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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The importance of sulfonate to the self-doping mechanism of the water-soluble conjugated polyelectrolyte PCPDTBT-SO 3 K

The conjugated polyelectrolyte poly[2,6-(4,4-bis-potassium butanylsulfonate-4H-cyclopenta-[2,1-b;3,4-b']-dithiophene)-alt-4,7-(2,1,3-benzothiadiazole)] (PCPDTBTSO 3 K, or CPE-K) is part of a unique class of organic semiconducting polymers that are soluble in water and become doped in the presence of a proton source. One of these proton sources is water, which CPE-K is exposed to during purification by dialysis, allowing for its immediate use without an additional doping step. Previous studies have suggested that the actual dopant is H + , and that the addition of sodium hydroxide to CPE-K reverses the process and de-dopes the polymer. Curiously, the majority of these water-soluble self-doped polymers in the literature contain a pendant sulfonate group. However, a detailed study to gain insight into the importance of the sulfonate group in water-soluble self-doped polymer systems is lacking, despite its widespread presence in the literature. In this work, using Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and ultraviolet-visible-near infrared (UV-vis-NIR) absorption spectroscopy, we are able to elucidate the role of the pendant sulfonate group with regards to the fundamental doping mechanism of CPE-K. Specifically, we found the CPDT unit can be protonated by water, which is due to both the stabilizing influence of the sulfonate group, and the relatively high oxidation potential of the CPDT unit, both of which are required for self-doped water soluble polymer systems. Furthermore, we estimate the doping efficiency of CPE-K using electrical measurements and X-ray reflectivity (XRR), and reveal several different methods for the doping and de-doping of this material, showcasing this particular material's superior versatility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Predicting the chemical reactivity of organic materials using a machine-learning approach

Stability and compatibility between chemical components are essential parameters that need to be considered in the selection of functional materials in configuring a system. In configuring devices such as batteries or solar cells, not only the functionality of individual constituting materials such as electrodes or electrolyte but also an appropriate combination of materials which do not undergo unwanted side reactions is critical in ensuring their reliable performance in long-term operation. While the universal theory that can predict the general chemical reactivity between materials is long awaited and has been the subject of studies with a rich history, traditional ways proposed to date have been mostly based on simple electronic properties of materials such as electronegativity, ionization energy, electron affinity and hardness/softness, and could be applied to only a small group of materials. Moreover, prediction has often been far from accurate and has failed to offer general implications; thus it was practically inadequate as a selection criterion from a large material database, i.e. data-driven material discovery. Herein, we propose a new model for predicting the general reactivity and chemical compatibility among a large number of organic materials, realized by a machine-learning approach. As a showcase, we demonstrate that our new implemented model successfully reproduces previous experimental results reported on side-reactions occurring in lithium–oxygen electrochemical cells. Furthermore, the mapping of chemical stability among more than 90 available electrolyte solvents and the representative redox mediators is realized by this approach, presenting an important guideline in the development of stable electrolyte/redox mediator couples for lithium–oxygen batteries.

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

Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces

The performance of functional materials is dictated by chemical and structural properties of individual atomic sites. In catalysts, for instance, the thermodynamic stability of constituting atomic sites is a key descriptor from which more complex properties, such as molecular adsorption energies and reaction rates, can be derived. In this study, we present a widely applicable machine learning (ML) approach to instantaneously compute the stability of individual atomic sites in structurally and electronically complex nano-materials. Conventionally, we determine such site stabilities using computationally intensive first-principles calculations. With our approach, we predict the stability of atomic sites in sub-nanometer metal clusters of 3–55 atoms with mean absolute errors in the range of 0.11–0.14 eV. To extract physical insights from the ML model, we introduce a genetic algorithm (GA) for feature selection. This algorithm distills the key structural and chemical properties governing the stability of atomic sites in size-selected nanoparticles, allowing for physical interpretability of the models and revealing structure–property relationships. The results of the GA are generally model and materials specific. In the limit of large nanoparticles, the GA identifies features consistent with physics-based models for metal–metal interactions. By combining the ML model with the physics-based model, we predict atomic site stabilities in real time for structures ranging from sub-nanometer metal clusters (3–55 atom) to larger nanoparticles (147 to 309 atoms) to extended surfaces using a physically interpretable framework. Finally, we present a proof of principle showcasing how our approach can determine stable and active nanocatalysts across a generic materials space of structure and composition.

