carbon fiber and the amount of coal that would be needed to produce even a sizeable share of this market may still be relatively small compared to current coal production. Thus, other coal-based products like graphene, graphite, carbon foams, resins, and carbon-based building products will play important roles in sustaining coal production as coal-fired power generation continues to decline.

01 COAL, LIGNITE, AND PEAT↗

Thermal aging effects on crosslinked polyethylene cable insulation with decabromodiphenyl ether flame retardant alternative

Decabromodiphenyl ether (decaBDE) has been extensively used as a flame retardant in several applications, including nuclear electrical cable insulation. However, decaBDE has been identified as a persistent, bioaccumulative and toxic (PBT) substance, leading to regulatory scrutiny. The Environmental Protection Agency (EPA) published a regulation on January 6, 2021, aimed at phasing out the manufacturing, processing, and distribution of decaBDE. This rule set a compliance deadline of March 8, 2021, for the manufacture and processing of decaBDE, and an extended deadline of January 6, 2023, for specific applications including wire and cable insulation in nuclear power generation facilities. In response to such regulations, RSCC, a major supplier of safety-related electrical cables and associated products to the U.S. nuclear industry updated the formula of their crosslinked polyethylene (XLPE) insulation to replace the historically used decaBDE flame retardant with an acceptable alternative. This change from the previous decaBDE-containing XLPE prompted interest in comparative performance of the two material formulations, especially with respect to characteristics relevant to safety-related function such as thermal and radiation resistance. RSCC graciously provided samples of wire insulated with the decaBDE-containing XLPE formulation and corresponding wire insulated with XLPE of the new formulation, containing a decaBDE alternative. In this work we compare characteristics of the two formulations and a previously produced commercial version of the RSCC decaBDE-containing XLPE insulation subjected to thermal aging at 150 °C and 165 °C. The comparison was focused on mechanical durability, thermal stability in the oxidative environment, and chemical structures. Briefly, • Tensile elongation at break (EAB) results showed loss of mechanical elasticity with longer aging time, as expected. Aging time dependence of EAB did not differ between the decaBDE-containing and decaBDE-alternative samples. • Subtle differences between the two materials can be detected from Fourier-transform infrared spectroscopy (FTIR) absorbance spectra in the range below 1700 cm -1 , are assumed to be related to decomposition of flame retardant additives during thermal aging. • The oxidation induction time (OIT) data seemed to show that the unaged decaBDE-containing XLPE material is more thermally stable than the unaged decaBDE-alternative material, but the discrepancy in OIT decreased with aging time and the OIT values of the two materials became similar starting with the 4 th day of aging at 165 °C. This thermal aging investigation confirmed that the mechanical durability, a key property monitored for cable qualification, was not significantly affected by the modification of the formulation with a decaBDE alternative flame-retardant system in the investigated thermal aging conditions. Further studies on the same sets of materials exposed to thermal and gamma radiation aging would further inform comparison of the materials safety-related function.

36 MATERIALS SCIENCE↗

Summary report of the 4th IAEA Technical Meeting on Fusion Data Processing, Validation and Analysis (FDPVA)

The objective of the Fourth Technical Meeting on Fusion Data Processing, Validation and Analysis was to provide a platform during which a set of topics relevant to fusion data processing, validation and analysis are discussed with the view of extrapolating needs to next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge-based understanding of the physical processes governing the dynamics of these plasmas. This paper presents the recent progress and achievements in the domain of plasma diagnostics and synthetic diagnostics data analysis (including image processing, regression analysis, inverse problems, deep learning, machine learning, big data and physics-based models for control) reported at the meeting. The progress in these areas highlight trends observed in current major fusion confinement devices. A special focus is dedicated on data analysis requirements for ITER and DEMO with a particular attention paid to artificial intelligence for automatization and improving reliability of control processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Physics informed deep neural network embedded in a chemical transport model for the Amazon rainforest

