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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A selective WDR5 degrader inhibits acute myeloid leukemia in patient-derived mouse models

Interactions between WD40 repeat domain protein 5 (WDR5) and its various partners such as mixed lineage leukemia (MLL) and c-MYC are essential for sustaining oncogenesis in human cancers. However, inhibitors that block protein-protein interactions (PPIs) between WDR5 and its binding partners exhibit modest cancer cell killing effects and lack in vivo efficacy. Here, we present pharmacological degradation of WDR5 as a promising therapeutic strategy for treating WDR5-dependent tumors and report two high-resolution crystal structures of WDR5-degrader-E3 ligase ternary complexes. We identified an effective WDR5 degrader via structure-based design and demonstrated its in vitro and in vivo antitumor activities. On the basis of the crystal structure of an initial WDR5 degrader in complex with WDR5 and the E3 ligase von Hippel–Lindau (VHL), we designed a WDR5 degrader, MS67, and demonstrated the high cooperativity of MS67 binding to WDR5 and VHL by another ternary complex structure and biophysical characterization. MS67 potently and selectively depleted WDR5 and was more effective than WDR5 PPI inhibitors in suppressing transcription of WDR5-regulated genes, decreasing the chromatin-bound fraction of MLL complex components and c-MYC, and inhibiting the proliferation of cancer cells. In addition, MS67 suppressed malignant growth of MLL-rearranged acute myeloid leukemia patient cells in vitro and in vivo and was well tolerated in vivo. Collectively, our results demonstrate that structure-based design can be an effective strategy to identify highly active degraders and suggest that pharmacological degradation of WDR5 might be a promising treatment for WDR5-dependent cancers.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Gradient-informed Hamiltonian Monte Carlo for multicomponent CALPHAD model optimization and uncertainty quantification

CALPHAD model parameter optimization is inherently challenging due to non-smooth objective functions, high-dimensional parameter spaces, and the need for uncertainty quantification (UQ). Traditional weighted nonlinear least squares approaches are computationally efficient but local, whereas black-box global optimizers and ensemble Markov Chain Monte Carlo (MCMC) methods provide broader exploration at substantial computational cost. The objective of this work is to combine the global exploration capability of gradient-informed Hamiltonian Monte Carlo – specifically the No-U-Turn Sampler (NUTS) – with local deterministic refinement using BFGS to efficiently optimize multicomponent CALPHAD models with minimal manual intervention. Analytic gradients are computed via the Jansson derivative framework. The methodology is demonstrated on the Cr—Fe binary system and extended to the Cr—Fe—Ni ternary system with 32 degrees of freedom. For Cr—Fe, NUTS achieves comparable or superior optimality relative to ensemble MCMC while requiring over an order-of-magnitude fewer likelihood evaluations. Parameter uncertainties are quantified through NUTS sampling and propagated to thermodynamic observables using local expansion, demonstrating a novel modular approach that combines binary and ternary parameter subsets without requiring global relaxation. These results establish gradient-informed exploration as a scalable strategy for multicomponent CALPHAD optimization and provide a practical route towards efficient higher-order database development with quantified uncertainty.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Saga of Endocrine FGFs

Fibroblast growth factors (FGFs) are cell-signaling proteins with diverse functions in cell development, repair, and metabolism. The human FGF family consists of 22 structurally related members, which can be classified into three separate groups based on their action of mechanisms, namely: intracrine, paracrine/autocrine, and endocrine FGF subfamilies. FGF19, FGF21, and FGF23 belong to the hormone-like/endocrine FGF subfamily. These endocrine FGFs are mainly associated with the regulation of cell metabolic activities such as homeostasis of lipids, glucose, energy, bile acids, and minerals (phosphate/active vitamin D). Endocrine FGFs function through a unique protein family called klotho. Two members of this family, α-klotho, or β-klotho, act as main cofactors which can scaffold to tether FGF19/21/23 to their receptor(s) (FGFRs) to form an active complex. There are ongoing studies pertaining to the structure and mechanism of these individual ternary complexes. These studies aim to provide potential insights into the physiological and pathophysiological roles and therapeutic strategies for metabolic diseases. Herein, we provide a comprehensive review of the history, structure–function relationship(s), downstream signaling, physiological roles, and future perspectives on endocrine FGFs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Improving Cooperative Interactions Between Halogenated Aromatic Additives and Aromatic Side Chain Acceptors for Realizing 19.22% Efficiency Polymer Solar Cells

