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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Versatile Sequential Casting Processing for Highly Efficient and Stable Binary Organic Photovoltaics

Forming an ideal bulk heterojunction (BHJ) morphology is a critical issue governing the photon to electron process in organic solar cells (OSCs). Complementary to the widely-used blend casting (BC) method for BHJ construction, sequential casting (SC) can also enable similar or even better morphology and device performance for OSCs. Here, BC and SC methods on three representative donor:acceptor (D:A) blends are utilized, that is, PM6:PC 71 BM, PM6:IT-4F and PM6:L8-BO. Higher power conversion efficiencies (PCEs) in all cases by taking advantage of beneficial morphology from SC processing are achieved, and a champion PCE of 18.86% (certified as 18.44%) based on the PM6:L8-BO blend is reached, representing the record value among binary OSCs. The observations on phase separation and vertical distribution inspire the proposal of the swelling–intercalation phase-separation model to interpret the morphology evolution during SC processing. Further, the vertical phase segregation is found to deliver an improvement of device performance via affecting the charge transport and collection processes, as evidenced by the D:A-ratio-dependent photovoltaic properties. Besides, OSCs based on SC processing show advantages on device photostability and upscale fabrication. Finally, this work demonstrates the versatility and efficacy of the SC method for BHJ-based OSCs.

14 SOLAR ENERGY↗
DOE OSTI2026

Enabling Bipolar Membrane Manufacturing Using Microscopy

Bipolar membranes (BPMs) used for water treatment suffer from interface instabilities, causing premature failure and decreased performance. Recent research has highlighted the impacts of membrane morphology on mechanical behavior and performance. Improved material performance of thin film membranes requires enhanced transport properties coupled with better control of the mechanical characteristics to avoid premature failure of the film. Thus, morphology is a key parameter when developing and evaluating novel membrane materials. Microscopy offers unique advantages for nano-scale characterization of thin film membrane interfaces and morphologies. In this study, the interface junction of BPMs was evaluated using scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). BPMs were fabricated using (1) hot pressing lamination, (2) bench-scale solution casting, and (3) roll-to-roll sequential casting (R2R). Both commercial and in-house fabricated ion exchange membranes were used in the BPMs. The BPMs were comprised of a cation exchange membrane and an anion exchange membrane with a catalyst layer sandwiched in between. Cross sectional SEM and EDX images of the membrane interface junction were compared among the different fabrication techniques and materials. The bench cast catalyst layers were nonuniform compared to the R2R and hot pressed membranes, demonstrating the importance of precise catalyst application conditions. Different thicknesses of the BPMs and individual membrane layers revealed that polymer solution concentration needs to be optimized during manufacturing. This work shows that microscopy can identify key processing parameters that affect BPM interface junction quality at the microscale to enable manufacturing of high performance BPMs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Enabling Roll-to-Roll Manufacturing of Bipolar Membranes Using Microscopy

Bipolar membranes (BPMs) used for water treatment suffer from interface instabilities, causing premature failure and decreased performance. Recent research has highlighted the impacts of membrane morphology on mechanical behavior and performance. Improved material performance of thin film membranes requires enhanced transport properties coupled with better control of the mechanical characteristics to avoid premature failure of the film. Thus, morphology is a key parameter when developing and evaluating novel membrane materials. Microscopy offers unique advantages for nano-scale characterization of thin film membrane interfaces and morphologies. In this study, the interface junction of BPMs was evaluated using scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). BPMs were fabricated using (1) hot pressing lamination, (2) bench-scale solution casting, and (3) roll-to-roll sequential casting (R2R). Both commercial and in-house fabricated ion exchange membranes were used in the BPMs. The BPMs were comprised of a cation exchange membrane and an anion exchange membrane with a catalyst layer sandwiched in between. Cross sectional SEM and EDX images of the membrane interface junction were compared among the different fabrication techniques and materials. The bench cast catalyst layers were nonuniform compared to the R2R and hot pressed membranes, demonstrating the importance of precise catalyst application conditions. Different thicknesses of the BPMs and individual membrane layers revealed that polymer solution concentration needs to be optimized during manufacturing. This work shows that microscopy can identify key processing parameters that affect BPM interface junction quality at the microscale to enable manufacturing of high performance BPMs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High-performance organic photodetectors enabled by a refined fibrillar multiphase morphology

