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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Hybrid Solid Oxide Fuel Cell/Gas Turbine Model Development for Electric Aviation

A thermodynamic model was developed and validated to analyze a high-performance solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system for electric aviation. This study used a process simulation software package (ProMax) to study the role of SOFC design and operation on the feasibility and performance of the hybrid system. Standard modules, including compressor, turbine, heat exchanger, reforming reactor, and combustor were used from the ProMax tool suite while a custom module was created to simulate the SOFC stack. The model used an SOFC test data set as an input. Additional SOFC stack performance effects, such as pressure, temperature, and utilization of air and fuel, were added from open source data. System performance predictors were SOFC specific power, fuel-to-electricity conversion efficiency, and hybrid system efficiency. Using these input data and predictors, a static thermodynamic performance model was created that can be modified for different system configurations and operating conditions. Prior to creating the final aircraft performance model, initial demonstration models were developed to validate output results. We used the NASA SOFC model as a benchmark, which was created with their Numerical Propulsion System Simulator (NPSS) software framework. Our output results matched within 1% of both the NASA model and open source SOFC performance data. With confidence gained in the accuracy of this model, a 1-MW SOFC-GT hybrid power system was constructed for an aircraft propulsion concept. Overall hybrid system efficiencies of > 75% FTE were observed during standard 36,000 feet cruise flight conditions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Ce IV 70 Oxosulfate Rings, Frameworks, Supramolecular Assembly, and Redox Activity**

Abstract M IV molecular oxo‐clusters (M=Zr, Hf, Ce, Th, U, Np, Pu) are prolific in bottoms‐up material design, catalysis, and elucidating reaction pathways in nature and in synthesis. Here we introduce Ce 70 , a wheel‐shaped oxo‐cluster, [Ce IV 70 (OH) 36 (O) 64 (SO 4 ) 60 (H 2 O) 10 ] 4− . Ce 70 crystallizes into intricate high pore volume frameworks with divalent transition metals and Ce‐monomer linkers. Eight crystal‐structures feature four framework types in which the Ce 70 ‐rings are linked as propellers, in offset‐stacks, in a tartan pattern, and as isolated rings. Small‐angle X‐ray scattering of Ce 70 dissolved in butylamine, with and without added cations (Ce IV , alkaline earths, Mn II ), shows the metals‘ differentiating roles in ring linking, leading to supramolecular assemblies. The large acidic pores and abundant terminal sulfates provide ion‐exchange behavior, demonstrated with U IV and Nd III . Frameworks featuring Ce III/IV ‐monomer linkers demonstrate both oxidation and reduction. This study opens the door to mixed‐metal, highly porous framework catalysts, and new clusters for metal‐organic framework design

Colliard, Ian↗
DOE OSTI2023

Flow Measurements in Pressurized Helium Gas Cooling Channels: Rev. 1

Compressed helium gas is used to cool the NorthStar Medical Radioisotope (NMR) target system, also called the trident, chosen due to its superior heat transfer capabilities and its inability to react with Molybdenum-100 (Mo-100) during irradiation. To test the housing and NMR target stack at Los Alamos National Laboratory (LANL), two sets of helium gas flow loop facilities have been set-up and tested. One system is used for bench-top experiments to systematically investigate individual components of the NMR target, and the other, larger system is more representative of the system at NMR and is used for testing the full NMR target stack.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Automated phase segmentation and quantification of high-resolution TEM image for alloy design