Secondary organic aerosols (SOA) are fine particles in the atmosphere, which interact with clouds, radiation and affect the Earth’s energy budget. SOA formation involves chemistry in gas phase, aqueous aerosols, and clouds. Simulating these chemical processes involve solving a stiff set of differential equations, which are computationally expensive steps for three-dimensional chemical transport models. Deep neural networks (DNNs) are universal function approximators that could be used to represent the complex nonlinear changes in aerosol physical and chemical processes; however, key challenges such as generalizability to extended time periods, preservation of mass balance, simulating sparse model outputs, and maintaining physical constraints have limited their use in atmospheric chemistry. Here, we develop an approach of using a physics-informed DNN that overcomes previous such challenges and demonstrates its applicability for the chemical formation processes of isoprene epoxydiol SOA (IEPOX-SOA) over the Amazon rainforest. The DNN is trained with data generated by simulating IEPOX-SOA over the entire atmospheric column, using the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem). The trained DNN is then embedded within WRF-Chem to replace the computationally expensive default solver of IEPOX-SOA formation. The trained DNN predictions generalizes well with the default model simulation of the IEPOX-SOA mass concentrations and its size distribution (20 size bins) over several days of simulations in both dry and wet seasons. The embedded DNN reduces the computational expense of WRF-Chem by a factor of 2. Our approach shows promise in terms of application to other computationally expensive chemistry solvers in climate models.

54 ENVIRONMENTAL SCIENCES↗

Description of Sensor Assignment Optimization Method as Deployed on a Multi-Node Cluster

Data analytic methods are being developed to address the problem of how to assign a sensor set in a nuclear facility such that a requisite level of process monitoring capability is realized and that the sensor set is sufficiently rich to determine the status of the individual sensors with respect to need for calibration. There is an awareness in the nuclear industry that data analytics combined with rich sensor sets represent a means to improve operations and reduce costs. In the industry the calibration problem has been previously approached as an empirical data-driven problem with several methods having been developed. However, the experience of the utilities over the past ten years with these methods indicates that the absence of physics-based information renders the data-driven approach less reliable. Complicating factors such as the inherent variability of operation (both equipment alignment and operating condition) can confound a pure data-driven approach while there are no rigorous guidelines for determining what constitutes an adequate sensor set. The solution under development to overcome these shortcomings supplements the data analytic method with process information in a so-called process-constrained data-analytic approach. Simple balance equations are written for generic components (e.g., mechanical pump, valve, and heat exchanger). These do not require a priori knowledge of process parameters, such as heat transfer coefficients or friction factors. All that is needed on the part of the utility user is to identify the components and how they are connected. This report describes the development of a parallel computing capability for determining the optimal sensor set. The optimal sensor set problem suffers from the curse of dimensionality. Computation time increases exponentially as the size of the system grows. To overcome this difficulty a pre-conditioner algorithm is developed to find an approximate solution close the actual solution. This serves as a seed for the full-blown algorithm and acts to constrain the space that must searched. The optimization algorithms are described and the implementation on a parallel computing platform is described. The application of the method to a use case we are solving in collaboration with our utility partner served to illustrate how the default sensor set in a nuclear plant may not provide sufficient coverage to infer sensor calibration status.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Quantitative Proteome Profiling Reveals Cellobiose-Dependent Protein Processing and Export Pathways for the Lignocellulolytic Response in Neurospora crassa

Filamentous fungi are intensively used for producing industrial enzymes, including lignocellulases. Employing insoluble cellulose to induce the production of lignocellulases causes some drawbacks, e.g., a complex fermentation operation, which can be overcome by using soluble inducers such as cellobiose. Here, a triple β-glucosidase mutant of Neurospora crassa, which prevents rapid turnover of cellobiose and thus allows the disaccharide to induce lignocellulases, was applied to profile the proteome responses to cellobiose and cellulose (Avicel). Our results revealed a shared proteomic response to cellobiose and Avicel, whose elements included lignocellulases and cellulolytic product transporters. While the cellulolytic proteins showed a correlated increase in protein and mRNA levels, only a moderate correlation was observed on a proteomic scale between protein and mRNA levels (R 2 = 0.31). Ribosome biogenesis and rRNA processing were significantly overrepresented in the protein set with increased protein but unchanged mRNA abundances in response to Avicel. Ribosome biogenesis, as well as protein processing and protein export, was also enriched in the protein set that showed increased abundance in response to cellobiose. NCU05895, a homolog of yeast CWH43, is potentially involved in transferring a glycosylphosphatidylinositol (GPI) anchor to nascent proteins. This protein showed increased abundance but no significant change in mRNA levels. Disruption of CWH43 resulted in a significant decrease in cellulase activities and secreted protein levels in cultures grown on Avicel, suggesting a positive regulatory role for CWH43 in cellulase production. The findings should have an impact on a systems engineering approach for strain improvement for the production of lignocellulases.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental determinations of carbon and hydrogen isotope fractionations and methane clumped isotope compositions associated with ethane pyrolysis from 550 to 600°C