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

Alkyl decorated metal–organic frameworks for selective trapping of ethane from ethylene above ambient pressures

Here the trapping of paraffins is beneficial compared to selective olefin adsorption for adsorptive olefin purification from a process engineering point of view. Here we demonstrate the use of a series of Zn 2 (X-bdc) 2 (dabco) (where X-bdc 2- is bdc 2- = 1,4-benzenedicarboxylate with substituting groups X, DM-bdc 2- = 2,5-dimethyl-1,4-benzenedicarboxylate or TM-bdc 2- = 2,3,5,6-tetramethyl-1,4-benzenedicarboxylate and dabco = diazabicyclo[2.2.2.]octane) metal-organic frameworks (MOFs) for the adsorptive removal of ethane from ethylene streams. The best performing material from this series is Zn2(TM-bdc)2(dabco) (DMOF-TM), which shows a high ethane uptake of 5.31 mmol g -1 at 110 kPa, with a good IAST selectivity of 1.88 towards ethane over ethylene. Through breakthrough measurements a high productivity of 13.1 L/kg per breakthrough is revealed with good reproducibility over five consecutive cycles. Molecular simulations show that the methyl groups of DMOF-TM are forming a van der Waals trap with the methylene groups from dabco, snuggly fitting the ethane. Further, rarely used high pressure coadsorption measurements, in pressure regimes that most scientific studies on hydrocarbon separation on MOFs ignore, reveal an increase in ethane capacity and selectivity for binary mixtures with increased pressures. The coadsorption measurements reveal good selectivity of 1.96 at 1000 kPa, which is verified also through IAST calculations up to 3000 kPa. This study overall showcases the opportunities that pore engineering by alkyl group incorporation and pressure increase offer to improve hydrocarbon separation in reticular materials.

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

Mechanistic Investigation of Redox Processes in Zn-MnO2 battery in Mild Aqueous Electrolytes

Zinc-MnO2 based batteries have acquired attention for grid-level applications, due to impressive theoretical performance, cost effectiveness and intrinsic safety. However, there are still many challenges that remain elusive due to the complex and controversial mechanisms of operation that hinders commercialization. In this work, the detailed redox processes that occur at the cathode during Zn-MnO2 battery operation are elucidated. Using a blend of structural and electrochemical techniques, the redox pairs that occur during operation are mechanistically studied while also showcasing the true impact of the electrolyte additive (0.1 M MnSO4) in a 1 M ZnSO4 electrolyte. An electrochemical quartz-crystal microbalance (EQCM) has been leveraged to reveal the effect of zinc hydroxy sulfate salt (Zn4SO4(OH)6·nH2O) and zinc manganese oxide (ZnxMnyOz) dissolution/deposition, which are believed to be major components during discharge and charge conditions. . These results provide insight not currently available, allowing a holistic view of the electrochemical reaction mechanisms during battery operation.

Rodriguez Perez, Ismael A.↗
DOE OSTI2022

Copper(ii)-photocatalyzed decarboxylative oxygenation of carboxylic acids

Showcasing the concept of light-induced homolysis for the generation of radicals, the Cu II -photocatalyzed decarboxylative oxygenation of carboxylic acids with molecular oxygen as the terminal oxidant is described. Here, two Cu II -carboxylate complexes with different coordination geometries were synthesized and characterized by X-ray analysis, correlating their structure with their ability to initiate light-induced decarboxylations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

“Breathing” organic cation to stabilize multiple structures in low-dimensional Ge-, Sn-, and Pb-based hybrid iodide perovskites

Low-dimensional hybrid inorganic–organic perovskites are excellent candidates for stable optoelectronic devices. The dimensionality of these perovskites depends largely on the organic and inorganic compositions, as well as the synthetic conditions. We report five new hybrid iodides, (ETU) 4 Ge 5 I 18 , (ETU)GeI 4 , (ETU)SnI 4 , (ETU)PbI 4 , and (ETU) 3 Pb 2 I 10 using only one type of organic cation, namely, S-(2-aminoethyl)isothiouronium (ETU). (ETU)GeI 4 and (ETU)SnI 4 belong to the (110)-oriented structure-type with “3 × 3” sawtooth corrugated layers and crystallize in a structure with the orthorhombic space group Pbca. (ETU) 4 Ge 5 I 18 crystallizes in a structure with the triclinic space group P$\bar{1}$with combining macron], featuring a 2D layered structure with combinations of corner, edge, and face-sharing [GeI 6 ] octahedra. For the Pb-based series, (ETU)PbI 4 has the conventional (100) – oriented 2D type whereas (ETU) 3 Pb 2 I 10 has a unique 0D structure. Remarkably, the unstable 2D orange-phase (ETU)PbI 4 transforms to a stable 0D yellow phase (ETU) 3 Pb 2 I 10 , accompanied by the reduction of the C–S–C angle of the organic cation ETU. The optical band gaps are largely regulated by the diverse types of structure and are in the range of 1.8 eV to 2.8 eV. (ETU)SnI 4 is the only material showing notable photoluminescence at room-temperature. Our work showcases the flexibility of the organic cation in determining the structural dimensionality and provides a new strategy in generating new hybrid materials.