Processing additive plays an important role in the standard operation procedures for fabricating top performing polymer solar cells (PSCs) through efficient interactions with key photovoltaic materials. However, improving interaction study of acceptor materials to high performance halogenated aromatic additives such as diiodobenzene (DIB) is a widely neglected route for molecular engineering toward more efficient device performances. Here, in this work, two novel Y-type acceptor molecules of BTP-TT and BTP-TTS with different aromatic side chains on the outer positions are designed and synthesized. The resulting aromatic side chains significantly enhanced the interactions between the acceptor molecules and DIB through an arene/halogenated arene interaction, which improved the crystallinity of the acceptor molecules and induced a polymorph with better photovoltaic performances. Thus, high power conversion efficiencies (PCEs) of 18.04% and 19.22% are achieved in binary and ternary blend devices using BTP-TTS as acceptor and DIB as additive. Aromatic side chain engineering for improving additive interactions is proved to be an effective strategy for achieving much higher performance photovoltaic materials and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Versatile Approach to Stabilize Liquid–Liquid Interfaces using Surfactant Self-Assembly

Stabilizing liquid–liquid interfaces, whether between miscible or immiscible liquids, is crucial for a wide range of applications, including energy storage, microreactors, and biomimetic structures. Here, in this study, a versatile approach for stabilizing the water-oil interface is presented using the morphological transitions that occur during the self-assembly of anionic, cationic, and nonionic surfactants mixed with fatty acid oils. The morphological transitions underlying this approach are characterized and extensively studied through small-angle X-ray scattering (SAXS), rheometry, and microscopy techniques. Dissipative particle dynamics (DPD) as a simulation tool is adopted to investigate these morphological transitions both in the equilibrium ternary system as well as in the dynamic condition of the water-oil interface. Such a versatile strategy holds promise for enhancing applications such as liquid-in-liquid 3D printing. Moreover, it has the potential to revolutionize a wide range of fields where stabilizing liquid–liquid interfaces not only offers unprecedented opportunities for fine-tuning nanostructural morphologies but also imparts interesting practical features to the resulting liquid shapes. These features include perfusion capabilities, self-healing, and porosity, which could have significant implications for various industries.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A versatile approach to stabilize liquid-liquid interfaces using surfactant self-assembly

Stabilizing liquid–liquid interfaces, whether between miscible or immiscible liquids, is crucial for a wide range of applications, including energy storage, microreactors, and biomimetic structures. In this study, a versatile approach for stabilizing the water-oil interface is presented using the morphological transitions that occur during the self-assembly of anionic, cationic, and nonionic surfactants mixed with fatty acid oils. The morphological transitions underlying this approach are characterized and extensively studied through small-angle X-ray scattering (SAXS), rheometry, and microscopy techniques. Dissipative particle dynamics (DPD) as a simulation tool is adopted to investigate these morphological transitions both in the equilibrium ternary system as well as in the dynamic condition of the water-oil interface. Such a versatile strategy holds promise for enhancing applications such as liquid-in-liquid 3D printing. Moreover, it has the potential to revolutionize a wide range of fields where stabilizing liquid–liquid interfaces not only offers unprecedented opportunities for fine-tuning nanostructural morphologies but also imparts interesting practical features to the resulting liquid shapes. These features include perfusion capabilities, self-healing, and porosity, which could have significant implications for various industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Active learning of ternary alloy structures and energies

Abstract Machine learning models with uncertainty quantification have recently emerged as attractive tools to accelerate the navigation of catalyst design spaces in a data-efficient manner. Here, we combine active learning with a dropout graph convolutional network (dGCN) as a surrogate model to explore the complex materials space of high-entropy alloys (HEAs). We train the dGCN on the formation energies of disordered binary alloy structures in the Pd-Pt-Sn ternary alloy system and improve predictions on ternary structures by performing reduced optimization of the formation free energy, the target property that determines HEA stability, over ensembles of ternary structures constructed based on two coordinate systems: (a) a physics-informed ternary composition space, and (b) data-driven coordinates discovered by the Diffusion Maps manifold learning scheme. Both reduced optimization techniques improve predictions of the formation free energy in the ternary alloy space with a significantly reduced number of DFT calculations compared to a high-fidelity model. The physics-based scheme converges to the target property in a manner akin to a depth-first strategy, whereas the data-driven scheme appears more akin to a breadth-first approach. Both sampling schemes, coupled with our acquisition function, successfully exploit a database of DFT-calculated binary alloy structures and energies, augmented with a relatively small number of ternary alloy calculations, to identify stable ternary HEA compositions and structures. This generalized framework can be extended to incorporate more complex bulk and surface structural motifs, and the results demonstrate that significant dimensionality reduction is possible in thermodynamic sampling problems when suitable active learning schemes are employed.