In the alloy design and development process, a wealth of atomically resolved structural high-resolution transmission electron microscopy (HRTEM) images are produced. Identifying the different nano-precipitate phases and tracking their evolution under various compositions and during manufacturing or post-processing requires hundreds of HRTEM images and thousands of precipitates. The nanoscopic phase information labeling and analysis purely relies on humans are prohibitively costly and time-consuming, sometimes not reliable because of the lack of authoritative knowledge. Here, in this work, we develop a novel unsupervised machine learning approach coupled with adaptive computer vision techniques with features in the Fourier space to automatically determine the number of phases and segment/quantify the phases with nanoscale resolution, allowing for quantitative correlation between nanostructure formation, processing and functional properties. To automate the phase extraction/quantification and ascertain its applicability, we have applied the developed framework to the HRTEM images from several alloy systems, processing conditions, image magnifications, and phase types and morphologies (precipitates, nano-twins, stacking faults, crystalline matrix, and amorphous structures) for verification. This study paves the road for compression, visualization, and translation of raw image structural data into physically relevant information in real-time with minimal human supervision. It shows the promise of enabling high-throughput materials characterization for the acceleration of alloy manufacturing and design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Orientation dependence of the effect of short-range ordering on the plastic deformation of a medium entropy alloy

Multi-principal-element alloys (also known as medium and high entropy alloys) offer a much larger and richer design space than conventional alloys, providing opportunities for discovering new functionalities and their governing physics. Some of these alloys exhibit an outstanding combination of high strength and ductility, linked to the activation of various deformation modes triggered by low-energy stacking faults. However, a pressing question remains: Is the plasticity of medium- and high-entropy alloys governed only by stacking fault energy, or does atomic short-range order (SRO) play a role? Here, to answer this, we investigated how SRO affects the deformation in single-crystalline NiCoCr, with previous contradictory findings. First, we established unique experimental evidence for SRO formation in bulk single crystals using high-energy synchrotron transmission X-Ray Diffraction. By tuning the degree of SRO by aging at high temperatures, twinning density and strain-induced martensitic phase transformation can be significantly increased in the [110] and [111] orientations under tension, increasing the tensile ductility; yet, no increase was observed along the [001] orientation due to lack of TWinning-Induced Plasticity (TWIP) or TRansformation-Induced Plasticity (TRIP), indicating a strong crystallographic orientation dependence. Our first-principles thermodynamic calculations unequivocally show SRO exists and governs the observed microstructural evolution and deformation hardening behavior. Here we find direct proof that SRO triggers a simultaneous TWIP and TRIP in NiCoCr, a rare microstructural evolution path. Our findings establish that the interplay of SRO and plasticity could be exploited to alter deformation modes and yield unprecedented mechanical response in medium- and high-entropy alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Enhancing dimensionality prediction in hybrid metal halides via feature engineering and class-imbalance mitigation

We present a machine learning (ML) framework for predicting the structural dimensionality of hybrid metal halides (HMHs), including organic-inorganic perovskites, using a combination of chemically-informed feature engineering and advanced class-imbalance handling techniques. This study is motivated by the small and highly imbalanced nature of experimentally available HMH datasets, which limits the applicability and reliability of conventional ML approaches. The dataset, consisting of 494 HMH structures, is highly imbalanced across dimensionality classes (0D, 1D, 2D, 3D), posing significant challenges to predictive modeling. To mitigate this limitation, the dataset was augmented to 1336 samples using the synthetic minority oversampling technique, enabling improved learning of underrepresented dimensionality classes while preserving chemically meaningful feature relationships. We developed interaction-based descriptors designed to capture coupled steric and polarity effects relevant to dimensionality prediction, which are not readily captured by standard single-parameter or composition-only descriptors. These descriptors are integrated into a multi-stage workflow combining feature selection, ensemble stacking, and performance optimization. Our approach significantly improves F1-scores for underrepresented classes, achieving robust cross-validation performance across all dimensionalities. This work demonstrates a generalizable strategy for extracting reliable and interpretable structure–dimensionality relationships from limited experimental data, enabling pre-synthesis screening of organic cations and providing a practical blueprint for small-data ML in hybrid materials systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Securing Federated Learning Against Active Reconstruction Attacks

