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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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Projection pursuit adaptation on polynomial chaos expansions

Here, the present work addresses the issue of accurate stochastic approximations in high-dimensional parametric space using tools from uncertainty quantification (UQ). The basis adaptation method and its accelerated algorithm in polynomial chaos expansions (PCE) were recently proposed to construct low-dimensional approximations adapted to specific quantities of interest (QoI). The present paper addresses one difficulty with these adaptations, namely their reliance on quadrature point sampling, which limits the reusability of potentially expensive samples. Projection pursuit (PP) is a statistical tool to find the “interesting” projections in high-dimensional data and thus bypass the curse-of-dimensionality. In the present work, we combine the fundamental ideas of basis adaptation and projection pursuit regression (PPR) to propose a novel method to simultaneously learn the optimal low-dimensional spaces and PCE representation from given data. While this projection pursuit adaptation (PPA) can be entirely data-driven, the constructed approximation exhibits mean-square convergence to the solution of an underlying governing equation and thus captures the supports and probability distributions associated with the physics constraints. The proposed approach is demonstrated on a borehole problem and a structural dynamics problem, demonstrating the versatility of the method and its ability to discover low-dimensional manifolds with high accuracy with limited data. In addition, the method can learn surrogate models for different quantities of interest while reusing the same data set.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Tradeoff between Intermolecular Interaction and Backbone Disorder by High Molecular Dipole Block for Improving Blend Morphology of Polymer Solar Cells

Constructing terpolymer has attracted increasing attention as a strategy to improve the performance of polymer solar cell. Terpolymer usually offers an opportunity to lower the frontier molecular orbital energy level, introduces additional absorption band and sometimes optimizes the morphology of the active blend. Generally, the additional segment in terpolymer backbone inevitably introduces backbone disorder, which causes entropy rises. However, selecting a suitable dipole unit introduces extra driving forces for crystallization by enhancing intermolecular interactions. This provides a handy knob for tradeoff between intermolecular interaction and backbone disorder, thus regulating the blend morphology. In this study, a high dipole and electron-deficient group of pyrrolo[3,4-f ]benzotriazole-5,7(6H)-dione (TzBI) is incorporated into the high-performance donor polymer and a series of terpolymers with different content of TzBI are designed. As expected, the morphology is optimized gradually for improving charge generation and charge transport, also suppressing charge recombination. The champion device with 10% TzBI exhibited a power conversion efficiency (PCE) of 18.36%, which is 5% increase compared to the controlled device. This study presents a charming terpolymer strategy by highly electron-deficient and high dipole segment to realize a tradeoff between intermolecular interaction and backbone disorder, facilitating the optimization of morphology and elevation of fill factor and device efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Neural chaos: A spectral stochastic neural operator

Building surrogate models for operators with uncertainty quantification capabilities is essential for many engineering applications where randomness–such as variability in material properties, boundary conditions, and initial conditions–is unavoidable. Polynomial Chaos Expansion (PCE) is widely recognized as a go-to method for constructing stochastic surrogates in both intrusive and non-intrusive ways, and it has recently been used in the context of operator learning. However, its application becomes challenging for complex or high-dimensional processes, as achieving accuracy requires higher-order polynomials, which can increase computational demand and/or the risk of overfitting. Furthermore, PCE requires specialized treatments to manage random variables that are not independent, and these treatments may be problem-dependent or may fail with increasing complexity. Here, in this work, we adopt the same formalism as the spectral expansion used in PCE; however, we replace the classical polynomial basis functions with neural network (NN) basis functions to leverage their expressivity. To achieve this, we propose an algorithm that identifies NN-parameterized basis functions in a purely data-driven manner, without any prior assumptions about the joint distribution of the random variables involved, whether independent or dependent, or about their marginal distributions. The proposed algorithm identifies each NN-parameterized basis function sequentially, ensuring they are orthogonal with respect to the data distribution. The basis functions are constructed directly on the joint stochastic variables without requiring a tensor product structure or assuming independence of the random variables. This approach may offer greater flexibility for complex stochastic models, while simplifying implementation compared to the tensor product structures typically used in PCE to handle random vectors. This is particularly advantageous given the current state of open-source packages, where building and training neural networks can be done with just a few lines of code and extensive community support. We demonstrate the effectiveness of the proposed scheme through several numerical examples of varying complexity and provide comparisons with classical PCE.