Film morphology of donor:acceptor blend layers plays a critical role in photon-to-current efficiency and dark/noise current of organic photodetectors (OPDs). One effective approach to manipulate crystallization and mesoscale phase separation of such blend layers is sequential casting (SC). However, the guiding strategies to control the morphology and the impacts on OPD performance of the SC films remain elusive, as the film structural evolution during SC is different from conventional blend casting (BC). In this report a refined fibrillar multiphase morphology is demonstrated by SC in an NT812:IEICO-4F blend film, where the high-quality IEICO-4F crystallites infiltrate the robust NT812 fibril network from the surface to the bulk. Such a morphology leads to improved charge generation and collection, reduced trap states, and enhanced charge block capability of resultant device, enabling simultaneous achievement of high external quantum efficiency and low dark/noise current. A maximum special detectivity of 5 × 10 13 Jones is achieved at 860 nm under –0.1 V, which is among the highest detectivities for vis-to-NIR OPDs. The linear dynamic range and response speed are also improved. Such enhancements are parallelly observed from OPD devices based on other blend systems with similar fibrillar refinement, which provides guidelines for film structure manipulation towards high OPD performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Auxiliary sequential deposition enables 19%-efficiency organic solar cells processed from halogen-free solvents

High-efficiency organic solar cells are often achieved using toxic halogenated solvents and additives that are constrained in organic solar cells industry. Therefore, it is important to develop materials or processing methods that enabled highly efficient organic solar cells processed by halogen free solvents. In this paper, we report an innovative processing method named auxiliary sequential deposition that enables 19%-efficiency organic solar cells processed by halogen free solvents. Our auxiliary sequential deposition method is different from the conventional blend casting or sequential deposition methods in that it involves an additional casting of dithieno[3,2-b:2’,3’-d]thiophene between the sequential depositions of the donor (D18-Cl) and acceptor (L8-BO) layers. The auxiliary sequential deposition method enables dramatic performance enhancement from 15% to over 18% compared to the blend casting and sequential deposition methods. Furthermore, by incorporating a branched-chain-engineered acceptor called L8-BO-X, device performance can be boosted to over 19% due to increased intermolecular packing, representing top-tier values for green-solvent processed organic solar cells. Comprehensive morphological and time-resolved characterizations reveal that the superior blend morphology achieved through the auxiliary sequential deposition method promotes charge generation while simultaneously suppressing charge recombination. This research underscores the potential of the auxiliary sequential deposition method for fabricating highly efficient organic solar cells using environmentally friendly solvents.

14 SOLAR ENERGY↗
DOE OSTI2023

Role of reinforcement learning for risk-based robust control of cyber-physical energy systems

Critical infrastructures such as cyber-physical energy systems (CPS-E) integrate information flow and physical operations that are vulnerable to natural and targeted failures. Safe, secure, and reliable operation and control of CPS-E is critical to ensure societal well-being and economic prosperity. Automated control is key for real-time operations and may be mathematically cast as a sequential decision-making problem under uncertainty. Emergence of data-driven techniques for decision making under uncertainty, such as reinforcement learning (RL), have led to promising advances for addressing sequential decision-making problems for risk-based robust CPS-E control. However, existing research challenges include understanding the applicability of RL methods across diverse CPS-E applications, addressing the effect of risk preferences across multiple RL methods, and development of open-source domain-aware simulation environments for RL experimentation within a CPS-E context. This article systematically analyzes the applicability of four types of RL methods (model-free, model-based, hybrid model-free and model-based, and hierarchical) for risk-based robust CPS-E control. Problem features and solution stability for the RL methods are also discussed. We demonstrate and compare the performance of multiple RL methods under different risk specifications (risk-averse, risk-neutral, and risk-seeking) through the development and application of an open-source simulation environment. Motivating numerical simulation examples include representative single-zone and multizone building control use cases. Finally, six key insights for future research and broader adoption of RL methods are identified, with specific emphasis on problem features, algorithmic explainability, and solution stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Efficient and mechanically-robust organic solar cells based on vertical stratification modulation through sequential blade-coating