Federated Learning (FL) has amassed notable attention for its ability to preserve user privacy while emphasizing the retainment of model training efficiency. Due to this potential, FL has been integrated in many domains, such as healthcare, finance, law, and industrial engineering, where data cannot be easily exchanged due to sensitive information and strict privacy laws. However, current research has indicated that FL protocols are easily compromised by active data reconstruction attacks employed by actively dishonest servers. The malicious modification of global model parameters allows an actively dishonest server to obtain a direct copy of users’ private data via gradient inversion. Here, this class of attacks is highly underexplored and continues to be a major challenge due to the intense threat model. In this paper, we propose OASIS as a scalable and modality-agnostic defense based on data augmentation that counteracts active data reconstruction attacks while preserving model performance. To generalize our defense, we uncover the intuition behind gradient inversion that enables these attacks and theoretically establish the conditions by which the defense can be considered robust regardless of attack design. From this, we formulate our defense with data augmentation that illustrates its ability to undermine the attack principle. We evaluate OASIS on five real-world datasets–two image-based (ImageNet and CIFAR100) and three text-based (Wikitext, Stack Overflow, and Shakespeare)–which span diverse uses cases such as vision tasks and language modeling. Comprehensive evaluations on these datasets exhibit the efficacy of OASIS and highlight its feasibility as a solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Transport Analysis & Optimization in a MW-Scale CO2 Electrolyzer (Final Report)

As Twelve continues to scale up their CO2 electrolyzers, both in the size of a single cell and in the number of cells used in a stack, thermal management becomes a growing concern, since excess heat can affect reaction yield and accelerate degradation. In this project, we aim to computationally explore how the anode flow fields used in Twelve’s CO2 electrolyzers function as heat exchangers. In particular, using a homogenized model of a CO2 electrolyzer, we first estimate the amount of heat generated in a cell. Then, we develop a computational fluid dynamics (CFD) model of the so-called “flow field”, i.e. a flow manifold, based on Twelve’s CAD drawings, to evaluate how these flow fields perform as a heat exchanger for the generated heat. We explore both a single cell and a 3-cell stack operating in parallel, where heat generated in one cell can now be transferred to another cell. We evaluate how performance is affected when environmental heat losses are taken into account. Finally, we leverage topology optimization to explore the types of design features a computational optimization algorithm would suggest to supplement our intuition. Overall, our work aims to provide design recommendations for CO2 electrolyzer flow fields and provides a foundation for future studies of flow field optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Assembly of short amphiphilic peptoids into nanohelices with controllable supramolecular chirality

Abstract A long-standing challenge in bioinspired materials is to design and synthesize synthetic materials that mimic the sophisticated structures and functions of natural biomaterials, such as helical protein assemblies that are important in biological systems. Herein, we report the formation of a series of nanohelices from a type of well-developed protein-mimetics called peptoids. We demonstrate that nanohelix structures and supramolecular chirality can be well-controlled through the side-chain chemistry. Specifically, the ionic effects on peptoids from varying the polar side-chain groups result in the formation of either single helical fiber or hierarchically stacked helical bundles. We also demonstrate that the supramolecular chirality of assembled peptoid helices can be controlled by modifying assembling peptoids with a single chiral amino acid side chain. Computational simulations and theoretical modeling predict that minimizing exposure of hydrophobic domains within a twisted helical form presents the most thermodynamically favorable packing of these amphiphilic peptoids and suggests a key role for both polar and hydrophobic domains on nanohelix formation. Our findings establish a platform to design and synthesize chiral functional materials using sequence-defined synthetic polymers.

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

kynema-fmb [SWR-23-07]