Polynomial chaos expansion↗
DOE OSTI2023

Seed‐Assisted Growth for Scalable and Efficient Perovskite Solar Modules

Perovskite solar modules (PSMs) have shown remarkable photovoltaic potentials, but they still suffer from large power conversion efficiency (PCE) loss on scale‐up and instability due to inferior uniformity and crystallization over large areas. Herein, the scalable production of efficient and stable PSMs using a suite of all‐scalable fabrication methods featuring a two‐step blade/dip‐coating approach to deposit the perovskite absorber layer is demonstrated. Rubidium chloride is introduced to embed (PbI 2 ) 2 RbCl complex seeds in the first‐deposited PbI 2 precursor, which assists in uniform crystallization of the perovskite layer with high crystallinity and reduced defect density over large areas. Following the optimization of RbCl additives, a champion PSM with 17.9% PCE on a 7.6 × 7.6 cm 2 substrate with a 37 cm 2 aperture area is achieved. Moreover, the RbCl‐incorporated PSMs demonstrate excellent reproducibility and stability under continuous 1 sun illumination. This work shows that the two‐step blade/dip coating is a promising method for producing high‐efficiency and stable PSMs on an industrially relevant scale.

Energy & Fuels↗
DOE OSTI2020

3,4‐Dicyanothiophene—a Versatile Building Block for Efficient Nonfullerene Polymer Solar Cells

Abstract In this contribution, a versatile building block, 3,4‐dicyanothiophene (DCT), which possesses structural simplicity and synthetic accessibility for constructing high‐performance, low‐cost, wide‐bandgap conjugated polymers for use as donors in polymer solar cells (PSCs), is reported. A prototype polymer, PB3TCN‐C66, and its cyano‐free analogue polymer PB3T‐C66, are synthesized to evaluate the potential of using DCT in nonfullerene PSCs. A stronger aggregation property in solution, higher thermal transition temperatures with higher enthalpies, a larger dipole moment, higher relative dielectric constant, and more linear conformation are exhibited by PB3TCN‐C66. Solar cells employing IT‐4F as the electron acceptor offer power conversion efficiencies (PCEs) of 11.2% and 2.3% for PB3TCN‐C66 and PB3T‐C66, respectively. Morphological characterizations reveal that the PB3TCN‐C66:IT‐4F blend exhibits better π–π paracrystallinity, a contracted domain size, and higher phase purity, consistent with its higher molecular interaction parameter, derived from thermodynamic calculations. Moreover, PB3TCN‐C66 offers a higher open‐circuit voltage and reduced energy loss than most state‐of‐the‐art wide‐bandgap polymers, without the need of additional electron‐withdrawing substituents. Two additional polymers derived from DCT also demonstrate promising performance with a higher PCE of 13.4% being achieved. Thus, DCT represents a versatile and promising building block for constructing high‐performance, low‐cost, conjugated polymers for application in PSCs.

Zhang, Bo↗
DOE OSTI2024

Supramolecular design principles in pseudohalides for high-performance perovskite solar mini modules

In this work, we reveal the role of non-covalent interactions, which are known to play important roles in supramolecular phenomena, in achieving efficient perovskite surface and grain boundary passivation. By using a series of pseudohalides, we find that trifluoroacetate (TFA - ) provides the strongest binding to iodide vacancies by means of non-covalent hydrogen bonding and dispersion interactions. By exploiting additional non-covalent dispersion and hydrophobic interactions in aromatic 3,3-diphenylpropylammonium (DPA + ), we present a dual-ion passivation strategy that not only minimizes the non-radiative recombination center and local chemical inhomogeneities but also induces preferentially oriented growth of α-FAPbI 3 lattice. Further, this leads to an outstanding power conversion efficiency (PCE) of 25.63% with an exceptional open-circuit voltage of 1.191 V in a perovskite solar cell with a small area, while perovskite solar mini modules with aperture areas of 25 and 64cm 2 achieved PCE of 22.47% (quasi-steady-state [QSS]-certified 20.50%) and 20.88%, respectively, with outstanding stability under high-humidity conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Optimized NiTe 2 /Ni back contacts via chemical deposition for high performance CdTe solar cells

