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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High-Throughput Characterization and Optimization of Polyamide Hydrolase Activity Using Open Port Sampling Interface Mass Spectrometry

Enzymatic biodegradation of polymers, such as polyamides (PA), has the potential to cost-effectively reduce plastic waste, but enhancements in degradation efficiency are needed. Engineering enzymes through directed evolution is one pathway toward identification of critical domains needed for improving activity. However, screening such enzymatic libraries (100s-to-1000s of samples) is time-consuming. Here we demonstrate the use of robotic autosampler (PAL) and immediate drop on demand technology (I.DOT) liquid handling systems coupled with open-port sampling interface-mass spectrometry (OPSI-MS) to screen for PA6 and PA66 hydrolysis by 6-aminohexanoate-oligomer endo-hydrolase (nylon hydrolase, NylC) in a high-throughput (8–20 s/sample) manner. The OPSI-MS technique required minimal sample preparation and was amenable to 96-well plate formats for automated processing. Enzymatic hydrolysis of PA characteristically produced soluble linear oligomer products that could be identified by OPSI-MS. Incubation temperatures and times were optimized for PA6 (65 °C, 24 h) and PA66 (75 °C, 24 h) over 108 experiments. In addition, the I.DOT/OPSI-MS quantified production of PA6 linear dimer (8.3 ± 1.6 μg/mL) and PA66 linear monomer (13.5 ± 1.5 μg/mL) by NylC with a lower limit of detection of 0.029 and 0.032 μg/mL, respectively. For PA6 and PA66, linear oligomer production corresponded to 0.096 ± 0.018% and 0.204 ± 0.028% conversion of dry pellet mass, respectively. The developed methodology is expected to be utilized to assess enzymatic hydrolysis of engineered enzyme libraries, comprising hundreds to thousands of individual samples.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Truncating 2D Framework Materials Down to a Single Pore: Synthetic Approaches and Opportunities

Here, in this Accounts article, we summarize our recent work on truncating conjugated two-dimensional framework materials down to a single pore, or a single macrocycle. Conjugated 2D architectures have emerged as one of the most synthetically adaptable motifs for coupling semiconductivity and porosity in metal–organic frameworks (MOFs) and covalent organic frameworks (COFs). However, despite their prevalence, 2D architectures have several limitations. In particular, the strong interlayer π–π stacking can limit both processability and the accessibility of internal active sites. We have found that simple macrocycles preserve key aspects of 2D framework structure and function, including porosity and out-of-plane electrical conductivity, while providing improved processability, surface tunability, and mass transport properties. In this article, we first describe our synthetic approach and general design considerations. Specifically, we show how ditopic analogues of the tritopic ligands commonly found in the synthesis of 2D MOFs and COFs can be used to achieve a diverse library of conjugated macrocycles that resemble fragments of semiconducting frameworks in both form and function. The length of the peripheral side chains, the size of the aromatic core, and the solubility of intermediates are all key variables in favoring selective macrocycle formation over undesired linear polymers and oligomers. Next, we highlight the unique advantages that macrocycles provide, including improved processability, atomically precise surface tunability, and greater active site accessibility. In particular, the identity of the peripheral side chains dramatically impacts both solubility and colloidal stability as well as crystal size and morphology. We further show how the solution processability and nanoscale dimensions of macrocycles can simplify electronic device fabrication and improve electrochemical performance. Finally, we end with a forward-looking discussion on how macrocycles offer a unique bridge between conjugated molecules and extended frameworks, enabling new application areas and fundamental science.

charge transport↗
DOE OSTI2022

Ultrafast infrared plasmon switching in aligned carbon-nanotube optical resonators