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

Active learning of chemical reaction networks via probabilistic graphical models and Boolean reaction circuits

Discerning networks of many reactions among multiple interconverting species is challenging. Here, we present a reaction network identification methodology. Our methodology enumerates all stoichiometrically and chemically feasible reactions and requires statistical evidence from effluent concentrations for the inclusion or exclusion of each from the reaction network, contrasting with the commonly seen incremental approach and other work of relying heavily upon chemical intuition and assuming the reactions occurring. Using graph theory alongside an active learning design of experiments that propose maximally informative feeds, we identify the underlying reaction network with minimal laboratory runs. Here, we introduce chemistry-probabilistic graphical modeling and Boolean reaction circuits to statistically quantify which reactions occur from effluent concentrations. Our methodology accurately discerns active reactions, as showcased upon a laboratory network of cross-ketonization of furoic and lauric acid and validated upon simulated networks of thermal and CO 2 -assisted ethane dehydrogenation.

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

Spatially resolved multimodal vibrational spectroscopy under high pressures

In this perspective, we discuss the potential impact on in situ studies under controlled environments of a novel multimodal spectroscopic technique, optical photothermal infrared + Raman spectroscopy, which enables the simultaneous collection of infrared and Raman scattering spectra, along with hyperspectral imaging and chemical imaging with wavelength-independent sub-500 nm spatial resolution. A brief review of the current literature regarding the O-PTIR technique is presented along with recent work from our own lab on determining the crystallinity of soft and inorganic materials. The results highlight the possibility of resolving differences in the crystallinity of soft materials associated with changes in material processing. Here, we also demonstrate the first reported use of a diamond anvil cell with simultaneous infrared and Raman measurements that showcases, using a high energy material as an example, the potential use of O-PTIR spectroscopy in diamond anvil cell techniques.

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

Strategies for designing biocatalysts with new functions

Enzymes can be optimized to accelerate chemical transformations via a range of methods. In this review, we showcase how protein engineering and computational design techniques can be interfaced to develop highly efficient and selective biocatalysts.

09 BIOMASS FUELS↗
DOE OSTI2023

Uncovering novel liquid organic hydrogen carriers: a systematic exploration of chemical compound space using cheminformatics and quantum chemical methods

We present a comprehensive, in silico-based discovery approach to identifying novel liquid organic hydrogen carrier (LOHC) candidates using cheminformatics methods and quantum chemical calculations. We screened over 160 billion molecules from ZINC15 and GDB-17 chemical databases for structural similarity to known LOHCs and employed a data-driven selection criterion connecting molecular features with dehydrogenation enthalpy. This scoring criterion effectively predicts dehydrogenation enthalpies from SMILES strings, streamlining the LOHC screening process. After rigorous screening and down-selection, we compiled a database of 3000 dehydrogenation reactions for the most promising LOHC candidates, setting the stage for future selection based on kinetics and catalysis. This work demonstrates the significant impact of integrating quantum chemistry and cheminformatics in materials discovery, accelerating the selection process while reducing experimental efforts and time. By proposing new molecules as prospective LOHC candidates, our study provides a valuable resource for researchers and engineers in the development of advanced LOHC systems and showcases a successful approach for high-throughput discovery, contributing to more efficient and sustainable energy storage solutions.