The development of efficient and stable back contacts remains a major challenge in achieving high performance and long-term stability of CdTe thin-film solar cells. Here, this work revisits the formation of NiTe 2 by chemical bath deposition (CBD) as a back contact for CdTe devices. An optimized CBD recipe, based on high-purity precursors and the addition of copper chloride directly into the bath, was developed and applied to fabricate Cu-doped CdTe solar cells. A modified Cu-free methodology was also applied to Group V doped absorbers. The process included pinhole filling, ion milling, CBD, annealing, and sputtering to form a low-barrier back contact. Devices fabricated using this method achieved consistent open-circuit voltages (V oc ) above 800 mV and fill factors (FF) exceeding 70%. The best Cu-doped devices reached power conversion efficiencies (PCE) above 18 %, and preliminary results with Group V-doped material demonstrated compatibility of the method with high-efficiency, state-of-the-art CdTe devices. This study shows that NiTe 2 /Ni back contacts, formed via an optimized chemical process followed by sputtering of Ni, represent a promising pathway for achieving low-barrier and potentially stable back contacts in modern CdTe photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2023

Developing Efficient Benzene Additives for 19.43% Efficiency of Organic Solar Cells by Crossbreeding Effect of Fluorination and Bromination

Employing volatile solid additives have emerged as a promising method to optimize the morphology and improve the performance of organic solar cells (OSCs). However, principles governing the efficient design of solid additives remain elusive. In this work, the programmed fluorination and/or bromination on benzene core to develop efficient additives for OSCs is reported. The programmed fluorination and/or bromination endow the five halogen benzene derivatives, 1,3,5-trifluorobenzene, hexafluorobenzene, 1,3,5-tribromo-2,4,6-trifluorobenzene (TFTB), 1,3,5-tribromobenzene, and hexabromobenzene, with different melting and boiling points, volatility, as well as interactions with the host blend. Studies indicate that the additives with extremely high and low volatility are almost powerless and even detrimental to the morphology evolution. Among them, the combination of fluorine and bromine atoms on TFTB not only enables the more appropriate m.p./b.p. and volatility, but also exerts stronger molecular interactions with the host blend, giving rise to higher ordered molecular packing and more favorable morphology. Importantly, TFTB exhibits good universality to optimize the performances of OSCs with high power conversion efficiencies (PCEs; over 18%) in a group of binary blend systems, and an impressive PCE of 19.43% in the ternary PBTz-F:PM6:L8-BO system.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Inorganic cesium lead mixed halide based perovskite solar materials modified with functional silver iodide

Inorganic CsPbIBr 2 perovskites have recently attracted enormous attention as a viable alternative material for optoelectronic applications due to their higher efficiency, thermal stability, suitable bandgap, and proper optical absorption. However, the CsPbIBr 2 perovskite films fabricated using a one-step deposition technique is usually comprised of small grain size with a large number of grain boundaries and compositional defects. In this work, silver iodide (AgI) will be incorporated as an additive into the CsPbIBr 2 perovskite precursor solution to prepare the unique perovskite CsI(PbBr 2 ) 1-x (AgI) x . The AgI additive in the precursor solution works as a nucleation promoter which will help the perovskite to grow and merge into a continuous film with reduced defects. With detailed characterizations, we found that incorporating AgI additive resulted in a uniform perovskite film with fewer grain boundaries, increased grain size, crystallinity, optical absorption while decreasing carrier recombination and trap density. Using the AgI in an optimum amount, we fabricated CsPbIBr 2 perovskite solar cells (PSCs) with a simple structure and achieved a power conversion efficiency (PCE) of 7.2% with a reduced hysteresis index. This work offers an alternative approach towards preparing high-quality CsPbIBr 2 perovskite films for solar cells with higher stability and other optoelectronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Computational evolution of high-performing unfused non-fullerene acceptors for organic solar cells