Mechanically durable organic solar cells (OSCs) with high efficiency are deemed as the ideal candidate for the power source of the next generation wearable electronic devices. However, the brittle nature of small molecules in most high-efficiency OSCs consisting of polymer and small molecule encourages easy formation of cracks in the photoactive film under deformation. Here, the vertical composition distribution of the active layer has been well optimized through sequential blade coating to realize highly deformable while efficient OSC. The optimized morphology exhibits distinct donor-rich and homogenous region distributed along the vertical direction in the bulk. The donor-rich region provides sufficient chain entanglements and strong interfaces beneficial for mechanical robustness of film, while homogeneously mixed region offers continuous interpenetrating network to maintain high device through-put, resulting in superior efficiency of 14.4% with high crack-onset strain (COS) of 30.5%. This efficiency versus COS combination is much higher than the best combination reported in all polymer systems (COS of 15.9% and efficiency of 11.1%). To the best of our knowledge, it is the highest COS value achieved in polymer-small molecule systems. As a result, the rational control over vertical stratification demonstrated here would guide researchers in the development of innovative wearable electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mechanical and Thermophysical properties of low enriched uranium-10wt% molybdenum rolled foils

In this study, low-enriched (~19.75% 235 U) U-10Mo(wt%) foils were evaluated for both mechanical and thermophysical properties to establish baseline characteristics prior to irradiation testing. Cast U-10Mo ingots were sequentially hot and cold rolled to two different final foil thicknesses, resulting in different levels of cold work being present in the finished foils. The mechanical response of the U-10Mo foils was evaluated in the temperature range of 293–623 K. Increasing test temperatures resulted in decreases of both yield and ultimate tensile strength. Comparison of results to earlier work performed on depleted U-10Mo rolled foils indicates that the material in this study has lower strength and increased ductility. However, a comparison of the two different foil thicknesses in this study found that they were nearly identical in yield and ultimate tensile strength, differing by only 10–20 MPa (<2%). Thermal conductivity was calculated from the measurements of specific heat, linear thermal expansion, and thermal diffusivity from 323 to 1273 K on both thicknesses of the foils. These data were approximately 5–10% lower than previously published data above 573 K and were similar to data for temperature ranges below 573 K. Differences are likely related to differences in grain size and/or impurity content and variation in fabrication history.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Learning to Trigger: Reinforcement Learning at the Large Hadron Collider

High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (\textit{triggering}) under tight constraints on bandwidth, latency, and storage. In practice, trigger menus are largely static and hand-tuned and can become suboptimal as detector conditions, pileup, and background composition drift over time. We cast online threshold tuning as a sequential decision-making problem: a reinforcement learning agent ingests streaming summaries of recent rates and signal-sensitive features and updates trigger thresholds to maximize signal efficiency while tracking a target background rate within a tolerance band. We adapt Group-Filtered Policy Optimization (GFPO) to streaming control and introduce two variants (GFPO-F, GFPO-FR) that enforce background rate feasibility during training. On a benchmark that emulates realistic collider operation, we study two representative triggers: a total transverse energy ($H_{T}$) trigger sensitive to pileup variation, and an anomaly-detection (AD) trigger based on reconstruction loss for rare or non-standard signatures. On Monte Carlo streams, our agent increases the fraction of in-tolerance time intervals by 48% ($H_T$) and 28% (AD), with a cumulative gain of up to 2% in signal efficiency on those in-tolerance intervals. Transferring from simulation to \emph{real} collision data (CMS Run 283408), the same agent, without fine-tuning, achieves a 56% ($H_T$) and 28% (AD) in-tolerance improvement over baselines, with further signal-efficiency gain on both triggers. To our knowledge, this is the \emph{first} demonstration of RL-based trigger control on real Large Hadron Collider collision data. Code is available at https://github.com/Zixind/GFPO_LHC (see repo for details).

