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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

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

Polymer Hole Transport Materials for Perovskite Solar Cells via Buchwald–Hartwig Amination

The development of low-cost materials for charge-selective contacts that provide good energetic alignment with perovskite active layers, favorable thermal properties, and lead to efficient photoconversion is becoming an increasingly important aspect of the perovskite solar cell (PSC) field. Presented here is a series of polymers based on a one-pot polymerization of aryl dihalides with primary aryl amines to produce solution-processable polymers in high yield, with simple purification, and promising properties for high performing P-I-N PSC devices. How these properties can be tuned by careful selection of the reactant chemical moieties is discussed. Through this strategy, a wide range of relevant properties such as glass transition temperature, highest occupied molecular orbital tuning, and polydispersity are explored. When implemented into devices using a triple-cation FAMACs perovskite active layer, the hole transport material series shows average power conversion efficiencies (PCE) in excess of 17%, which is comparable to controls using state-of-the-art poly(triarylamine). How different synthetic parameters such as the reaction time and purification protocol impact device performance is also investigated.

14 SOLAR ENERGY↗
DOE OSTI2023

Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning

Polyimides have been widely used in modern industries because of their excellent mechanical and thermal properties, e.g., high-temperature fuel cells, displays, and aerospace composites. However, it usually takes decades of experimental efforts to develop a successful product. Aiming to expedite the discovery of high-performance polyimides, we utilize computational methods of machine learning (ML) and molecular dynamics (MD) simulations. Our study provides compelling evidence for the effectiveness of a data-driven approach in discovering novel polyimides. We first build a comprehensive library of more than 8 million hypothetical polyimides based on the polycondensation of existing dianhydride and diamine/diisocyanate molecules. Then we establish multiple ML models for the thermal and mechanical properties of polyimides based on their experimentally reported values, including glass transition temperature, Young’s modulus, and tensile yield strength. The obtained ML models demonstrate excellent predictive performance in identifying the key chemical substructures influencing the thermal and mechanical properties of polyimides. The use of explainable machine learning describes the effect of chemical substructures on individual properties, from which human experts can understand the cause of the ML model decision. Applying the well-trained ML models, we obtain property predictions of the 8 million hypothetical polyimides. Then, we screen the whole hypothetical dataset and identify three (3) best-performing novel polyimides that have better-combined properties than existing ones through Pareto frontier analysis. For an easy query of the discovered high-performing polyimides, we also create an online platform https://polyimide-explorer.herokuapp.com/ that embeds the developed ML model with interactive visualization. Furthermore, we validate the ML predictions through all-atom MD simulations and examine their synthesizability. The MD simulations are in good agreement with the ML predictions and the three novel polyimides are predicted to be easy to synthesize via Schuffenhauer’s synthetic accessibility score. Following the proposed ML guidance, we successfully synthesized a novel polyimide and the experimentally obtained high glass transition/thermal decomposition temperature demonstrated its excellent thermal stability. Here our study demonstrates an efficient way to expedite the discovery of novel polymers using ML prediction and MD validation. The high-throughput screening of a large computational dataset can serve as a general approach for new material discovery in other polymeric material exploration problems, such as organic photovoltaics, polymer membranes, and dielectrics.

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

Encapsulation Materials Tailored to Perovskite Photovoltaics

The work combines NREL as the world leader in perovskite and polymeric materials, and teams them up with The Dow Chemical Company, the world leader in commercial production of PV encapsulation materials. The team will design and evaluate encapsulation materials that are tailored to perovskite photovoltaics. Demonstration of polyolefin-based encapsulants for perovskite PV will be impactful for a number of reasons: 1) There is no clear-cut choice for encapsulation for perovskite PV to date. 2) There is high synthetic control of the material properties for future perovskite module designs. 3) Among the candidate materials, they have the highest barrier properties, 4) Polyolefins are the most prevalent (>20 million metric tons consumed in the US alone) and inexpensive (<1.5 $USD/kg) polymers used worldwide. 5) They are recyclable and may play a role in future of circular PV materials. 6) They are manufactured domestically. The work also highlights careful design of perovskite transport layer materials for surviving vacuum encapsulation.