Kynema-FMB (FKA: Kynema) is an open-source performance portable flexible multibody (FMB) dynamics solver designed for time-domain simulations. While originally tailored for wind turbine structural dynamics, the formulation and implementation are those of a general flexible-multidbody dynamics solver that can readily be applied to a wide range of systems. Kynema was designed with a narrow focus, namely to provide a lightweight, fast, accurate FMD solver for coupling to computational-fluid-dynamics (CFD) codes, especially the CFD codes in the Kynema suite, for fluid-structure-interaction (FSI) simulations. Kynema-FMB is equipped to model systems that can be represented as a collection of beams and rigid bodies that are connected through constraints. Degrees of freedom are defined in the inertial/global frame of reference and include displacements and rotations (formally as rotation matrices, but stored as quaternions). The underlying formulation is built on a Lie-group time integrator designed for index-3 differential-algebraic equations, which is second-order accurate in time (Bruls et al., 2012). Beam models are based on geometrically exact beam theory and are discretized as high-order spectral finite elements similar to those in BeamDyn (Wang et al., 2017). The governing equations for a FMD system like a wind turbine constitute a highly nonlinear system of constrained partial-differential equations. Kynema-FMB uses analytical Jacobians in the nonlinear-system solves in each time step. Linear systems use sparse storage and several third-party sparse-linear-system solvers are enabled. Ill conditioning of linear systems is mitigated with preconditioning described in Bottasso et al, 2008. Kynema-FMB is integrated with a simple open-source controller (ROSCO). There is an application programming interface (API) for coupling to geometry-resolved CFD (like that in Sharma et al., 2023) and actuator-force CFD (like that in Kuhn et al., 2025). In the latter, for actuator-line models, Kynema-FMB includes an internal blade-element solver that depends on user-provided lookup tables for coefficients of lift and drag, i.e., aerodynamic polars. Kynema-FMB is written in C++ and leverages Kokkos and Kokkos-Kernels (KokkosEcosystem) as its performance portability layer enabling simulations on both CPU and GPU systems. The repository is equipped with extensive automated testing at the unit and regression/system levels. The following describes the high-level development objectives conceived for Kynema: *Kynema will follow modern software development best practices, including test-driven development (TDD), version control, hierarchical automated testing, and continuous integration (CI) for a robust development environment. *The core data structures are memory efficient and enable vectorization and parallelization at multiple levels. *Data structures are data-oriented to exploit methods for accelerated computing including high utilization of chip resources (e.g., single instruction multiple data (SIMD) instruction sets) and parallelization using GP-GPUs. *The computational algorithms incorporate robust open-source libraries for mathematical operations, resource allocation, and data management. *The API design considers multiple stakeholder needs and ensure integration with existing and future ecosystems for data science, machine learning, and AI. *Kynema-FMB is written in modern C++ and leverages Kokkos as its performance-portability library with inspiration from the kynema stack.

Sprague, MichaelA.↗
DOE OSTI2020

Lateral Heterostructures of Multilayer GeS and SnS van der Waals Crystals

Engineered heterostructures derive distinct properties from materials integration and interface formation. Two-dimensional crystals have been combined to form vertical stacks and lateral heterostuctures with covalent line interfaces. While thicker vertical stacks have been realized, lateral heterostructures from multilayer van der Waals crystals, which could bring the benefits of high-quality interfaces to bulk-like layered materials, have remained much less explored. In this work, we demonstrate the integration of anisotropic layered Sn and Ge monosulfides into complex heterostructures with seamless lateral interfaces and tunable vertical design using a two-step growth process. The anisotropic lattice mismatch at the lateral interfaces between GeS and SnS is relaxed via dislocations and interfacial alloying. Nanoscale optoelectronic measurements by cathodoluminescence spectroscopy show the characteristic light emission of joined high-quality van der Waals crystals. Spectroscopy across the lateral interface indicates valley-selective luminescence in the bulk SnS component that arises due to anisotropic electron transfer across the interface. The results demonstrate the ability to realize high-quality lateral heterostructures of multilayer van der Waals crystals for diverse applications, e.g., in optoelectronics or valleytronics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Luminescence from Self‐Trapped Excitons and Energy Transfers in Vacancy‐Ordered Hexagonal Halide Perovskite Cs 2 HfF 6 Doped with Rare Earths for Radiation Detection