Reconfigurable plasmonic materials are crucial components in active photonic devices for optical communication, signal processing, and sensing applications. Certain candidates including transparent conducting oxides, small-bandgap semiconductors (i.e. Ge, InSb), and conducting polymers can exhibit switchable free carrier concentrations triggered by optical, electrical or thermal excitations. Here, we show that aligned films of single-walled carbon nanotubes (SWCNTs) can serve as all-optically tunable plasmonic material in the mid-infrared range, thereby adding them to the library of switchable plasmonic materials. Interband optical pumping with femtosecond laser pulses results in the photoexcitation of free charge carriers, which transiently blueshifts the plasmon resonances of patterned, periodic SWCNT nano-resonators spanning the mid-infrared spectral range from 1700 to 2700 cm -1 . Furthermore. the ultrafast plasmon modulation exhibits a nearly single-picosecond decay time, attributed to interband carrier relaxation and inter-tube charge transfer. Given that aligned films of SWCNTs have high thermal stability, excellent photostability, epsilon-near-zero property, and extremely large optical anisotropy, their dynamic tunability represents a promising pathway towards active optical devices in the technologically important mid-infrared range.

single-walled carbon nanotubes↗
DOE OSTI2023

ABF DFO with Technology Holding, Inc.

This Agile BioFoundry Directed Funding Opportunity project with Technology Holding and partners focuses on the development of both a strain of Pseudomonas putida KT2440 and a corresponding bioprocess to convert cellulosic sugars to beta-ketoadipic acid, which can be used in performance nylons and polyesters. Our approach follows the Design-Build-Test-Learn cycle wherein we have transferred learnings from muconic acid production in P. putida to develop a glucose and xylose-utilizing beta-ketoadipic acid production strain. This strain achieves 65 g/L of beta-ketoadipic acid at 0.7 g/L/hr and a C-mol yield of 0.40. We are currently on-boarding arabinose utilization as well. To identify non-intuitive strain modifications as well, we are deploying a beta-ketoadipic acid biosensor and building randomly barcoded transposon insertion sequencing (RB-TnSeq) libraries and gene over-expression libraries in beta-ketoadipic acid production strains. Moreover, we are using global metabolomics and other systems biology tools to identify off-target pathways. Lastly, we are scaling up beta-ketoadipic acid production to kg-scale production for Technology Holding to evaluate in performance polymers with their partners.

beta-ketoadipic acid↗
DOE OSTI2022

LigninGraphs: lignin structure determination with multiscale graph modeling

Lignin is an aromatic biopolymer found in ubiquitous sources of woody biomass. Designing and optimizing lignin valorization processes requires a fundamental understanding of lignin structures. Experimental characterization techniques, such as 2D-heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra, could elucidate the global properties of the polymer molecules. Computer models could extend the resolution of experiments by representing structures at the molecular and atomistic scales. We introduce a graph-based multiscale modeling framework for lignin structure generation and visualization. The framework employs accelerated rejection-free polymerization and hierarchical Metropolis Monte Carlo optimization algorithms. We obtain structure libraries for various lignin feedstocks based on literature and new experimental NMR data for poplar wood, pinewood, and herbaceous lignin. The framework could guide researchers towards feasible lignin structures, efficient space exploration, and future kinetics modeling. Its software implementation in Python, LigninGraphs, is open-source and available on GitHub.

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

Highly stretchable ionically crosslinked acrylate elastomers inspired by polyelectrolyte complexes

Dynamic bonds are a powerful approach to tailor the mechanical properties of elastomers and introduce shape-memory, self-healing, and recyclability. Among the library of dynamic crosslinks, electrostatic interactions among oppositely charged ions have been shown to enable tough and resilient elastomers and hydrogels. In this work, we investigate the mechanical properties of ionically crosslinked ethyl acrylate-based elastomers assembled from oppositely charged copolymers. Using both infrared and Raman spectroscopy, we confirm that ionic interactions are established among polymer chains. We find that the glass transition temperature of the complex is in between the two individual copolymers, while the complex demonstrates higher stiffness and more recovery, indicating that ionic bonds can strengthen and enhance recovery of these elastomers. We compare cycles to increasing strain levels at different strain rates, and hypothesize that at fast strain rates ionic bonds dynamically break and reform while entanglements do not have time to slip, and at slow strain rates ionic interactions are disrupted and these entanglements slip significantly. Further, we show that a higher ionic to neutral monomer ratio can increase the stiffness, but its effect on recovery is minimal. Lastly, taking advantage of the versatility of acrylates, ethyl acrylate is replaced with the more hydrophilic 2-hydroxyethyl acrylate, and the latter is shown to exhibit better recovery and self-healing at a cost of stiffness and strength. The design principles uncovered for these easy-to-manufacture polyelectrolyte complex-inspired bulk materials can be broadly applied to tailor elastomer stiffness, strength, inelastic recovery, and self-healing for various applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Renewable low viscosity polyester-polyols for biodegradable thermoplastic polyurethanes