14 SOLAR ENERGY↗
DOE OSTI2024

Vapor Infiltration Synthesis of Indium Sulfide Magic Size Cluster

The energetically favorable formation of atomically precise clusters, known as magic size clusters, in the solution phase enables a precision nanoscale synthesis with exquisite uniformity. Here, we report the synthesis of magic size clusters via vapor infiltration of atomic layer deposition precursors directly in a polymer thin film. Sequential infiltration of trimethylindium vapor and hydrogen sulfide gas into poly(methyl methacrylate) leads to the formation of clusters with uniform properties consistent with a magic size cluster-In 6 S 6 (CH 3 ) 6 . While an increase in cluster size might be expected with additional sequential infiltration cycles of the reactive In and S precursors, uniform properties consistent with magic size clusters form in multiple polymers under a range of processing conditions. Ultraviolet-visible absorption spectra of In 6 S 6 (CH 3 ) 6 are largely independent of the number of sequential infiltration cycles and exhibit air stability, both of which are attributed to an energetically favorable synthetic pathway that is evaluated with density functional theory.

atomic layer deposition↗
DOE OSTI2026

Improved nylon polymerization using amide diads

Nylons, a major class of synthetic polyamides, are widely used due to their excellent mechanical strength, thermal stability, and chemical resistance. Conventional nylon production relies on the polymerization of lactams or stoichiometric nylon salts. However, applying these approaches to unconventional precursors such as bio-derived glutaric acid produces polymers with low molecular weight and limited applications. To address these challenges, we demonstrated that chemically-synthesized nylon diads enable the production of higher-molecular-weight polyamides compared with traditional salts. We then identified a biosynthetic approach using amide synthetases to convert unprotected bifunctional substrates into nylon-relevant diads. Using a cofactor regeneration system, enzymatic diad synthesis was scaled to produce sufficient material for laboratory-scale characterization and solid-state polymerization. Amide synthetases demonstrated broad substrate scope, catalyzing the regioselective assembly of diverse nylon-relevant diacids, diamines, and ω-amino acids. This strategy offers a novel route to synthesize challenging nylon monomers and advances production of bioderived nylons.

Qian, Liangyu [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2023

p -Azaquinodimethane: A Versatile Quinoidal Moiety for Functional Materials Discovery

The past 50 years of discovery in organic electronics have been driven in large part by the donor–acceptor design principle, wherein electron-rich and electron-poor units are assembled in conjugation with each other to produce small band gap materials. While the utility of this design strategy is undoubtable, it has been largely exhausted as a frontier of new avenues to produce and tune novel functional materials to meet the needs of the ever-increasing world of organic electronics applications. Its sister strategy of joining quinoidal and aromatic groups in conjugation has, by comparison, received much less attention, to a great extent due to the categorically poor stability of quinoidal conjugated motifs. In 2017 though, the p-azaquinodimethane (AQM) motif was first unveiled, which showed a remarkable level of stability despite being a close structural analogue to p-quinodimethane, a notably reactive compound. In contrast, dialkoxy AQM small molecules and polymers are stable even under harsh conditions and could thus be incorporated into conjugated polymers. When polymerized with aromatic subunits, these AQM-based polymers show notably reduced band gaps that follow reversed structure–property trends to some of their donor–acceptor polymer counterparts and yield organic field-effect transistor (OFET) hole mobilities above 5 cm 2 V –1 s –1 . Additionally, in an ongoing study, these AQM-based compounds are also showing promise as singlet fission (SF) active materials due to their mild diradicaloid character. An expanded world of AQMs was accessed through their ditriflate derivatives, which were first used to produce ionic AQMs (iAQMs) sporting two directly attached cationic groups that significantly affect the AQM motif’s electronics, producing strongly electron-withdrawing quinoidal building blocks. Conjugated polyelectrolytes (CPEs) created with these iAQM building blocks exhibit optical band gaps stretching into the near-infrared I (NIR-I) region and showed exemplary behavior as photothermal therapy agents. In contrast to these stable AQM examples, the synthetic exploration of AQMs also produced examples of more typical diradicaloid reactivity but in forms that were controllable and produced intriguing and high-value products. With certain substitution patterns, AQMs were found to dimerize to form highly substituted [2.2]paracyclophanes in distinctly more appreciable yields than typical cyclophane formation reactions. Certain AQM ditriflates, when crystallized, undergo light-induced topochemical polymerization to form ultrahigh molecular weight (>10 6 Da) polymers that showed excellent performances as dielectric energy storage materials. These same AQM ditriflates could be used to produce the strongly electron-donating redox-active pentacyclic structure: pyrazino[2,3-b:5,6-b']diindolizine (PDIz). Importantly, the PDIz motif allowed for the synthesis of exceedingly small band gap (0.7 eV) polymers with absorbances reaching all the way into the NIR-II region that were also found to produce strong photothermal effects. Both as stable quinoidal building blocks and through their controllable diradicaloid reactivity, AQMs have already proven to be versatile and effective as functional organic electronics materials.