Abstract Compared to halides Cs 2 HfX 6 (X = Cl, Br, I) with a vacancy‐ordered cubic double perovskite structure, the halide Cs 2 HfF 6 (CHF), with a hexagonal Bravais lattice, possesses a higher mass density and chemical stability for radiation detection. Luminescence properties and energy transfer mechanisms of rare‐earths‐doped CHF materials are studied here. The structure of CHF is identified as a new type of vacancy‐ordered hexagonal perovskite, with the same type of building blocks of the double perovskite but stacked with single layers. Density‐functional theory calculations reveal a large bandgap of CHF. A broad emission is observed from the pristine CHF host, which is suggested to be associated with self‐trapped excitons (STEs). A series of rare‐earths‐doped materials are designed utilizing the STE emissions, and efficient energy transfers from STEs and Tb 3+ to Eu 3+ are achieved for tunable emissions. The codoped material shows stable emission under X‐ray irradiation, with 10.2% reduction from its initial emission intensity, associated with possible structural evolution by radiation‐induced deformation of the soft host. The radiation responses of singly and codoped materials are evaluated, and the codoped material is found to be more sensitive to the radiation energy than the singly doped or pristine CHF for radiation detection.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Improvements to the Recycler/Main Injector to Deliver 850 kW+

The Main Injector is used to deliver a 120 GeV high power proton beam for Neutrino experiments. The design power of 700 kW was reached in early 2017 but further improvements have seen a new sustained peak power of 893 kW. Two of the main improvements include the shortening of the Main Injector ramp length as well optimizing the slip-stacking procedure performed in the Recycler to reduce the amount of uncaptured beam making its way into the Main Injector. These improvements will be discussed in this paper as well future upgrades to reach higher beam powers.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Molecular Simulation of Functionalized Covalent Organic Framework Membranes for Inorganic Salt Separation

Covalent organic frameworks (COFs) enable molecular-level design of nanochannels for selective separation in pressure-driven membrane processes. Through variation of building blocks and, subsequently, the pore structure and chemistry, membrane performance can be tailored. This study employs nonequilibrium molecular dynamics simulations to theoretically demonstrate the tunable selectivity of COF membranes through a bottom-up functionalization approach. Water and salt transport are evaluated for six β-ketoenamine-linked COFs with varying multilayer thicknesses. For the thinnest multilayer (0.64–0.72 nm), all COFs exhibit low sodium sulfate (Na 2 SO 4 ) rejection (55–66%). However, 20 stacked sheets (6.4–7.2 nm) provide 67–98% rejection, with the sulfonated COF providing the highest Na 2 SO 4 rejection. Analysis of time-resolved ion density profiles reveals that solute rejection is primarily governed by interfacial exclusion arising from pore size and functional group chemistry. Although increasing salt rejection compromises water permeance, the permeance of all COF membranes is at least two orders of magnitude greater than that of a commercially available nanofiltration membrane. Overall, this work guides the rational design of COF membranes for aqueous salt separation.

Nanofiltration↗
DOE OSTI2024

Molecular Mechanisms of Sorbed Ion Effects during Boehmite Particle Aggregation

Classical theories of particle aggregation, such as Derjaguin–Landau–Verwey–Overbeek (DLVO), do not explain recent observations of ion-specific effects or the complex concentration dependence for aggregation. Thus, here, we probe the molecular mechanisms by which selected alkali nitrate ions (Na + , K + , and NO 3 –) influence aggregation of the mineral boehmite (γ-AlOOH) nanoparticles. Nanoparticle aggregation was analyzed using classical molecular dynamics (CMD) simulations coupled with the metadynamics rare event approach for stoichiometric surface terminations of two boehmite crystal faces. Calculated free energy landscapes reveal how electrolyte ions alter aggregation on different crystal faces relative to pure water. Consistent with experimental observations, we find that adding an electrolyte significantly reduces the energy barrier for particle aggregation (~3–4×). However, in this work, we show this is due to the ions disrupting interstitial water networks, and that aggregation between stoichiometric (010) basal–basal surfaces is more favorable than between (001) edge–edge surfaces (~5–6×) due to the higher interfacial water densities on edge surfaces. The interfacial distances in the interlayer between aggregated particles with electrolytes (~5–10 Å) are larger than those in pure water (a few Ångströms). Together, aggregation/disaggregation in salt solutions is predicted to be more reversible due to these lower energy barriers, but there is uncertainty on the magnitudes of the energies that lead to aggregation at the molecular scale. By analyzing the peak water densities of the first monolayer of interstitial water as a proxy for solvent ordering, we find that the extent of solvent ordering likely determines the structures of aggregated states as well as the energy barriers to move between them. Further, the results suggest a path for developing a molecular-level basis to predict the synergies between ions and crystal faces that facilitate aggregation under given solution conditions. Such fundamental understanding could be applied extensively to the aggregation and precipitation utilization in the biological, pharmaceutical, materials design, environmental remediation, and geological regimes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ce IV 70 oxosulfate rings, frameworks, supramolecular assembly and redox activity