In the transition to renewably sourced, biodegradable polymers, the preparation of low viscosity polyester-polyols has posed a challenge for renewable polyurethane (PU) development. Low viscosity polyols not only reduce the requirement for high process temperatures but also decrease manufacturing time. In our efforts to incorporate increasing ratios of bio-based monomers into renewable PUs, we mixed diacids such as even carbon sebacic acid and odd carbon azelaic acid along with a renewable diol. This provided library of 2000 g/mol molecular weight polyester-polyols, and structures were established by 1 H and 13 C NMR analysis. The prepared polyester-polyols offered lower viscosity and enable lower fabrication temperatures to make TPUs, and their structure and material metrics were evaluated. The formation of TPUs is ascertained from FTIR and NMR analysis. The final TPUs displayed good physical and mechanical properties. Further, these TPUs exhibited T g in the range of -56.5 to -39.7°C, corresponding to TPU soft block structure, and T m between 98.3 and 105.1°C originating from the hard segment. Prepared TPUs exhibit excellent biodegradation under compost environmental conditions. These TPUs showed up to 57% decrease in molecular weight by GPC analysis after 9 weeks of biodegradation, and respirometer analysis displayed up to 97% biodegradation over 120 days.

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

RB-TnSeq elucidates dicarboxylic-acid-specific catabolism in β-proteobacteria for improved plastic monomer upcycling

Dicarboxylic acids are key components of many polymers and plastics, making them a target for both engineered microbial degradation and sustainable bioproduction. In this study, we generated a comprehensive data set of functional evidence for the genetic basis of dicarboxylic and fatty acid metabolism using randomly barcoded transposon sequencing (RB-TnSeq). We identified four β-proteobacteria that displayed robust growth with dicarboxylic acid sole carbon source and cultured their mutant libraries with dicarboxylic and fatty acids with carbon chain lengths from C3 to C12. The resulting fitness data suggested that dicarboxylic and fatty acid metabolisms are largely distinct, and different sets of β-oxidation genes are required for catabolizing dicarboxylic versus fatty acids of the same carbon chain lengths. In addition, we identified transcriptional regulators and transporters with strong fitness phenotypes related to dicarboxylic acid utilization. In Ralstonia sp. UNC404CL21Col (R. CL21), we deleted two transcriptional repressors to improve its utilization of short-chain dicarboxylic acids. We exploited the diacid-utilizing catabolism of R. CL21 to upcycle a mock mixture of the dicarboxylic acids produced when polyethylene is oxidized. After introducing a heterologous indigoidine production pathway, this engineered Ralstonia produced 0.56 ± 0.02 g/L indigoidine from a mixture of dicarboxylic acids as a carbon source, demonstrating the potential of R. CL21 to upcycle plastic wastes to products derived from tricarboxylic acid (TCA) cycle intermediates. IMPORTANCE: Upcycling the carbon in plastic wastes to value-added products is a promising approach to address the plastic waste and climate crises, and dicarboxylic acid metabolism is an important facet of several approaches. Improving our understanding of the genetic basis of this metabolism has the potential to uncover new enzymes and genetic parts for engineered pathways involving dicarboxylic acids. Our data set is the most comprehensive interrogation of dicarboxylic acid catabolism to date, and this work will be of utility to researchers interested in both plastics bioproduction and upcycling applications.