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

A Semiconducting Two‐Dimensional Polymer as an Organic Electrochemical Transistor Active Layer

Abstract Organic electrochemical transistors (OECTs) are devices with broad potential in bioelectronic sensing, circuits, and neuromorphic hardware. Their unique properties arise from the use of organic mixed ionic/electronic conductors (OMIECs) as the active channel. Typical OMIECs are linear polymers, where defined and controlled microstructure/morphology, and reliable characterization of transport and charging can be elusive. Semiconducting two‐dimensional polymers (2DPs) present a new avenue in OMIEC materials development, enabling electronic transport along with precise control of well‐defined channels ideal for ion transport/intercalation. To this end, a recently reported 2DP, TIIP, is synthesized and patterned at 10 µm resolution as the channel of a transistor. The TIIP films demonstrate textured microstructure and show semiconducting properties with accessible oxidation states. Operating in an aqueous electrolyte, the 2DP‐OECT exhibits a device‐scale hole mobility of 0.05 cm 2 V –1 s –1 and a µ C * figure of merit of 1.75 F cm –1 V –1 s –1 . 2DP OMIECs thus offer new synthetic degrees of freedom to control OECT performance and may enable additional opportunities such as ion selectivity or improved stability through reduced morphological modulation during device operation.

2D-polymer↗
DOE OSTI2023

Sequence Design of Random Heteropolymers as Protein Mimics

Random heteropolymers (RHPs) have been computationally designed and experimentally shown to recapitulate protein-like phase behavior and function. However, unlike proteins, RHP sequences are only statistically defined and cannot be sequenced. Recent developments in reversible-deactivation radical polymerization allowed simulated polymer sequences based on the well-established Mayo–Lewis equation to more accurately reflect ground-truth sequences that are experimentally synthesized. This led to opportunities to perform bioinformatics-inspired analysis on simulated sequences to guide the design, synthesis, and interpretation of RHPs. We compared batches on the order of 10000 simulated RHP sequences that vary by synthetically controllable and measurable RHP characteristics such as chemical heterogeneity and average degree of polymerization. Our analysis spans across 3 levels: segments along a single chain, sequences within a batch, and batch-averaged statistics. We discuss simulator fidelity and highlight the importance of robust segment definition. Examples are presented that demonstrate the use of simulated sequence analysis for in-silico iterative design to mimic protein hydrophobic/hydrophilic segment distributions in RHPs and compare RHP and protein sequence segments to explain experimental results of RHPs that mimic protein function. To facilitate the community use of this workflow, the simulator and analysis modules have been made available through an open source toolkit, the RHPapp.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Enzymatic Nylon Deconstruction: Enzyme Discovery, Engineering, and Opportunities

Nylons are widely used synthetic polyamides valued for their strength, versatility, and durability across diverse applications. However, their petrochemical origin and energy-intensive production underscore the need for efficient, circular solutions. Conventional recycling methods remain limited by incomplete recovery, material degradation, and costly sorting requirements. Enzymatic depolymerization offers a selective, low-energy alternative capable of processing mixed waste streams under mild conditions. While significant progress has been achieved for polyesters, enzymatic degradation of polyamides is still at an early stage. The discovery of nylon hydrolases demonstrated the potential of biological systems to evolve catalysts for synthetic polyamides, yet reported depolymerization yields remain low. These limitations reflect both the structural complexity of nylons and the need for improved enzyme discovery and engineering. In conclusion, this review highlights recent advances, key challenges, and future directions for enzymatic nylon recycling, outlining its potential role enabling mixed polymer waste to be used as a green feedstock for remanufacturing.

