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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances

The market for illicit drugs has been reshaped by the emergence of more than 1100 new psychoactive substances (NPS) over the past decade, posing a major challenge to the forensic and toxicological laboratories tasked with detecting and identifying them. Tandem mass spectrometry (MS/MS) is the primary method used to screen for NPS within seized materials or biological samples. The most contemporary workflows necessitate labor-intensive and expensive MS/MS reference standards, which may not be available for recently emerged NPS on the illicit market. Here, we present NPS-MS, a deep learning method capable of accurately predicting the MS/MS spectra of known and hypothesized NPS from their chemical structures alone. NPS-MS is trained by transfer learning from a generic MS/MS prediction model on a large data set of MS/MS spectra. We show that this approach enables a more accurate identification of NPS from experimentally acquired MS/MS spectra than any existing method. We demonstrate the application of NPS-MS to identify a novel derivative of phencyclidine (PCP) within an unknown powder seized in Denmark without the use of any reference standards. We anticipate that NPS-MS will allow forensic laboratories to identify more rapidly both known and newly emerging NPS. NPS-MS is available as a web server at https://nps-ms.ca/, which provides MS/MS spectra prediction capabilities for given NPS compounds. Additionally, it offers MS/MS spectra identification against a vast database comprising approximately 8.7 million predicted NPS compounds from DarkNPS and 24.5 million predicted ESI-QToF-MS/MS spectra for these compounds.

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

A Novel Solid Form of Erlotinib: Synthesis by Heterogeneous Complexation and Characterization by NMR Crystallography

We describe the synthesis of a novel complex of the anticancer "active pharmaceutical ingredient erlotinib (ERL) via heterogeneous nucleation on polished zinc tiles. The resulting product, ERL 2 ·ZnCl 2 , is characterized by single-crystal X-ray diffraction, multinuclear solid-state NMR (ssNMR) spectroscopy, and density functional theory (DFT) calculations. Also characterized are the hydrochloride salt (ERL·HCl) and monohydrate free base (ERL·H 2 O) forms of erlotinib. 13 C ssNMR spectroscopy is useful for site-by-site assignment and rapid fingerprinting, while also providing preliminary structural interpretations, such as the number of molecules in the asymmetric unit. 35 Cl ssNMR can readily differentiate between the chloride ions in ERL·HCl and the covalently bonded chlorine in ERL 2 ·ZnCl 2 . 15 N ssNMR proves to be critical here because of the large isotropic chemical shift differences between ERL·H 2 O, ERL·HCl, and ERL 2 ·ZnCl 2 . The 15 N chemical shift tensors are linked directly to differences in structure and bonding with the aid of DFT calculations. Together, these results demonstrate the utility of multinuclear NMR crystallography for the characterization of solid forms of APIs, especially when other analytical techniques face significant challenges.

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

Highly Active and Stable Palladium Catalysts on Novel Ceria–Alumina Supports for Efficient Oxidation of Carbon Monoxide and Hydrocarbons

Precious metal catalysts with superior low-temperature activity and excellent thermal stability are highly needed in environmental catalysis field. In this study, a novel two-step incipient wetness impregnation (T-IWI) method was developed for the fabrication of a unique and highly stable CeO 2 /Al 2 O 3 support (CA-T). Pd anchored on CA-T exhibited a much higher low-temperature catalytic activity and superior thermal stability in carbon monoxide (CO) and hydrocarbon (HC) oxidations, compared to Pd anchored on conventional CeO 2 /Al 2 O 3 (CA), which was prepared by a one-step IWI method. After aging treatment at 800 °C, the CO oxidation rate on Pd/CA-T (1.69 mmol/(g Pd s)) at 120 °C was 4.1 and 84.5 times of those on Pd/CA (0.41 mmol/(g Pd s)) and Pd/Al 2 O 3 (0.02 mmol/(g Pd s)), respectively. It was revealed that the CA-T support with well-controlled small CeO 2 particles (ca. 12 nm) possessed abundant defects for Pd anchoring, which created rich Pd-CeO 2 interfaces with strengthened interaction between Pd and CeO 2 where oxygen could be efficiently activated. This resulted in the significantly improved oxidation activity and thermal stability of Pd/CA-T catalysts. The T-IWI method developed herein can be applied as a universal approach to prepare highly stable metal oxide-alumina-based supports, which have broad application in environmental catalyst design, especially for automobile exhaust aftertreatment.