Pearson, Allison N↗
DOE OSTI2021

Progress Towards a New Model Chemolithoautotrophic Host (CRADA Final Report)

Some of the largest scale chemical processes for the production of important commodity chemicals and fuels involve an H 2 -containing gas mixture as an intermediate [e.g. ammonia, urea, methanol, Fischer-Tropsch (F-T) diesel, and hydrotreatment of crude petroleum to refined fuels]. The successful development of a model H 2 -oxidizing chemoautotrophic host could expand the range of fuels and chemicals produced from H 2 and CO 2 intermediates in the chemical, oil, and gas sectors in the near term, as well as from renewable and waste-derived sources of these gases that are expected to greatly expand in coming years. Among non-photosynthetic bacteria that can utilize H 2 and CO 2 , Cupriavidus necator (C. necator, formerly Ralstonia eutropha), is the best studied. C. necator is an excellent microbial host for the production of a variety of chemicals because it grows extremely quickly to very high cell densities autotrophically on H 2 and CO 2 , is genetically tractable, and has the ability to accumulate polymers, such as polyhydroxybutyrate, at industrial levels. Despite having great potential as a platform bioproduction host, genetic tools are limited, making metabolic engineering of this organism slow and laborious. In this CRADA project, we developed a number of genetic tools for C. necator: 1) Improvement of C. necator genetic transformation efficiency 2) Integration of heterologous genes into the C. necator chromosome and development of promoter library 3) Development of graded RBSs to control heterologous protein expression 4) Use of RBSs to demonstrate fatty alcohol production in C. necator 5) Demonstration of CRISPR-Cas9 gene editing in C. necator

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

An exopolysaccharide pathway from a freshwater Sphingomonas isolate

Bacteria embellish their cell envelopes with a variety of specialized polysaccharides. Biosynthesis pathways for these glycans are complex, and final products vary greatly in their chemical structures, physical properties, and biological activities. This tremendous diversity comes from the ability to arrange complex pools of monosaccharide building blocks into polymers with many possible linkage configurations. Due to the complex chemistry of bacterial glycans, very few biosynthetic pathways have been defined in detail. As part of an initiative to characterize novel polysaccharide biosynthesis enzymes, we isolated a bacterium from Lake Michigan called Sphingomonas sp. LM7 that is proficient in exopolysaccharide (EPS) production. We identified genes that contribute to EPS biosynthesis in LM7 by screening a transposon mutant library for colonies displaying altered colony morphology. A gene cluster was identified that appears to encode a complete wzy/wzx-dependent polysaccharide assembly pathway. Deleting individual genes in this cluster caused a non-mucoid phenotype and a corresponding loss of EPS secretion, confirming the role of this gene cluster in polysaccharide production. We extracted EPS from LM7 cultures and determined that it contains a linear chain of 3- and 4-linked glucose, galactose, and glucuronic acid residues. Finally, we show that the EPS pathway in Sphingomonas sp. LM7 diverges from that of sphingan-family EPSs and adhesive polysaccharides such as the holdfast that are present in other Alphaproteobacteria. Our approach of characterizing complete biosynthetic pathways holds promise for engineering polysaccharides with valuable properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Superlative mechanical energy absorbing efficiency discovered through self-driving lab-human partnership

Energy absorbing efficiency is a key determinant of a structure’s ability to provide mechanical protection and is defined by the amount of energy that can be absorbed prior to stresses increasing to a level that damages the system to be protected. Here, we explore the energy absorbing efficiency of additively manufactured polymer structures by using a self-driving lab (SDL) to perform >25,000 physical experiments on generalized cylindrical shells. We use a human-SDL collaborative approach where experiments are selected from over trillions of candidates in an 11-dimensional parameter space using Bayesian optimization and then automatically performed while the human team monitors progress to periodically modify aspects of the system. The result of this human-SDL campaign is the discovery of a structure with a 75.2% energy absorbing efficiency and a library of experimental data that reveals transferable principles for designing tough structures.

42 ENGINEERING↗
DOE OSTI2022

On the Response of a Herschel–Bulkley Fluid Due to a Moving Plate

In this paper, we study the boundary-layer flow of a Herschel–Bulkley fluid due to a moving plate; this problem has been experimentally investigated by others, where the fluid was assumed to be Carbopol, which has similar properties to cement. The computational fluid dynamics finite volume method from the open-source toolbox/library OpenFOAM is used on structured quad grids to solve the mass and the linear momentum conservation equations using the solver “overInterDyMFoam” customized with non-Newtonian viscosity libraries. The governing equations are solved numerically by using regularization methods in the context of the overset meshing technique. The results indicate that there is a good comparison between the experimental data and the simulations. The boundary layer thicknesses are predicted within the uncertainties of the measurements. The simulations indicate strong sensitivities to the rheological properties of the fluid.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Harnessing ionic complexity: A modeling approach for hierarchical ionic circuit design