Materials optimization for organic solar cells (OSCs) is a highly active field, with many approaches using empirical experimental synthesis, computational brute force to screen a subset of chemical space, or generative machine learning methods that often require significant training sets. While these methods may find high-performing materials, they can be inefficient and time-consuming. Genetic algorithms (GAs) are an alternative approach, allowing for the “virtual synthesis” of molecules and a prediction of their “fitness” for some property, with new candidates suggested based on good characteristics of previously generated molecules. In this work, a GA is used to discover high-performing unfused non-fullerene acceptors (NFAs) based on an empirical prediction of power conversion efficiency (PCE) and provides design rules for future work. The electron-withdrawing/donating strength, as well as the sequence and symmetry, of those units are examined. The utilization of a GA over a brute-force approach resulted in speedups up to 1.8 × 10 12 . New types of units, not frequently seen in OSCs, are suggested, and in total 5426 NFAs are discovered with the GA. Of these, 1087 NFAs are predicted to have a PCE greater than 18%, which is roughly the current record efficiency. While the symmetry of the sequence showed no correlation with PCE, analysis of the sequence arrangement revealed that higher performance can be achieved with a donor core and acceptor end groups. Future NFA designs should consider this strategy as an alternative to the current A-D-A'-D-A architecture.

14 SOLAR ENERGY↗
DOE OSTI2024

Unraveling the Formation Mechanisms of Highly Oriented Tin Perovskite with a 3D-over-2D Heterostructure

Tin-based perovskites (TinPVKs) have become the most promising candidates for lead-free perovskite solar cells, owing to its low toxicity and improved photovoltaic performance. However, due to the absence of 4f shell, TinPVKs suffer from uncontrolled crystallization, limiting the power conversion efficiency (PCE) of tin perovskite solar cells (TinPSCs). Here, we systematically study the ligand regulated crystallization process of TinPVK. We find that with elongated spin time, TinPVK crystals undergo reorientation and lateral growth. 3D α-phase FASnI3 and 2D (n = 2) and 2D (n = 1) phases emerge sequentially to form a “3D-over-2D” heterostructure via a proposed “diffusion-propagation” mechanism. TinPSCs exhibit improved open circuit voltage (V OC ) due to favorable energy level alignment of the 3D-over-2D heterostructure, with a champion PCE value of 13.07% and T 80 value of over 1200 h. Furthermore, this work provides mechanistic insights on controlled crystallization and heterostructure formation of TinPVKs, paving the way toward high-efficiency TinPSCs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