Amides↗
DOE OSTI2024

Epoxy Coating of Biofiber: An Effective Modifier of Biofiber Physical and Flow Properties for Improved Tensile Behavior of Biofiber-Reinforced Biocomposite

Biocomposites combine renewable, plant-based fibers with degradable polymers and are an attractive option for sustainable, lightweight, and cost-effective materials with a low carbon footprint, especially for large-scale additive manufacturing. One of the major challenges in the widespread adoption of biocomposites is that their mechanical performance is significantly inferior to that of synthetic composites. Surface treatment is a common and effective technique to improve the mechanical properties of the biofibers used in biocomposites. This study aims to investigate the physical and flow properties of surface-treated biofibers, as well as the tensile properties of their PLA-based biocomposite, to gain insights into how surface treatment changes the fiber‘s characteristics and biocomposite‘s mechanical properties. Surface treatment was created using a two-component epoxy system by reacting poly(bisphenol A-co-epichlorohydrin) glycidyl end-capped (PBG) and dicyandiamide (DICY). The treatment was tested on two different biofibers (loblolly pine and corn stover fibers) with three different PBG/DICY molar ratios (0.25, 0.5, and 2). Results showed that surface-treated fibers improved the tensile strength and Young‘s modulus of the biocomposites. Loblolly pine biocomposites from fibers treated with a PBG/DICY ratio of 0.25 exhibited the best tensile properties. The surface treatment resulted in a more loosely dispersed fiber bulk structure, as evidenced by less fiber agglomeration into smaller particle sizes, higher fiber sphericity, and lower loose bulk density. This can enhance stress distribution and the overall mechanical performance of the biocomposites. Additionally, surface-treated fibers exhibited better dynamic flow properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Understanding the Structure and Dynamics of Conjugated Polymers by Advancing Deuteration Chemistry and Neutron Scattering (Final Report)

The overarching goal of the proposed work was to set up a partnership between the University of Southern Mississippi (USM) and Oak Ridge National Laboratory (ORNL) to develop novel approaches to measure the backbone rigidity of conjugated polymers (CPs) and understand the critical role of sidechains on the backbone conformation and the materials macroscopic property. The backbone rigidity greatly influences the electronic properties of CPs, which ultimately determines the functionality and performance of these materials. Improvements in the electronic properties of CPs would allow for enhanced charge transport in semiconductor devices, improved photovoltaic performance, recycling of waste heat in thermoelectrics, and discovery of new phenomena that will enable the next generation of energy technologies. Although significant progress has been made to optimize the optical and electronic properties of CPs, largely through Edisonian methodologies, it remains a challenge to experimentally characterize conjugated backbone conformation (chain rigidity, torsion, planarity, and short-range order) and relate these to the fundamental optical and electronic properties (electronic coupling, charge transport, etc.). This has left fundamental gaps in our knowledge of the most basic structure/property relationships within these systems, precluded the study of fundamental physical phenomena, and constrained the design and realization of new electronic and device functionalities. Thus, the major goal of this work is to use novel deuteration methodologies via systematic synthetic approaches, and neutron scattering techniques to comprehensively characterize the structural and dynamic properties of CPs in contrast-matching solvents. Our work would, for the first time, elucidate the relationship between backbone rigidity and macroscopic properties. They will also allow a rational formulation of design principles for next-generation CPs that are resilient to disorder through precise control of the delocalized electrons along the polymer backbone. Overall, this project will advance our understanding of the structure, dynamics, and fundamental physics of these materials, which is crucial for enabling the prediction, design, control, and manipulation of current and emerging material electronic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Advanced Algal Biofoundries for the Production of Polyurethane Precursors