Ding, Zixin [Chicago U.]↗
NASA NTRS2017

The HITRAN2016 Molecular Spectroscopic Database

This paper describes the contents of the 2016 edition of the HITRAN molecular spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2012 and its updates during the intervening years. The HITRAN molecular absorption compilation is composed of five major components: the traditional line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, infrared absorption cross-sections for molecules not yet amenable to representation in a line-by-line form, collision-induced absorption data, aerosol indices of refraction, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, added line-shape formalisms, and validity. Moreover, molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth. Of considerable note, experimental IR cross-sections for almost 300 additional molecules important in different areas of atmospheric science have been added to the database. The compilation can be accessed through www.hitran.org. Most of the HITRAN data have now been cast into an underlying relational database structure that offers many advantages over the long-standing sequential text-based structure. The new structure empowers the user in many ways. It enables the incorporation of an extended set of fundamental parameters per transition, sophisticated line-shape formalisms, easy user-defined output formats, and very convenient searching, filtering, and plotting of data. A powerful application programming interface making use of structured query language (SQL) features for higher-level applications of HITRAN is also provided.

HITRAN↗
NASA NTRS1980

The influence of structural response on sympathetic detonation

The role that a munition's structural response plays in the ignition process and the development of violent reactions and detonations is explored. The munition's structural response is identified as one of the factors that influences reaction violence. If the structural response of a round is known, this knowledge can be used to redstruce the probability that a large explosion would result from the sequential detonation of individual rounds within a large storage array. The response of an acceptor round was studied. The castings fail in the same manner regardless of whether or not there is a fill material present in the round. These failures are caused by stress waves which are transformed from compressive waves to tensile waves by reflection as the impact energy moves around the casting. Since these waves move in opposite directions around the projectile circumference and collide opposite the point of impact, very high tensile forces are developed which can crack the casing.

Watson, J. L.↗
NASA NTRS1983

Population Control of Self-Replicating Systems: Option C

From the conception and development of the theory of self-replicating automata by John von Neumann, others have expanded on his theories. In 1980, Georg von Tiesenhausen and Wesley A. Darbro developed a report which is a "first' in presenting the theories in a conceptualized engineering setting. In that report several options involving self-replicating systems are presented. One of the options allows each primary to generate n replicas, one in each sequential time frame after its own generation. Each replica is limited to a maximum of m ancestors. This study involves determining the state vector of the replicas in an efficient manner. The problem is cast in matrix notation, where F = fij is a non-diagonalizable matrix. Any element fij represents the number of elements of type j = (c,d) in time frame k+1 generated from type i = (a,b) in time frame k. It is then shown that the state vector is: bar F(k)=bar F (non-zero) X F sub K = bar F (non-zero) xmx J sub kx m sub-1 where J is a matrix in Jordan form having the same eigenvalues as F. M is a matrix composed of the eigenvectors and the generalized eigenvectors of F.

Mccord, R. L.↗
DOE OSTI2025

Strong, ductile, and hierarchical hetero-lamellar-structured alloys through microstructural inheritance and refinement