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

Identification of Novel Microcystins Using High-Resolution MS and MS n with Python Code

Cyanotoxins called microcystins (MCs) are highly toxic and can be present in drinking water sources. Determining the structure of MCs is paramount because of its effect on toxicity. Though over 300 MC congeners have been discovered, many remain unidentified. In this work, a method is described for the putative identification of MCs using liquid chromatography (LC) coupled with high-resolution (HR) Orbitrap mass spectrometry (MS) and a new bottom-up sequencing strategy. Maumee River water samples were collected during a harmful algal bloom and analyzed by LC–MS with simultaneous HRMS and MS/MS. Unidentified ions with characteristic MC fragments (135 and 213 m/z) were recognized as possible novel MC congeners. An innovative workflow was developed for the putative identification of these ions. Python code was written to generate the potential structures of unidentified MCs and to assign ions after the fragmentation for structural confirmation. The workflow enabled the putative identification of eight previously reported MCs for which standards are not available and two newly discovered congeners, MC-HarR and MC-E(OMe)R.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Molecular Insights into Novel Struvite–Hydrogel Composites for Simultaneous Ammonia and Phosphate Removal

Struvite (NH 4 MgPO 4 ·6H 2 O) mineralization is an effective technique for removing ammonium and phosphate species from wastewater. However, its wider use faces obstacles because of the copresence of various pollutants in wastewater and the additional requirement for magnesium to achieve proper supersaturation conditions. To address these challenges, this study developed novel mineral–hydrogel composites that can remove ammonium and phosphate simultaneously via heterogeneous struvite and calcium phosphate (CaP) mineralization in hydrogel matrices. The composites include in situ formed struvite and CaP mineral seeds, decreasing the nucleation energy barrier of struvite and CaP formation and promoting their heterogeneous nucleation kinetics even under undersaturation conditions in bulk solution. The dual struvite and CaP seeded composites can simultaneously reduce the ammonium and total phosphate concentrations up to 60% (26.3 mg of N/g) and 91% (9.54 mg of P/g), respectively. Furthermore, the average particle sizes in composites were increased from 6.12 to 14.8 nm after wastewater treatment. Moreover, various ions commonly existing in wastewater did not significantly interfere with the removal of ammonium and phosphate. Thus, these new mineral–hydrogel composites can provide an innovative way to lower nutrient levels before discharge to streams. Moreover, encapsulating ammonium and phosphate in mineral-hydrogel composites enables their upcycling in agricultural or biorefinery applications.

Cations↗
DOE OSTI2025

Benchmarking Concentration and Extraction Methods for Wastewater-Based Surveillance of Eight Human Respiratory Viruses: Implications for Rapid Application to Novel Pathogens

To provide early warning and support a rapid response to a novel virus through wastewater surveillance, it would be ideal to understand in advance which concentration and extraction methods are likely to be effective for dPCR-based methods, depending on virus characteristics. In this study, we spiked raw wastewater samples with eight human respiratory viruses and processed them with four methods that concentrate and/or extract nucleic acids from both liquid and solid fractions (Promega, Nanotrap, and InnovaPrep) or only the solid fraction of wastewater (Solids). Our findings provide encouraging evidence that all four methods combined with dPCR could detect an emerging virus in wastewater, although they differed in sensitivity. The pattern of recovery efficiency for adenoviruses, coronaviruses, and influenza A viruses was consistent across methods, with Promega producing higher median recovery efficiencies, while distinct patterns were observed for coxsackieviruses. We also normalized the concentration data with two endogenous fecal indicators, PMMoV and Carjivirus (formerly crAssphage). We found that normalization could reduce method-associated differences if the indicator exhibited a recovery pattern similar to that of the target virus. These findings can guide the selection of concentration and extraction methods for wastewater monitoring based on the properties of target viruses, thus enhancing pandemic preparedness.