Chemistry↗
DOE OSTI2023

19.28% Efficiency and Stable Polymer Solar Cells Enabled by Introducing an NIR–Absorbing Guest Acceptor

Here, a near-infrared (NIR)-absorbing small-molecule acceptor (SMA) Y-SeNF with strong intermolecular interaction and crystallinity is developed by combining selenophene-fused core with naphthalene-containing end-group, and then as a custom-tailor guest acceptor is incorporated into the binary PM6:L8-BO host system. Y-SeNF shows a 65 nm red-shifted absorption compared to L8-BO. Thanks to the strong crystallinity and intermolecular interaction of Y-SeNF, the morphology of PM6:L8-BO:Y-SeNF can be precisely regulated by introducing Y-SeNF, achieving improved charge-transporting and suppressed non-radiative energy loss. Consequently, ternary polymer solar cells (PSCs) offer an impressive device efficiency of 19.28% with both high photovoltage (0.873 V) and photocurrent (27.88 mA cm –2 ), which is one of the highest efficiencies in reported single-junction PSCs. Notably, ternary PSC has excellent stability under maximum-power-point tracking for even over 200 h, which is better than its parental binary devices. The study provides a novel strategy to construct NIR-absorbing SMA for efficient and stable PSCs toward practical applications.

14 SOLAR ENERGY↗
DOE OSTI2021

Dynamic Process Intensification via Data-Driven Dynamic Optimization: Concept and Application to Ternary Distillation

Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of the process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation that ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI strategy (Do-DPI) that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. Here, an extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.

42 ENGINEERING↗
DOE OSTI2024

Improving luminescence response in ZnGeN 2 /GaN superlattices: defect reduction through composition control

Abstract Color-mixed (cm) light-emitting diodes (LEDs) are theoretically the most efficient white light emitters, projected to improve white light luminous efficacy by 34% compared to incumbent phosphor converted LEDs. Since white light technology is pervasive and essential, small improvements in LED technology can result in energy savings. However, cm-LEDs are not yet realized due to poor efficacy in green and amber emitting materials, a spectral region colloquially referred to as the Green Gap. ZnGeN 2 is nearly isostructural and closely lattice-matched to GaN and can be heteroepitaxially integrated with existing GaN devices; ZnGeN 2 /GaN hybrid structures are theorized to emit green (~530 nn) light with a spontaneous emission rate 4.6–4.9 times higher than traditional InGaN LEDs when incorporated into III-N LED structures. In this report we demonstrate the molecular beam epitaxy (MBE) growth of GaN and ZnGeN 2 superlattices, an important step towards realizing multiple quantum well structures required for efficient LEDs. Elemental analysis, including atom probe tomography, shows that Ga and Ge are observed in both ZnGeN 2 and GaN layers, degrading the structural uniformity. The lack of elemental abruptness also leads to increased defect luminescence and reabsorption of band edge luminescence. The source of unintentional Ga distributed throughout the ZnGeN 2 layers was identified as excess flux escaping from around the closed MBE shutter. The source of unintentional Ge, which tended to incorporate as a single delta-doped layer in GaN, was identified as Ge riding along the cyclical metal-rich Ga adlayer used for high quality GaN, incorporating during subsequent nitrogen-rich growth step. Modifying the growth strategy results in improved structural quality, elemental abruptness, and luminescence response. This realization of structurally and elementally abrupt interfaces demonstrates the potential of heteroepitaxially integrated binary and ternary nitrides for energy-relevant devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Editors’ Choice—Review—Designing Defects and Diffusion through Substitutions in Metal Halide Solid Electrolytes