The strength−ductility trade-off exists ubiquitously, especially in brittle intermetallic-containing multiple principal element alloys (MPEAs), where the intermetallic phases often induce premature failure leading to severe ductility reduction. Hierarchical heterogeneities represent a promising microstructural solution to achieve simultaneous strength−ductility enhancement. However, it remains fundamentally challenging to tailor hierarchical heterostructures using conventional methods, which often rely on costly and time-consuming processing. Here, we report a multiscale microstructural inheritance and refinement strategy to process “structural hierarchy precursors” in as-cast heterogeneous Al 0.7 CoCrFeNi MPEAs, which lead directly to a hierarchical hetero-lamellar structure (HLS) after simple rolling and annealing. Interestingly, it takes only 10 min of annealing time, two orders of magnitude less than that required to render the state-of-the-art properties during conventional processing of Al 0.7 CoCrFeNi, for us to achieve record-high strength−ductility combinations via the hierarchical HLS design that sequentially stimulates multiple unusual deformation and reinforcement mechanisms. In particular, the HLS-enabled high hetero-deformation-induced (HDI) internal stress triggers profuse <111>-type dislocations on over five independent slip systems in the supposedly brittle intermetallic phase and activates extensive stacking faults (SFs) and nanotwinning in the adjoining soft phase with a rather high SF energy. These unexpected, dynamically reinforcing hetero-deformation mechanisms across multiple length scales facilitate high sustained HDI strain hardening, along with a salient microcrack-mediated extrinsic ductilization effect, suggesting that the proposed microstructural inheritance and refinement strategy provides an efficient, fast, and low-cost approach to overcome the strength−ductility trade-off in a broad range of structural materials.

Science & Technology - Other Topics↗
NASA NTRS1996

CometBoards Users Manual Release 1.0

Several nonlinear mathematical programming algorithms for structural design applications are available at present. These include the sequence of unconstrained minimizations technique, the method of feasible directions, and the sequential quadratic programming technique. The optimality criteria technique and the fully utilized design concept are two other structural design methods. A project was undertaken to bring all these design methods under a common computer environment so that a designer can select any one of these tools that may be suitable for his/her application. To facilitate selection of a design algorithm, to validate and check out the computer code, and to ascertain the relative merits of the design tools, modest finite element structural analysis programs based on the concept of stiffness and integrated force methods have been coupled to each design method. The code that contains both these design and analysis tools, by reading input information from analysis and design data files, can cast the design of a structure as a minimum-weight optimization problem. The code can then solve it with a user-specified optimization technique and a user-specified analysis method. This design code is called CometBoards, which is an acronym for Comparative Evaluation Test Bed of Optimization and Analysis Routines for the Design of Structures. This manual describes for the user a step-by-step procedure for setting up the input data files and executing CometBoards to solve a structural design problem. The manual includes the organization of CometBoards; instructions for preparing input data files; the procedure for submitting a problem; illustrative examples; and several demonstration problems. A set of 29 structural design problems have been solved by using all the optimization methods available in CometBoards. A summary of the optimum results obtained for these problems is appended to this users manual. CometBoards, at present, is available for Posix-based Cray and Convex computers, Iris and Sun workstations, and the VM/CMS system.

Guptill, James D.↗
NASA NTRS2004

A Study of Penalty Function Methods for Constraint Handling with Genetic Algorithm

COMETBOARDS (Comparative Evaluation Testbed of Optimization and Analysis Routines for Design of Structures) is a design optimization test bed that can evaluate the performance of several different optimization algorithms. A few of these optimization algorithms are the sequence of unconstrained minimization techniques (SUMT), sequential linear programming (SLP) and the sequential quadratic programming techniques (SQP). A genetic algorithm (GA) is a search technique that is based on the principles of natural selection or "survival of the fittest". Instead of using gradient information, the GA uses the objective function directly in the search. The GA searches the solution space by maintaining a population of potential solutions. Then, using evolving operations such as recombination, mutation and selection, the GA creates successive generations of solutions that will evolve and take on the positive characteristics of their parents and thus gradually approach optimal or near-optimal solutions. By using the objective function directly in the search, genetic algorithms can be effectively applied in non-convex, highly nonlinear, complex problems. The genetic algorithm is not guaranteed to find the global optimum, but it is less likely to get trapped at a local optimum than traditional gradient-based search methods when the objective function is not smooth and generally well behaved. The purpose of this research is to assist in the integration of genetic algorithm (GA) into COMETBOARDS. COMETBOARDS cast the design of structures as a constrained nonlinear optimization problem. One method used to solve constrained optimization problem with a GA to convert the constrained optimization problem into an unconstrained optimization problem by developing a penalty function that penalizes infeasible solutions. There have been several suggested penalty function in the literature each with there own strengths and weaknesses. A statistical analysis of some suggested penalty functions is performed in this study. Also, a response surface approach to robust design is used to develop a new penalty function approach. This new penalty function approach is then compared with the other existing penalty functions.