Methane clumped isotope compositions signify the relative natural abundances of rare, doubly substituted isotopic species of methane ( 13 CH 3 D and 12 CH 2 D 2 ) and have emerged as a new isotopic tool to trace the sources, sinks, and lifecycles of methane in the environment. Such measurements can identify equilibration (or reequilibration) temperatures if found to be in isotopic equilibrium or non-equilibrium processes (e.g., kinetically controlled reactions or mixing) if not in isotopic equilibrium. Naturally occurring thermogenic methane—formed by the thermally activated breakdown of larger organic molecules—has been found to have clumped isotope compositions consistent with equilibrium at reasonable gas formation temperatures in some settings and non-equilibrium processes occurring during either formation, migration, storage, or extraction in others. To explore the potential controls on the isotopic composition of thermogenic methane, we conducted isothermal time-series ethane pyrolysis experiments at 550 and 600 °C to measure methane and ethane 13 C/ 12 C and D/H fractionations and methane clumped isotope compositions (resolved 13 CH 3 D and 12 CH 2 D 2 ). We explore the effects of modifying the initial clumped isotope composition of ethane and the addition of water vapor to pyrolysis experiments. We observe that ethane and methane 13 C/ 12 C are controlled by kinetic isotope effects and Rayleigh distillation processes. In contrast, ethane and methane D/H and methane clumped isotope compositions appear to be controlled by a combination of these processes and hydrogen isotope exchange. The hydrogen isotope exchange processes lead to isotopic equilibrium as reaction completion is approached for both D/H (ethane/methane) and methane clumped isotope compositions. Here, we develop a chemical model based on a mass balance approach that accounts for inheritance vs. hydrogen-abstraction formation pathways for singly and doubly substituted isotopologues of ethane and methane that is compared to the experimental data. The model allows the determination of carbon and hydrogen kinetic isotope effects associated with ethane cracking and hydrogen abstraction reactions that, where applicable, we compare to prior theoretical constraints. From the comparison of the model to the experimental data, we infer that the kinetically controlled ethane and methane bulk isotope compositions and methane clumped isotope compositions are controlled by kinetic isotope effects (both primary and secondary) associated with both C–C bond and C–H bond cleavage reactions. Specifically, the methane clumped isotope compositions likely result from a combination of clumped isotope effects associated with ethane breakdown and/or assembly of methane isotopologues (expressed in terms of γ-factor parameters ≠ 1) and combinatorial effects that arise probabilistically. We discuss our experimental results in the context of recent pyrolysis experiments and observations of naturally occurring thermogenic methane. We consider a proposal consistent with observations from nature that the hydrogen isotope exchange reactions that promote equilibration of methane isotopic molecules at or near formation temperature may be facilitated by free radicals generated by pyrolysis reactions. In this framework, isotope exchange effectively ceases when pyrolysis effectively ceases locking in compositions that can be consistent with peak formation temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Norm-Conserving Pseudopotentials and Basis Sets to Explore Actinide Chemistry in Complex Environments

We constructed and tested a new set of norm-conserving pseudopotentials, as well as companion Gaussian basis sets, for the actinide series (Ac–Lr) using the Goedecker, Teter and Hutter (GTH) formalism within the generalized gradient approximation (GGA) functional for exchange-correlation of Perdew, Burke and Ernzerhof (PBE). This fills a critical void in the literature for studying the chemistry of 5f–block elements in condensed phase. The accuracy and reliability of the newly parameterized An–GTH pseudopotentials and basis sets, a variety of tests on actinide-containing molecules were carried out and compared to all-electron and available experimental results. The new pseudopotentials include both medium ( [Xe]4f 14 ) and large core ( [Xe]4f 14 5d 10 ) options that successfully reproduced structure and energetics, particularly redox processes. The medium core size set, in particular, reproduced all electron calculations over multiple oxidation states from 0 to VII, whereas the large core set was suitable only for the early series elements and low oxidation states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spent-fuel recycling molecule degradation product standards can be produced with preparative liquid chromatography