Ternary metal halides A 3 MX 6 , ( A = Li + , Na + ; M = trivalent metal; X = halide) are a promising family of solid electrolytes for potential applications in all-solid-state batteries. Recent research efforts have demonstrated that chemical substitution at all three sites is an effective strategy to controlling battery-relevant material properties. The A 3 MX 6 family exhibits a wide breadth of structure and anion sublattice types, making it worthwhile to comprehend how chemical substitutions manifest desirable functional properties including ion transport, electrochemical stability, and environmental tolerance. Yet, a cohesive understanding of the materials design principles for these substitutions have not yet been developed. Here, we bring together prior literature focused on chemical substitutions in the A 3 MX 6 ternary metal halide solid electrolytes. Using materials chemistry perspectives and principles, we aim to provide insights into the relationships between crystal structure, choice of substituting ions and the extent of substitutions, ionic conductivity, and electrochemical stability. We further present targeted approaches to future substitution studies to enable transformative advances in A 3 MX 6 solid electrolytes and all-solid-state batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Elastic NaxMoS2-carbon-BASE triple interface direct robust solid-solid interface for all-solid-state Na-S batteries

The promises of all-solid-state (ASS) sodium batteries for the next generation energy storage are widely recognized but their developments have been severely constrained by the difficulties to design favorable solid-solid interfaces for unhindered Na-ion transport. Using the most promising ß?-Al2O3 solid state electrolyte (BASE) as a platform, we demonstrate here a triple nanojunction strategy that provides simultaneous strong Na adhesion and continuous Na-ions diffusion at solid-solid interface. Such triple junctions (NaxMoS2-carbon-BASE) were constructed by adhering ternary composite Na anodes containing dispersed 3 wt% MoS2 and 3 wt% carbon on BASE, and provide nearly complete adhesion of Na on BASE with a much smaller contact angle (~ 45o vs. 120o of pristine Na). The composite Na anodes exhibited ~ 3 times improved elastic property and the synergy of NaxMoS2 and carbon provides the required ionic and electronic diffusion channels at solid-solid interface, which significantly improve Na utilization and resist premature failure due to loss of solid-solid contact as Na shrink during high capacity stripping. As a result, Na metal at the triple junction exhibited more than five time reduced charge transfer resistance and at least 200 hours stable battery cycling at practical current densities. The novel anode architecture also enabled high capacity cycling of prototype ASS sodium sulfur batteries when coupled with advanced sulfur cathodes containing intrinsic Na-ions diffusion channels and redox catalytic mediators, leading to stable cycling with specific capacity of 1110 mAh g-1.

ß”-Al2O3 solid electrolyte, solid state batteries,↗
DOE OSTI2026

Leveraging large language models to address data scarcity in machine learning for graphene synthesis

Machine learning in experimental materials science faces significant challenges due to the scarcity of data, which are costly and time-consuming to generate, particularly when relying on in-house experiments. Literature data mining offers a potential solution but introduces issues like mixed data quality, inconsistent formats, and non-uniform reporting of synthesis parameters, resulting in partially missing and heterogeneous features across the dataset. Here, we propose data imputation and feature engineering methods that employ pre-trained large language models (LLMs) to enhance machine learning performance on scarce, heterogeneous datasets, demonstrated on graphene CVD synthesis data and the ML-HydPARK hydrogen storage dataset. GPT models perform data imputation via tailored prompting and semantic normalization of inconsistently reported features through embeddings, for example, to harmonize the complex nomenclature of CVD substrates. Beyond yielding more diverse and richer feature representations than traditional methods such as K-nearest neighbors (KNN) and Multivariate Imputation by Chained Equations (MICE), LLM-based data imputation is evaluated against dataset characteristics and prompting strategies. We vary the level of autonomy granted to the LLM, from generic prompting that leverages pre-trained knowledge for autonomous data generation to data-informed prompting that constrains outputs using target-specific information, and demonstrate which level of autonomy yields superior imputation performance across datasets and feature types. The proposed data engineering methods markedly improve downstream performance; for example, in graphene layer number classification using a support vector machine (SVM), binary accuracy increases from 39% to 65% and ternary accuracy from 52% to 72%. Fine-tuning experiments on both datasets show that combining our proposed LLM-based data imputation and feature encoding methods with numerical machine learning predictors outperforms standalone fine-tuned LLM predictors in data-scarce settings. The proposed strategies emphasize data enhancement techniques rather than refining learning architectures or regularizing loss functions, offering a broadly applicable framework for improving machine learning performance on scarce, inhomogeneous datasets.