Ortiz, Francisco↗
NASA NTRSDate not supplied

Probabilistic Calibration of Expensive Models using Efficiently Trained Surrogates

Calibration of computational models in the presence of uncertainty is often cast as a Bayesian inference problem and solved via sampling methods, e.g., Markov chain Monte Carlo. When the computational model is expensive, this task becomes intractable due to the large number of samples required to accurately estimate the posterior distribution of the calibration parameters. A popular solution to this problem is to use machine learning to develop a faster-to-evaluate, lower-fidelity substitute for the original model to serve as a surrogate while solving the inference problem. Although considered an offline cost, generating training data to construct this surrogate model can still be an expensive task in practice. An active learning algorithm is presented that focuses training on improving surrogate accuracy specifically in and around the bulk of the posterior distribution, as this is where the model is exercised during calibration. Candidate samples are drawn from families of distributions related to an approximation of the posterior. The sample maximizing predictive variance is then selected for evaluation by the original computational model, yielding a label for the training point. Iterating this approach increases efficiency relative to space filling designs (e.g., Latin hypercube sampling) by avoiding low probability points. Practical considerations are discussed, including the benefits of using a sequential Monte Carlo sampling approach, convergence heuristics, and the importance of both exploration and exploitation given that the true posterior is unknown a priori.

uncertainty quantification↗
NASA NTRS2012

Mars Aqueous Processing System

The goal of the Mars Aqueous Processing System (MAPS) is to establish a flexible process that generates multiple products that are useful for human habitation. Selectively extracting useful components into an aqueous solution, and then sequentially recovering individual constituents, can obtain a suite of refined or semi-refined products. Similarities in the bulk composition (although not necessarily of the mineralogy) of Martian and Lunar soils potentially make MAPS widely applicable. Similar process steps can be conducted on both Mars and Lunar soils while tailoring the reaction extents and recoveries to the specifics of each location. The MAPS closed-loop process selectively extracts, and then recovers, constituents from soils using acids and bases. The emphasis on Mars involves the production of useful materials such as iron, silica, alumina, magnesia, and concrete with recovery of oxygen as a byproduct. On the Moon, similar chemistry is applied with emphasis on oxygen production. This innovation has been demonstrated to produce high-grade materials, such as metallic iron, aluminum oxide, magnesium oxide, and calcium oxide, from lunar and Martian soil simulants. Most of the target products exhibited purities of 80 to 90 percent or more, allowing direct use for many potential applications. Up to one-fourth of the feed soil mass was converted to metal, metal oxide, and oxygen products. The soil residue contained elevated silica content, allowing for potential additional refining and extraction for recovery of materials needed for photovoltaic, semiconductor, and glass applications. A high-grade iron oxide concentrate derived from lunar soil simulant was used to produce a metallic iron component using a novel, combined hydrogen reduction/metal sintering technique. The part was subsequently machined and found to be structurally sound. The behavior of the lunar-simulant-derived iron product was very similar to that produced using the same methods on a Michigan iron ore concentrate, which demonstrates that lunar-derived material can be used in a manner similar to conventional terrestrial iron. Metallic iron was also produced from the Mars soil simulant. The aluminum and magnesium oxide products produced by MAPS from lunar and Mars soil simulants exhibited excellent thermal stability, and were shown to be capable of use for refractory oxide structural materials, or insulation at temperatures far in excess of what could be achieved using unrefined soils. These materials exhibited the refractory characteristics needed to support iron casting and forming operations, as well as other thermal processing needs. Extraction residue samples contained up to 79 percent silica. Such samples were successfully fused into a glass that exhibited high light transmittance.

Berggren, Mark↗