Solvent systems used for spent nuclear fuel separation schemes are subject to intense radiation fields from the spent fuel, resulting in a degradation of separation performance over time from both the radiolytic destruction of active compounds (extractants, holdback agents, etc.) and the production of degradation compounds (compounds produced from the destruction of the active compounds). Development of a quantitative understanding of the effects of radiolysis on separations is impeded by a near-complete lack of availability of degradation products from chemical manufacturers. Synthesis of these degradation products through traditional means is both cost and time prohibitive, inhibiting advancement of new fuel separation processes. We hypothesize that comprehensive sets of degradation products can be synthesized using preparative radiolysis, and purified using high performance liquid chromatography in quantities sufficient for unequivocal identification and subsequent use as quantitative analytical studies. Achieving this objective will facilitate development of a much more accurate understanding of radiolysis reactions and their effects on solvent extraction processes, positioning Idaho National Laboratory (INL) in a leadership role in the science of fuel cycle separations. We propose producing these degradation compounds by irradiating concentrated samples of solvent ligands in the INL gamma irradiator, separating the resulting mixture with preparative chromatography, and removing the mobile phase in the separated fractions with a vacuum concentrator. This will yield milligram to gram quantities of purified degradation products, sufficient for fundamental research, at a fraction of the time and cost of synthesis. Facile production of separation molecule degradation products at minimal cost will enable the fundamental research that will accelerate the development of fuel cycles that will ensure the competitiveness of nuclear energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Technetium Management Program Plan - 17376

Technetium management is a high-priority activity for the U.S. Department of Energy (DOE) Office of Environmental Management (EM) complex. Waste management and remediation issues involving technetium represent environmental risks and challenges that are unique to DOE. This plan lays out the technology development activities that are underway as well as future technology needs to address technetium issues across DOE EM sites and across programmatic areas of tank waste, groundwater and soils, and facility decommissioning and deactivation in order to be comprehensive and to allow integration of similar activities. The program was developed in close coordination with site representatives and program offices. Activities and needs that were identified share common themes and were grouped into areas of characterization, treatment, and disposition. Characterization includes understanding the inventory at particular locations, the chemical species, and chemical and physical behavior, whether in a treatment process flowsheet or a geological setting that displays periodic contaminant releases. The tools for characterization in these different environments might use the same sensors or protocols. Treatment options include methods to capture technetium such as ion-exchange or manipulation of oxidation states, which also may be applied across program areas. Disposition includes end-points of the processes and environmental risk, including waste form behavior, mobility of technetium once it is treated or remediated, and long-term monitoring. Disposition represents integration of all cleanup actions at a site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Study on Application of Geopolymer to the Retrieval of Fuel Debris in Fukushima Dai-ichi NPP

In order to retrieve fuel debris in Fukushima Dai-ichi NPP, many retrieval methods are proposed. Geopolymer is the candidate material applied for an alternative retrieval method. In this concept, Geopolymer can be used to stabilize fuel debris and suppress the diffusion of radioactive materials. Objective: Evaluation of geopolymer applied for retrieving fuel debris. Slump Flow Test: Slump flow values decreased as the test temperature increased. In air condition, water molecules evaporated from geopolymer and the viscosity of geopolymer increased. In water condition, the same trends as in air condition were observed. Slump flow values of geopolymer also depended on the elapsed time after mixing. By adding water, the slump flow values of geopolymer became higher (Even at 80 deg. C). It is possible to adjust the solidification time (Setting time) of geopolymer. Solidification Process of Geopolymer: After the first layer solidified, the second layer was injected. At 300 deg. C, porous structure was observed in the first layer, while the second layer structure was intact. In the actual application, multilayered geopolymer may be used to stabilize fuel debris. Conclusion: Fluidity of geopolymer decreased with raising temperature. Setting time can be adjusted by adding water. Geopolymer may be applied by injecting multiple times on high temperature materials above 100 deg. C.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Efficient Organic Solar Cell with 16.88% Efficiency Enabled by Refined Acceptor Crystallization and Morphology with Improved Charge Transfer and Transport Properties

Abstract Single‐layered organic solar cells (OSCs) using nonfullerene acceptors have reached 16% efficiency. Such a breakthrough has inspired new sparks for the development of the next generation of OSC materials. In addition to the optimization of electronic structure, it is important to investigate the essential solid‐state structure that guides the high efficiency of bulk heterojunction blends, which provides insight in understanding how to pair an efficient donor–acceptor mixture and refine film morphology. In this study, a thorough analysis is executed to reveal morphology details, and the results demonstrate that Y6 can form a unique 2D packing with a polymer‐like conjugated backbone oriented normal to the substrate, controlled by the processing solvent and thermal annealing conditions. Such morphology provides improved carrier transport and ultrafast hole and electron transfer, leading to improved device performance, and the best optimized device shows a power conversion efficiency of 16.88% (16.4% certified). This work reveals the importance of film morphology and the mechanism by which it affects device performance. A full set of analytical methods and processing conditions are executed to achieve high efficiency solar cells from materials design to device optimization, which will be useful in future OSC technology development.