Chemical vapor deposition↗
DOE OSTI2025

Hybridization Assessment of Trybrid Pumped Storage Hydropower System—Part 1: A Case Study of Corral Summit

This report is a part of the deliverables for technical assistance provided to Cat Creek Energy for the Coral Summit Trybrid (Triple Hybrid-Pumped Storage Hydropower, Battery Energy Storage System, and photovoltaic solar energy) energy project. This report explores the operational benefits and challenges of hybridizing an open loop PSH (200MW) located at Mackay, Custer County, Idaho with solar PV (Ground mount 300MW and floating 40MW) and battery (720MWhr). This document reports two activities performed as a part of the hybridization assessment task 1) optimal resource allocation and energy management strategy, and 2) power quality and reliability assessment. From optimal resource allocation and energy management strategy (activity 1), the following key findings can be observed: • Conventional PSH (CPSH) with two reversible pump turbines and separate penstocks can provide required flexibility equivalent to that from two ternary PSH with separate penstock. With single unit CPSH, upper reservoir head cannot be maintained accurately, the variation of water level is rapid and pump mode flexibility is not available. These disadvantages can be overcome by single unit TPSH. However, using two CPSH units with separate penstocks also overcome these disadvantages with the formation of the hydraulic short circuit between two conventional units. • Flooding of the lower reservoir is a severe concern when considering continuous operation for black start. This limits the duration of continuous operation from PSH alone to around 50 hours. Due to the complementary PV and battery action, the duration of continuous operation and smooth power output can be extended. • An optimization problem is framed that maximizes the power output on an hourly basis while minimizing constraint violations and respecting seasonal variations of solar PV and load profiles . Two value streams, arbitrage and baseload generation are served by this profile. It was uncovered that for smooth power output during regular operation, PV curtailment will be required, or the battery capacity needs to be increased above 90MW to accommodate additional PV. From power quality and reliability assessment (activity 2) the following takeaway points can be observed: • The Trybrid, when integrated at the Lost River bus, and limited to 250MW in generation mode and -150MW in the pump mode, causes no violation of voltage or flow.

13 - HYDRO ENERGY↗
DOE OSTI2020

Ternary PtIrNi Catalysts for Efficient Electrochemical Ammonia Oxidation

Due to high energy density, carbon-free feature, and easiness to be liquefied, ammonia (NH 3 ) has proved to be an effective alternative to hydrogen in low temperature fuel cells via its direct the ammonia oxidation reaction (AOR) for electricity generation. However, the kinetically sluggish AOR has prohibitively hindered the attractive direct ammonia fuel cell (DAFC) applications. Here we report an efficient AOR catalyst, in which ternary PtIrNi alloy nanoparticles well dispersed on a binary composite support consisting of porous silicon dioxide (SiO 2 ) and carboxyl-functionalized carbon nanotube (PtIrNi/SiO 2 -CNT-COOH) through a sonochemical-assisted synthesis strategy. The PtIrNi alloy nanoparticles, with the aid of abundant OHad provided by porous SiO 2 , and the improved electrical conductivity by CNTs, exhibit remarkable catalytic activity for the AOR in alkaline media. It is evidenced by a lower onset potential (~0.40 V vs. RHE) at room temperature, than that of commercial PtIr/C (ca. 0.43 V vs. RHE). Increasing NH 3 concentrations and operation temperatures significantly improve AOR performance of this catalyst. Specifically, AOR activity of the optimal PtIrNi nanoparticle catalyst can be significantly enhanced by elevating the temperature to 80ºC, with a much lower onset potential (~0.32 V vs. RHE), indicating that DAFC can be operated at higher temperature for increased performance. Constant-potential density functional theory (DFT) calculations showed that the Pt-Ir ensembles on {100}-terminated surfaces serve as the active site. Importantly, the introduction of Ni raises the center energy of the density of states projected onto the group d-orbitals of surface sites and thus lowers the theoretical onset potential for *NH 2 dehydrogenation to *NH when compared to Pt and Pt 3 Ir alloy.