Biological and medical sciences↗
DOE OSTI2021

Identification of Known and Novel Monomers for Poly(hydroxyurethanes) from Biobased Materials

Sourcing polymers from biobased materials is desirable for a transition to a more sustainable world. However, finding new monomers sourced from biobased molecules requires extensive experimental effort, due to the fact that most biomolecules lack the functional groups or properties needed to serve as a monomer in a particular polymeric system without chemical modification. In this work, we demonstrate a computational screening method to obtain monomers of a non-isocyanate polyurethane (NIPU), polyhydroxyurethane (PHU), from biomolecules. Our method generates candidate monomers from a list of 15 selected biobased starting molecules by performing chemical transformations that are standard to chemical catalysis and organic synthesis on these starting molecules and then screening the results for molecules with moieties that can be used as monomers for a PHU. Product molecules from two generations of reaction, a total number of 20,057, were analyzed automatically to identify molecules that have two or more epoxy or cyclic carbonate functional groups as candidates for further derivatization. These 21 candidate molecules were then subjected to another two generations of reaction, producing a set of 17,913 additional molecules. Further scrutiny of this set for desired functional groups characterizing PHUs and querying against the PubChem database was carried out, and 15 known molecules that are commercially available were identified, with the desirable features that they are predicted to be derived from biobased starting molecules in four or fewer steps. Moreover, molecule space generated from this process was primarily comprised of molecules that were not known to PubChem, indicating the framework also has the ability to generate novel candidate monomers that originate from biobased starting points.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Novel Multiagent Resource Sharing Algorithm for Control of Advanced Energy Systems

This paper implements a novel resource sharing control strategy on a fuel cell–gas turbine hybrid power system at the National Energy Technology Laboratory’s Hybrid Performance Facility (Hyper). In a fuel cell–gas turbine hybrid power system, the simultaneous interaction of the gas turbine and the fuel cell creates a tightly coupled environment characterized by conflicting dynamics. In this paper, a model-free control approach is applied to solve the tightly coupled control problem posed by this challenging environment. Specifically, this control problem is presented as a resource sharing problem that can be solved using a resource sharing algorithm that is defined based on the distribution construction concept. This algorithm creates computational agents and solves the problem through the distribution and redistribution of shared resources defined as blocks. Furthermore, two agents were created; the first agent (agent 1) controls the gas turbine speed by adjusting the electric load, and the second agent (agent 2) controls the cathode mass flow through the fuel cell using the cold-air bypass valve. A parametric study was performed over the course of 15 experimental tests for both agents 1 and 2 through an evaluation of the responses based on setpoint changes. The algorithm was shown to have behavior comparable to a previously implemented multi-input multioutput state-space controller, which was designed through a model-based control approach. The resource sharing algorithm was able to find stable performance during run-time operations without any prior system knowledge identification on the power plant and without creating models used in traditional control strategies.

25 ENERGY STORAGE↗
DOE OSTI2023

Discovery of Novel Rhizoctonia solani DHFR Inhibitors as Fungicides Using Virtual Screening

Dihydrofolate reductase (DHFR) is an essential enzyme in the folate pathway and has been recognized as a well-known target for antibacterial and antifungal drugs. We discovered eight compounds from the ZINC database using virtual screening to inhibit Rhizoctonia solani (R. solani), a fungal pathogen in crops. These compounds were evaluated with in vitro assays for enzymatic and antifungal activity. Among these, compound Hit8 is the most active R. solani DHFR inhibitor, with the IC 50 of 10.2 μM. The selectivity of inhibition is 22.3 against human DHFR with the IC 50 of 227.7 μM. Moreover, Hit8 has higher antifungal activity against R. solani (EC 50 of 38.2 mg L –1 ) compared with validamycin A (EC 50 of 67.6 mg L –1 ), a well-documented fungicide. These results suggest that Hit8 may be a potential fungicide. Finally, our study exemplifies a computer-aided method to discover novel inhibitors that could target plant pathogenic fungi.