LA17-V-InverseRadTransportProblem-PD2Kb. Final Project Report

In the inverse radiation transport problem, a radiation signal emanating from an unknown object is used to reconstruct geometric and material parameters of the object , e.g., the mass of special nuclear material (SNM), the isotopic composition of the SNM (e.g., the enrichment of 235U), the thickness of shielding, etc. The inverse radiation transport problem is one of the most fundamental and important in the emergency response mission, and has been addressed in previous NA-22 and NA-42/84 investments by using derivative-free optimization methods. Our project was aimed at (i) consolidating previous work by applying polynomial chaos expansion (PCE) for reducing significantly the number of forward model simulations required by derivative-free optimization methods; (ii) developing a general-purpose framework and stand-alone software for solving the inverse radiation transport problem by applying a new “predictive modeling” methodology (predictive modeling of coupled multi-physics systems, PM_CMPS) which enables the fusing of experimental and computational information; and (iii) developing several benchmarks (for unscattered gamma rays) for demonstrating the quantification of non-Gaussian features (e.g., skewness and kurtosis, which characterize asymmetries and long tails) of response distributions by deterministically and efficiently propagating parameter uncertainties (covariances and higher-order moments, where available) using high-order sensitivities computed by the recently developed comprehensive adjoint sensitivity analysis methodology (C-ASAM). With regard to (i), application of PCE, the most significant accomplishment of this project was an implementation of PCE into INVERSE that significantly reduced computation time for the DiffeRential Evolution Adaptive Metropolis (DREAM) and Differential Evolution (DE) methods. For inverse transport problems with measurements of neutron leakage, neutron multiplication, and neutron-induced gamma-rays, the solution times for the DREAM and DE methods were reduced by factors of 30-300, reducing run times from hours to minutes while maintaining the same accuracy as the standard (non-PCE) DREAM and DE. Speedups were further improved by exploring sparse grid quadrature sets using the Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN (Tasmanian) toolset. An initial exploration of sparse grids indicated that further speedups factors of 5-10 are obtainable. The implementation of PCE in INVERSE is not in a form that users can easily access. With regard to (ii), solving the inverse problem using a predictive modeling paradigm, the most significant accomplishment of this project were the derivation and implementation of adjoint-based second derivatives in neutron and photon transport theory. There are two codes that compute these derivatives. SENSPG computes them for uncollided gamma rays and SENSMG computes them for neutron leakage. SENSMG is open-source code available on github. Other significant accomplishments included a stand-alone code, MULTI-PRED, that implements the predictive modeling paradigm, along with a detailed manual. The code was implemented in the existing INVERSE code for inverse problems, but a head-to-head comparison of inverse methods was not achieved. We also derived and implemented the capability to compute sensitivities for multiplicity measurements into the SENSMG code, and this capability was used in a data assimilation application, but it was not used for solving inverse problems. With regard to (iii), developing benchmarks to demonstrate the importance of high-order sensitivity and uncertainty analysis, the most significant accomplishment of this project were two test problems that showed how important second-order sensitivities are.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Quantitative relationships between film morphology, charge carrier dynamics, and photovoltaic performance in bulk-heterojunction binary vs. ternary acceptor blends

Addressing pertinent and perplexing questions regarding why nonfullerene acceptors (NFAs) promote higher power conversion efficiencies (PCEs) than traditional fullerenes and how photoactive bulk heterojunction (BHJ) film morphology, charge photogeneration, and recombination dynamics dictate solar cell performance have stimulated many studies of polymer solar cells (PSCs), yet quantitative relationships remain limited. Better understanding in these areas offers the potential to advance materials design and device engineering, afford higher PCEs, and ultimate commercialization. Here we probe quantitative relationships between BHJ film morphology, charge carrier dynamics, and photovoltaic performance in model binary and ternary blend systems having a wide bandgap donor polymer, a fullerene, and a promising NFA. We show that optimal PC 71 BM incorporation in a PBDB-TF:ITIC-Th binary system matrix retains the original π-face-on orientation, ITIC-Th crystallinity and BHJ film crystallite dimensions, and reduces film upper surface ITIC-Th segregation. Such morphology changes together simultaneously increase hole (μ h ) and electron (μ e ) mobilities, facilitate light-activated ITIC-Th to PC 71 BM domain electron delocalization, reduce free charge carrier (FC) bimolecular recombination (BR) within PBDB-TF:ITIC-Th mixed regions, and increase FC extraction pathways viaPBDB-TF:PC 71 BM pairs. The interplay of these effects yields significantly enhanced inverted cell short-circuit current density (J SC ), fill factor (FF), and PCE. Unexpectedly, we also find that excessive PC 71 BM in the PBDB-TF:ITIC-Th binary system alters the PBDB-TF orientation to π-edge-on, increases large scale PC 71 BM-rich aggregations and BHJ upper surface PC 71 BM composition. Further, these morphology changes increase parasitic decay processes such as intersystem crossing from photoexcited PC 71 BM, compromising the J SC , FF, and PCE metrics. ITIC-Th X-ray diffraction reveals a unique sidechain-dominated molecular network with previously unknown sidechain-end group stacking, rationalizing the STEM and GIWAXS results, photophysics, and the high μ e . DFT computation reveals charge transfer networks within ITIC-Th crystallites, supporting excited-state electron delocalization from ITIC-Th to PC 71 BM. This structure–property understanding leads to a newly reported NFA blend with PCE near 17%.