M IV molecular oxo-clusters (M=Zr, Hf, Ce, Th, U, Np, Pu) are prolific in bottoms-up material design, catalysis, and elucidating reaction pathways in nature and in synthesis. Here we introduce Ce 70 , a wheel-shaped oxo-cluster, [Ce IV 70 -(OH) 36 (O) 64 (SO 4 ) 60 (H 2 O) 10 ] 4- . Ce 70 crystallizes into intricate high pore volume frameworks with divalent transition metals and Ce-monomer linkers. Eight crystal-structures feature four framework types in which the Ce 70 -rings are linked as propellers, in offset-stacks, in a tartan pattern, and as isolated rings. In this work, small-angle X-ray scattering of Ce 70 dissolved in butylamine, with and without added cations (Ce IV , alkaline earths, Mn II ), shows the metals‘ differentiating roles in ring linking, leading to supramolecular assemblies. The large acidic pores and abundant terminal sulfates provide ion-exchange behavior, demonstrated with U IV and Nd III . Frameworks featuring Ce III/IV -monomer linkers demonstrate both oxidation and reduction. Furthermore, this study opens the door to mixed-metal, highly porous framework catalysts, and new clusters for metal-organic framework design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Linking Pressure to Electrochemical Evolution in Solid-State Conversion Cathode Composites

Conversion-type cathodes, such as sulfur, FeS 2 , and FeF 3 , offer high theoretical capacities in solid-state lithium batteries but are hindered by substantial volume changes during cycling, leading to interfacial contact loss, crack formation, and microstructural degradation. Here, we investigate the relationships between electrochemical, mechanical, and structural evolution in solid-state electrode composites with these three active materials. Using real-time stack-pressure monitoring, synchrotron X-ray absorption spectroscopy, and electrokinetic modeling, we elucidate how stress evolution is linked to reversible and irreversible redox reactions. Nonlinear stack pressure evolution in cells with sulfur, FeS 2 , and FeF 3 electrode composites is found to arise from material-specific volume changes, the balance of volume change between the working and counter electrode, and the formation of distinct reaction intermediates. The three materials exhibit distinct stack pressure evolution, which is closely related to the different reaction processes in the materials, as demonstrated with X-ray absorption spectroscopy measurements. Through mesoscale modeling, we relate the experimental measurements to species evolution at the particle scale and track the dynamic coexistence of intermediate phases. Our findings highlight the importance of designing for volume changes of a given active material in solid-state battery systems.

batteries↗
DOE OSTI2023

Hexaazatriphenylene‐Based Two‐Dimensional Conductive Covalent Organic Framework with Anisotropic Charge Transfer

Abstract The development of covalent organic frameworks (COFs) with efficient charge transport is of immense interest for applications in optoelectronic devices. To enhance COF charge transport properties, electroactive building blocks and dopants can be used to induce extended conduction channels. However, understanding their intricate interplay remains challenging. We designed and synthesized a tailor‐made COF structure with electroactive hexaazatriphenylene (HAT) core units and planar dioxin (D) linkages, denoted as HD‐COF. With the support of theoretical calculations, we found that the HAT units in the HD‐COF induce strong, eclipsed π–π stacking. The unique stacking of HAT units and the weak in‐plane conjugation of dioxin linkages leads to efficient anisotropic charge transport. We fabricated HD‐COF films to minimize the grain boundary effect of bulk COFs, which resulted in enhanced conductivity. As a result, the HD‐COF films showed an electrical conductivity as high as 1.25 S cm −1 after doping with tris(4‐bromophenyl)ammoniumyl hexachloroantimonate.

Kim, Seong‐Wook↗