Since the 1950s, soft ionic devices have evolved from individual components to an expanding library of sensors, actuators, signal transmitters, and processors. However, integrating these components into complex, multifunctional systems remains challenging due to the nonintuitive and nonlinear interactions between ionic elements. In this work, we address these fundamental challenges by developing a lumped element model that enables interrogation of the physics that governs ionic circuits, as well as rapid design and optimization. Our model captures features specific to ionic charge carriers, while preserving the hierarchical design flexibility and computational efficiency of traditional circuit modeling. We demonstrate that our model can not only fit individual device behavior but also accurately predict the behavior of larger circuits formed by combining those devices. Additionally, we show how our tool utilizes the intrinsic nonlinearities of ionic systems to enable extended functionality, revealing how factors such as ion enrichment, ion leakage, and polymer charge density influence performance. Lastly, we present a fully ionic power supply, sensor, control system, and actuator for a soft robot that adapts its motion in response to environmental salt, illustrating the tool’s potential to accelerate advancements in chemical sensing, biointerfacing, biomimetic systems, and adaptive materials.

42 ENGINEERING↗
DOE OSTI2022

Priming self-assembly pathways by stacking block copolymers

Abstract Block copolymers spontaneously self-assemble into well-defined nanoscale morphologies. Yet equilibrium assembly gives rise to a limited set of structures. Non-equilibrium strategies can, in principle, expand diversity by exploiting self-assembly’s responsive nature. In this vein, we developed a pathway priming strategy combining control of thin film initial configurations and ordering history. We sequentially coat distinct materials to form prescribed initial states, and use thermal annealing to evolve these manifestly non-equilibrium states through the assembly landscape, traversing normally inaccessible transient structures. We explore the enormous associated hyperspace, spanning processing (annealing temperature and time), material (composition and molecular weight), and layering (thickness and order) dimensions. We demonstrate a library of exotic non-native morphologies, including vertically-oriented perforated lamellae, aqueduct structures (vertical lamellar walls with substrate-pinned perforations), parapets (crenellated lamellae), and networks of crisscrossing lamellae. This enhanced structural control can be used to modify functional properties, including accessing regimes that surpass their equilibrium analogs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

A critical review and commentary on recent progress of additive manufacturing and its impact on membrane technology

Membrane separations has been increasingly recognized as a key technology platform for improving the energy efficiency of many separations processes. Likewise, additive manufacturing (AM), or 3-dimensional (3D) printing as it is often called, is a rapidly emergent technology platform for manufacturing in many industrial sectors. It has become increasingly common to marry these two platforms to take advantage of the additive nature of 3D printing with the increasing need for membrane technology that is adaptable to separations needs. Conventional membrane manufacturing approaches, such as casting, typically result in thick membranes that limit productivity and potentially waste material in a non-performing support layer. Interfacial polymerization (IP) offered a new vision for thin-film composite desalination membranes, yet it was limited to certain chemistries while exhibiting other drawbacks. Additive manufacturing offers certain benefits over these techniques to membranes, including the ability to expand the library of materials that can be processed while also offering a degree of customization that is impossible in conventional manufacturing. This review article evaluates an increasing body of literature on using printing to make membranes and considers the limitations and opportunities for printing to enhance existing membrane technology and expand the reach of membranes into other industries. Furthermore, we also provide a perspective from leading experts in membrane technology to see where there are opportunities to use printing in different membrane science disciplines.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Exploring Microphase Separation in Semi-Fluorinated Diblock Copolymers: A Combined Experimental and Modeling Investigation