14 SOLAR ENERGY↗
DOE OSTI2023

Integrated Large-Scale Data Management Platform for Photovoltaic Power Conversion Equipment (PCE) Reliability Data

To meet the demand for accuracy and real-time capability of PV system degradation evaluation, massive volume data is needed to run high-fidelity and high-efficiency simulations and perform advanced data analysis. However, PV farm operators have a series of difficulties with PV inverter data, such as data collection from multiple channels, massive data storage, data management and massive data analysis. To address these challenges, we developed an integrated data management platform capable of data acquisition, processing, storage, query, and performing big data analysis utilizing AI algorithms. The platform can also achieve data correctness verification and provide an effective distributed data management solution to retrieve massive data and establish a connection to distributed computational frameworks.

data management platform↗
DOE OSTI2023

Integrated Large-Scale Data Management Platform for Photovoltaic Power Conversion Equipment (PCE) Reliability Data: Preprint

To meet the demand for accuracy and real-time capability of PV system degradation evaluation, massive volume data is needed to run high-fidelity and high-efficiency simulations and perform advanced data analysis. However, PV farm operators have a series of difficulties with PV inverter data, such as data collection from multiple channels, massive data storage, data management and massive data analysis. To address these challenges, we developed an integrated data management platform capable of data acquisition, processing, storage, query, and performing big data analysis utilizing AI algorithms. The platform can also achieve data correctness verification and provide an effective distributed data management solution to retrieve massive data and establish a connection to distributed computational frameworks.

data management↗
DOE OSTI2022

Electrical edge effect induced photocurrent overestimation in low-light organic photovoltaics

In many literatures, the short-circuit current (J SC ) of indoor organic photovoltaics is overestimated, leading to severely wrong device performance evaluation and analysis. In this work, based on the equivalent circuit model, we demonstrate that electrical edge effect is sensitive to both transverse surface resistance and light intensity. At low light intensity, the electrical edge effect could lead to J SC being significantly overestimated, i.e., by 100% and even more. We show that for a PM6:Y6 device capped with a MoOX layer, when measured under 0.01 sun, the usually overlooked interface doping mechanism would lead to J SC and PCE overestimation by 51% and 15%, respectively. Besides, we show that the magnitude of J SC overestimation drastically increases with high photoactive-layer surface roughness. This work emphasized the significant electrical edge effect on J SC evaluations for low-light solar cells and is conducive to understanding the intrinsic mechanism of edge effect, promoting a healthier development of organic photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2024

Eliminating the Burn‐in Loss of Efficiency in Organic Solar Cells by Applying Dimer Acceptors as Supramolecular Stabilizers

Abstract The meta‐stable active layer morphology of organic solar cells (OSCs) is identified as the main cause of the rapid burn‐in loss of power conversion efficiency (PCE) during long‐term device operation. However, effective strategies to eliminate the associated loss mechanisms from the initial stage of device operation are still lacking, especially for high‐efficiency material systems. Herein, the introduction of molecularly engineered dimer acceptors with adjustable thermal transition properties into the active layer of OSCs to serve as supramolecular stabilizers for regulating the thermal transitions and optimizing the crystallization of the absorber composites is reported. By establishing intimate π‐π interactions with small‐molecule acceptors, these stabilizers can effectively reduce the trap‐state density (N t ) in the devices to achieve excellent PCEs over 19%. More importantly, the lowN t associated with an initially optimized morphology can be maintained under external stresses to significantly reduce the PCE burn‐in loss in devices. This research reveals a judicious approach to improving OPV stability by establishing a comprehensive correlation between material properties, active‐layer morphology, and device performance, for developing burn‐in‐free OSCs.

Chemistry↗