Zhu, Lei↗

Connecting Femtosecond Transient Absorption Microscopy with Spatially Coregistered Time Averaged Optical Imaging Modalities

Multimodal all-optical imaging involving coregistered femtosecond transient absorption microscopy (TAM), time-integrated photoluminescence (PL), and steady-state modalities such as confocal reflectance and transmission offers an appealing approach to gain a comprehensive understanding of complex electronic excited-state phenomena in spatially heterogeneous systems. A unique combination of these modalities allows us to unravel not only the competing electronic excited-state dynamical processes but also the underlying morphological information with simultaneous high temporal and spatial resolution. However, correlating the various images obtained from time-resolved and time-independent modalities is generally nontrivial and particularly challenging when the electronic dynamics under study evolve in both time and space. Here, we demonstrate a new approach for rationally correlating time-resolved microscopy with coregistered time-integrated or steady-state modalities. Specifically, our approach involves an extended global lifetime analysis of the time-resolved microscopic data set to separate distinct dynamical processes taking place on commensurate time scales, and the resulting decay-associated amplitude maps (DAAMs) were applied to explore correlations with the images acquired using time-independent modalities. The feasibility of our approach was validated through analyzing a multimodal data set acquired from a thin film of chloride-containing mixed lead halide perovskites (CH 3 NH 3 PbI 3–x Cl x ) using femtosecond transient absorption, time-integrated PL, and confocal reflectance microscopies. Analysis of the results obtained enable us to gain new insight into the complex ultrafast relaxation dynamics in this highly heterogeneous system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ROV used in Sludge Retrieval and Treatment Project - 18575

The Orano-operated waste treatment site at La Hague, France, has treated large quantities of nuclear waste through-out its many decades of operation. During a period of over twenty years, a significant amount of the radioactive sludge resulting from the liquid waste treatment processes was placed into a set of adjoining tanks, called the STE2 silos. Now that those tanks are reaching capacity, a project has begun to retrieve this waste, transfer it to another location for homogenisation and characterization, and to then send it to another facility for conditioning and long-term storage. Because of the conditions inside and around these tanks, the waste retrieval process has many limitations. For example, the high radiation levels require that the retrieval be done efficiently, with a high removal rate and that operation be done remotely. The sludge retrieval tool will be operated and navigated while hidden inside the tank, under a significant amount of supernatant liquid, but needs to be accessible for maintenance and modifications and able to be transferred from one tank to the next. Additionally, the highly viscous consistency of the sludge requires special suction capabilities. All of these conditions need to be met, by a system that fits into the tanks' 900 mm (<3 ft) access ports. After almost three years of profound engineering, construction and testing efforts, a final design has been approved. The tool consists of a 250 kg (∼550 lb), remotely-operated vehicle (ROV) with an Archimedes-type screw attachment. It is delivered into and retrieved from the tank through a shielded glovebox that allows for maintenance and exchange of attachments. Sludge is sucked through a rotating screw and out a second tank opening with a consideration for limiting external water usage. To locate and navigate the tool, cameras detect LEDs attached to the ROV's buoys, and then calculate the ROV's position and orientation. With preliminary design and testing of the prototype complete, the project is preparing to award the ROV manufacturing contract and finalize the design of auxiliary systems, such as the rinsing and maintenance processes and localization instrumentation. After extensive final testing, the gloveboxes will be placed over the tanks in mid-2020, with entry into the first tank expected in April 2024. The ideas and experiences Orano is currently gathering during this effort will be of interest to laboratories and facilities that will soon be retrieving waste sludge from their aging storage tanks. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Neurogenesis Deep Learning: Extending deep networks to accommodate new classes

Neural machine learning methods, such as deep neural networks (DNN), have achieved remarkable success in a number of complex data processing tasks. These methods have arguably had their strongest impact on tasks such as image and audio processing – data processing domains in which humans have long held clear advantages over conventional algorithms. In contrast to biological neural systems, which are capable of learning continuously, deep artificial networks have a limited ability for incorporating new information in an already trained network. As a result, methods for continuous learning are potentially highly impactful in enabling the application of deep networks to dynamic data sets. Here, inspired by the process of adult neurogenesis in the hippocampus, we explore the potential for adding new neurons to deep layers of artificial neural networks in order to facilitate their acquisition of novel information while preserving previously trained data representations. Our results on the MNIST handwritten digit dataset and the NIST SD 19 dataset, which includes lower and upper case letters and digits, demonstrate that neurogenesis is well suited for addressing the stability-plasticity dilemma that has long challenged adaptive machine learning algorithms.

59 BASIC BIOLOGICAL SCIENCES↗