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

All-day passive radiative cooling using common salts

An infrared transparent foam made from inexpensive salts was developed enabling sub-ambient cooling of underlying surfaces for a full 24 hour cycle. This work showcases how non-convetional materials may be used for passive day-time radiative cooling.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Engineering endosomolytic nanocarriers of diverse morphologies using confined impingement jet mixing

The clinical translation of many biomolecular therapeutics has been hindered by undesirable pharmacokinetic (PK) properties, inadequate membrane permeability, poor endosomal escape and cytosolic delivery, and/or susceptibility to degradation. Overcoming these challenges merits the development of nanoscale drug carriers (nanocarriers) to improve the delivery of therapeutic cargo. Herein, we implement a flash nanoprecipitation (FNP) approach to produce nanocarriers of diverse vesicular morphologies by using various molecular weight PEG-bl-DEAEMA-co-BMA (PEG-DB) polymers. We demonstrated that FNP can produce uniform (PDI < 0.1) particles after 5 impingements, and that by varying the copolymer hydrophilic mass fraction, FNP enables access to a diverse variety of nanoarchitectures including micelles, unilamellar vesicles (polymersomes), and multi-compartment vesicles (MCVs). We synthesized a library of 2 kDa PEG block copolymers, with DEAEMA-co-BMA second block molecular weights of 3, 6, 12, 15, 20, and 30 kDa. All formulations were both pH responsive, endosomolytic, and capable of loading and cytosolically delivering small negatively charged molecules – albeit to different degrees. Using a B16.F10 melanoma model, we showcased the therapeutic potential of a lead FNP formulated PEG-DB nanocarrier, encapsulating the cyclic dinucleotide (CDN) cGAMP to activate the stimulator of interferon genes (STING) pathway in a therapeutically relevant context. Collectively, these data demonstrate that an FNP process can be used to formulate pH-responsive nanocarriers of diverse morphologies using a PEG-DB polymer system. As FNP is an industrially scalable process, these data address the critical translational challenge of producing PEG-DB nanoparticles at scale. Furthermore, the diverse morphologies produced may specialize in the delivery of distinct biomolecular cargos for other therapeutic applications, implicating the therapeutic potential of this platform in an array of disease applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Spectroelectrochemical determination of thiolate self-assembled monolayer adsorptive stability in aqueous and non-aqueous electrolytes

Self-assembled monolayers (SAM) are ubiquitous in studies of modified electrodes for sensing, electrocatalysis, and environmental and energy applications. However, determining their adsorptive stability is crucial to ensure robust experiments. Here, in this work, the stable potential window (SPW) in which a SAM-covered electrode can function without inducing SAM desorption was determined for aromatic SAMs on gold electrodes in aqueous and non-aqueous solvents. The SPWs were determined by employing cyclic voltammetry, attenuated total reflectance surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS), and surface plasmon resonance (SPR). The electrochemical and spectroscopic findings concluded that all the aromatic SAMs used displayed similar trends and SPWs. In aqueous systems, the SPW lies between the reductive desorption and oxidative desorption, with pH being the decisive factor affecting the range of the SPW, with the widest SPW observed at pH 1. In the non-aqueous electrolytes, the desorption of SAMs was observed to be slow and progressive. The polarity of the solvent was the main factor in determining the SPW. The lower the polarity of the solvent, the larger the SPW, with 1-butanol displaying the widest SPW. This work showcases the power of spectroelectrochemical analysis and provides ample future directions for the use of non-polar solvents to increase SAM stability in electrochemical applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Photosynthetic biohybrid systems for solar fuels catalysis

Photosynthetic reaction center (RC) proteins are finely tuned molecular systems optimized for solar energy conversion. RCs effectively capture and convert sunlight with near unity quantum efficiency utilizing light-induced directional electron transfer through a series of molecular cofactors embedded within the protein core to generate a long-lived charge separated state with a useable electrochemical potential. Of current interest are new strategies that couple RC chemistry to the direct synthesis of energy-rich compounds. This Feature Article highlights recent work from our lab on RC and RC-inspired hybrid systems that capture the Sun's energy and convert it to chemical energy in the form of H2, a carbon-neutral energy source derived from water. Further, biohybrids made from the Photosystem I (PSI) RC are among the best photocatalytic H2-producing protein hybrids to date. Targeted self-assembly strategies that couple abiotic catalysts to PSI translate to catalyst incorporation at intrinsic PSI sites within thylakoid membranes to achieve complete solar water-splitting systems. RC-inspired biohybrids interface synthetic photosensitizers and molecular catalysts with small proteins to create photocatalytic systems and enable the spectroscopic discernment of the structural features and electron transfer processes that underpin solar-driven proton reduction. In total, these studies showcase the incredible scientific opportunities photosynthetic biohybrid research provides for harnessing the optimal qualities of both artificial and natural photosynthetic systems and developing materials that capture, convert, and store solar energy as a fuel.

14 SOLAR ENERGY↗