The primary goal of the BEEPs project was to develop a process that could accelerate the development of algae as bioproduction platforms, from initial chemical product concept to an economically viable market supply. Under this program we elected to develop strains of algae that could generate polyurethane precursors, while simultaneously developing basic genetic tools to enable improved algal production systems. This program was specifically designed to incorporate National Laboratories as a means to utilize the expertise and facilities for new bio-production platforms. To that end, we designed a program to collaborate with the Agile BioFoundry at Lawrence Berkeley National Laboratory (LBNL) and computational platforms at Pacific Northwest National Laboratory (PNNL). In addition to these National Laboratory partners, we also had academic partners from UC Davis and Georgia Tech, as well as commercial partners Algenesis Materials and BASF. To achieve these goals, we initially focused on developing the genetic tools and high throughput screening technologies necessary to generate and assess production of polymer precursors (succinic acid) in algae and cyanobacteria, including advanced promoters and biosensors. In parallel, we computationally identified potential production bottlenecks and then used the developed genetic tools to increase production rates and yields. Constant feedback of data was used in conjunction with machine learning, high-throughput cell sorting, and synthetic biology, for additional targeted metabolic engineering. Multiple rounds of tool design, building, testing, and learning were supplied to partners at PNNL and LBNL to develop new models and tools that could expedite bioproduction platform development and increase yield performance. We targeted, and achieved, the FOA requirement yield metric of 20 g/L, as a milestone and deliverable from at least one of our engineered strains for the production of succinic acid.

09 BIOMASS FUELS↗
DOE OSTI2022

From Petroleum to Biobased Crude: A Thermoplastic Polyurethane from Lignin-Oil Without Isocyanates

The movement to transfer from petroleum-based products and materials to renewables does not necessarily have to bypass the use of oil. A new type of "black-gold" is readily abundant from the earth's most abundant source of aromatic carbon: lignin. While fractionation of petroleum yields fuels and chemicals for a diverse set of industries, lignin fractionation using targeted catalysts has demonstrated the ability to generate monomers and oligomers rich in functional groups for polymer synthesis. This study explores the use of lignin-oil, generated from reductive catalytic fractionation of popular wood, to a hydroxyl-rich mixture of aromatics that is used to synthesize a thermoplastic non-isocyanate polyurethane. The lignin-oil is first converted to a cyclocarbonated derivative using a benign synthetic sequence and further polymerized with a diamine to yield the non-isocyanate TPU. While more work is underway to optimize the reaction conditions and meet typical mechanical properties of commercial materials, initial analysis shows thermoplastic behavior and flexible properties consistent with traditional thermoplastic polyurethanes.

BIOMASS FUELS↗
DOE OSTI2026

Toxicity of Common Fluoropolymers and PFAS on C. Elegans and an Innovative Strategy to Promote in Situ Remediation - 26128

Per- and polyfluoroalkyl substances (PFAS) are a broad class of synthetic chemicals used in a variety of modern technologies and consumer products. PFAS have an alkyl backbone with all or most of the hydrogen (H) atoms replaced with fluorine (F) atoms. PFAS generally fall into one of two categories, they can be non-polymeric with relatively low molecular weights, or long-chain polymers. PFAS are a diverse group of organic compounds that can be solids, liquids, dispersions, or gases. Their mobility and toxicity are influenced by their chain lengths and functional groups. Non-polymeric PFAS are common building blocks for the manufacturing of fluoropolymers. Non-polymeric PFAS are known to be mobile in the environment and some are considered contaminants of emerging concern. Polymeric PFAS, or fluoropolymers, are typically thought to be of low concern, however few systematic investigations into their toxicity have been completed. PFAS, including fluoropolymers and microplastics, have been found in pristine environments and animals located far from site of origin including the arctic and deep ocean.

Jacobs, Stephanie [Savannah River National Laborat↗
DOE OSTI2024

Achieving 19% efficiency in non-fused ring electron acceptor solar cells via solubility control of donor and acceptor crystallization

Non-fused ring electron acceptors (NFREAs) potentially have lower synthetic costs than their fused counterparts. However, the low backbone planarity and the presence of bulky substituents adversely affect the crystallinity of NFREAs, impeding charge transport and the formation of bicontinuous morphology in organic solar cells. Here we show that a binary solvent system can individually control the crystallization and phase separation of the donor polymer (for example, D18) and the NFREA (for example, 2BTh-2F-C 2 ). We select solvents such as chloroform and o -xylene that evaporate at different temperatures and rates and have different solubility for D18. Upon evaporation of chloroform, D18 starts to assemble into fibrils. Then, the evaporation of o-xylene induces the rapid formation of a fibril network that phase segregates 2BTh-2F-C 2 into pure domains and leads to a bicontinuous morphology. In conclusion, the well-defined interpenetrating network morphology affords an efficiency of 19.02% on small-area cells and 17.28% on 1 cm 2 devices.

14 SOLAR ENERGY↗