25 ENERGY STORAGE↗
DOE OSTI2022

Highly efficient organic solar cells with superior deformability enabled by diluting the small molecule acceptor content

Developing efficient organic solar cells (OSCs) with strong mechanical deformability is important to be addressed to ensure their operational reliability in wearable electronics. However, it is challenging to achieve mechanically robust polymer/small molecule OSCs with an efficiency over 17% due to the abundant brittle donor/acceptor (D/A) interface. Decreasing the small molecule content can reduce the brittle D/A interface area to enhance deformability, but it may also cause discontinuous electron-conducting regions and thus deteriorate photovoltaic performance. Here, we incorporate a polymer donor (D18) into a binary PTQ10cm-BTP-PhC6 system at a constant PTQ10:m-BTP-PhC6 ratio of 1 : 1.2 to minimize the D/A interfacial area and modulate phase separation, and subsequently fabricate mechanically reliable OSCs with high efficiency. The large incorporation of D18 molecules increases the crystallinity of m-BTP-PhC6 molecules because of the poor interaction between D18 and the two host materials, affording sufficient pathways for efficient charge percolation at a large D/A ratio. More importantly, highly aggregated m-BTP-PhC6 molecules help to minimize the D/A interfacial area, enabling ternary films with better deformability than their binary counterparts. As a result, ternary OSCs with a large D/A ratio of 1.5 : 1.2 exhibit a high efficiency of 17.3% with a crack-onset strain (COS) of 8.8%, which significantly outperforms their binary counterparts with an efficiency of 13.8% and a COS of 4.4%. Finally, diluting the content of small molecules and controlling intermolecular interaction through the introduction of the second polymer donor represents a promising strategy to fabricate efficient OSCs with superior deformability.

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

Green-Solvent Processed Blade-Coating Organic Solar Cells with an Efficiency Approaching 19% Enabled by Alkyl-Tailored Acceptors

Power-conversion-efficiencies (PCEs) of organic solar cells (OSCs) in laboratory, normally processed by spin-coating technology with toxic halogenated solvents, have reached over 19%. However, there is usually a marked PCE drop when the blade-coating and/or green-solvents toward large-scale printing are used instead, which hampers the practical development of OSCs. Here, a new series of N-alkyl-tailored small molecule acceptors named YR-SeNF with a same molecular main backbone are developed by combining selenium-fused central-core and naphthalene-fused end-group. Thanks to the N-alkyl engineering, NIR-absorbing YR-SeNF series show different crystallinity, packing patterns, and miscibility with polymeric donor. The studies exhibit that the molecular packing, crystallinity, and vertical distribution of active layer morphologies are well optimized by introducing newly designed guest acceptor associated with tailored N-alkyl chains, providing the improved charge transfer dynamics and stability for the PM6:L8-BO:YR-SeNF-based OSCs. As a result, a record-high PCE approaching 19% is achieved in the blade-coating OSCs fabricated from a green-solvent o-xylene with high-boiling point. Notably, ternary OSCs offer robust operating stability under maximum-power-point tracking and well-keep > 80% of the initial PCEs for even over 400 h. Our alkyl-tailored guest acceptor strategy provides a unique approach to develop green-solvent and blade-coating processed high-efficiency and operating stable OSCs, which paves a way for industrial development.

14 SOLAR ENERGY↗
DOE OSTI2021

Investigation of phase-transformation path in TiZrHf(VNbTa)x refractory high-entropy alloys and its effect on mechanical property

Refractory high-entropy alloys (RHEAs) show a great potential as structural materials due to their remarkable properties, such as high strength and thermal stability. Despite these advantages, the RHEAs still suffer from the limited ductility at room temperature. To overcome the strength-ductility trade-off, the new RHEA design strategy, transformation-induced plasticity (TRIP) HEAs, have been developed by applying metastability-engineering approach. With the newly developed RHEAs design strategy, we designed metastable RHEAs, TiZrHfVxNbxTax (x = 1.0, 0.5 and 0.1) with decrease of the β-stabilizing elements (V, Nb, and Ta) to promote the transformation-induced ductility and work-hardening capability. The proper addition of the β-stabilizing elements (V, Nb, and Ta) into the ternary equi-molar TiZrHf alloy (TiZrHfV 0.1 Nb 0.1 Ta 0.1 ) leads to stress/strain-induced phase transformation from the body-centered cubic (BCC) to hexagonal-close-packed (HCP) α' and/or orthorhombic α" phases. Here, detailed studies on the phase transformation sequence during the deformation were carried out using X-ray diffraction (XRD), electron back-scattered diffraction (EBSD), and transmission-electron microscope (TEM), which revealed the stepwise phase transformation that is responsible for the strong strain hardening behavior. Furthermore, we further suggested the new transformation-induced-plasticity (TRIP) HEA design strategy, applying the Bo-Md approach.

36 MATERIALS SCIENCE↗