We report the combined experimental and theoretical study of the bulk self-assembly behavior of polystyrene-blockpoly( 2,3,4,5,6-pentafluorostyrene) diblock copolymers. These block copolymers were designed to create highly antagonistic blocks (with a high Flory−Huggins interaction parameter, χ) with minimum disruption to the molecular construct (i.e., only replacing five hydrogen atoms with five fluorine atoms). A large library of diblock copolymers (41 samples) was synthesized by reversible addition− fragmentation chain transfer (RAFT) polymerization to map out a major portion of the phase space. All block copolymers exhibited narrow molecular weight distributions with dispersity (D) values between 1.07 and 1.32, and subsequent thermal annealing revealed phase separation into well-defined nanoscale morphologies depending on their molecular composition, as determined from small-angle X-ray scattering and transmission electron microscopy analyses, with an experimental phase diagram being constructed. The χ value at 25 °C for this block copolymer was estimated to be 0.2 using strong segregation theory, based on trends in phase-separated domain spacing and interfacial width. When applying theoretical approaches, the majority of the domain spacing data trends were captured by a coil−coil diblock copolymer model; however, a better fit to the data for samples with shorter fluorinated blocks was obtained with a rod−coil model, indicating that the chains in these fluorinated blocks likely have a higher inherent stiffness and were thus rod-like. This observation demonstrates that, due to the very high value of χ, a transition from coil−coil to rod−coil behavior can be obtained purely by reducing the length of the stiffer of the two blocks and without varying temperature or the chemical composition of the polymers. Here, this work showcases the presence of strong microphase separation within AB diblock copolymers despite the relatively similar chemical composition of the constituent “A” and “B” units, with a clear transition from rod−coil to coil−coil segregation behavior.

RAFT polymerization↗
DOE OSTI2023

Novel Chalcopyrites for Advanced Photoelectrochemical Water Splitting

With the support of DoE’s EERE office, our team has established a unique tool-chest of capabilities, including theoretical modeling (Lawrence Livermore National Laboratory: LLNL), state-of-the-art synthesis (Hawaii Natural Energy Institute: HNEI, Stanford, and the National Renewable Energy Laboratory: NREL) and advanced materials and interfaces characterization (University of Nevada, Las Vegas: UNLV, and Lawrence Berkeley National Laboratory: LBNL), to accelerate the development of high efficiency and durable chalcopyrite materials for advanced photoelectrochemical (PEC) water splitting. Using this synergistic approach, we have successfully created new wide bandgap chalcopyrite photocathodes generating over 10 mA/cm 2 , developed innovative strategies to protect them from corrosion, and engineered novel integration methods to circumvent thin film materials mechanical, chemical and thermal incompatibility. In Task 1 “Modeling and synthesis of chalcopyrite photocathodes”, we expanded our library of wide bandgap chalcopyrites for PEC water splitting. With support from LLNL’s “Computational Materials Diagnostics and Optimization of PEC Devices”, LBNL’s “photophysical” and NREL’s “I-III-VI Compound Semiconductors for Water-Splitting” nodes, we investigated two new chalcopyrite candidates for PEC water splitting: Cu(In,Al)Se 2 and Cu(In,B)Se 2 . We also further developed ordered vacancy compounds, such as CuGa 3 Se 5 , with unprecedented durability during PEC waters splitting in acidic solutions. In Task 2 “Interfaces engineering for enhanced efficiency and durability”, we addressed both the non-ideal band-edge positions of chalcopyrites with respect to water redox potentials, as well as their chemical instability under PEC water splitting, with a buried-junctions approach. With help from NREL’s “High-Throughput Experimental Thin Film Combinatorial Capabilities” and “Corrosion Analysis of Materials” nodes, we engineered environmentally friendly n-type buffers, including Mn x Zn 1-x O, to adjust the chalcopyrite band-edge positions and achieved photovoltages as high as 925 mV. Also, we integrated non-precious catalytic-protecting layers, such as WO 3 , to enhance the water splitting long-term stability of chalcopyrite absorbers. Finally, in Task 3 “Hybrid photoelectrode device integration”, we proposed an innovative method to bond wide bandgap photocathodes onto narrow bandgap PV drivers at room temperature using conductive polymers. Our semi-monolithic approach addressed fundamental processing incompatibility issues, as both the photocathode and the PV driver are processed separately. Proof-of-concept whole-chalcopyrite tandems were obtained by consecutive exfoliation and transfer of fully integrated 1.85 eV CuGa 3 Se 5 and 1.13 eV CuInGaSe 2 stacks from their Mo/SLG substrates onto a new single FTO host substrate.

08 HYDROGEN↗
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↗