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

Design, Synthesis, and Biological Activity of Novel Ornithine Decarboxylase (ODC) Inhibitors

We here describe the design, synthesis, and biological activity of novel ornithine decarboxylase (ODC) inhibitors that show significantly higher potency in vitro than α-difluoromethylornithine (DFMO), a U.S. Food and Drug Administration (FDA) approved drug. We report two X-ray structures of ODC complexed with new ODC inhibitors, computational docking, molecular dynamics, and binding free energy calculations to validate the experimental models. The X-ray structures reveal that covalent adducts with pyridoxal phosphate (PLP) are formed in the active site of the human ODC enzyme, as verified by their preparation and enzymatic testing. Finally, we verified that the cellular activity of endogenous ODC was inhibited, and polyamine levels were reduced. Given that ODC is a clinically validated target, combined with the fact that DFMO is currently the only ODC inhibitor in clinical use for several indications, the further development of more potent ODC inhibitors with superior activity and physical properties is warranted.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Structure of Novel Phosphonium-Based Ionic Liquids with S and O Substitutions from Experiments and a Mixed Quantum-Classical Approach

This article presents experimental characterization information and synchrotron X-ray scattering measurements on a set of novel O- and S-substituted phosphonium-based ionic liquids (ILs) all coupled with the bis(fluorosulfonyl)imide (FSI-) anion. The ILs include the ethoxyethyltriethylphosphonium (P 222(2O2) + ) and triethyl[2-(ethylthio)ethyl]phosphonium (P 222(2S2) + ) cations, and we contrast results on these with those for unsubstituted triethylpentylphosphonium (P 2225 + ). The article also introduces a physics-based protocol that combines classical force field studies on larger simulation boxes with classical and first-principles studies on smaller boxes. The method produces significantly improved S(q) functions in the regime which in prior publications we have associated with inter- and intraionic adjacency correlations. By understanding which shorter-range structural changes improve S(q) in the q-regime of interest, we are also able to pinpoint specific deficiencies in the classical force field model. The approach we take should be quite general and could help study other complex liquids on different length scales.

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

NMR-Guided High-Temperature Electrolyte Design Using a Novel PF 5 Marker

The thermal degradation of electrolytes containing lithium hexafluorophosphate (LiPF 6 ) is a well-studied subject. However, practical application of the knowledge is difficult since the effects of the degradation process on battery performance are not well known. In this work, we propose a novel NMR experimental setup allowing direct observation of the effects of various perturbations on the electrolyte thermal degradation process, which guides the design and synthesis of new additives that improve lithium-ion battery performance at elevated temperatures.

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

THD-C Sheet: A Novel Nonbenzenoid Carbon Allotrope with Tetra-, Hexa-, and Dodeca-Membered Rings

Here, we propose a novel two-dimensional carbon-based structure with tetra-, hexa-, and dodeca-membered rings, which we refer to by the abbreviated name, THD-C. The structure presents a mixture of sp–sp 2 hybridization and can potentially be synthesized by the topological assembly of 4-ethynyldiphenylacetylene molecules. By employing first-principles calculations, the stability and ease of synthesis of the sheet are investigated and compared with various C-allotropes. We predict its metallic behavior and excellent kinetic and dynamic stability. Due to the crystal structure of the sheet, a strong mechanical anisotropy is observed. The effects of functionalization on the electronic properties of the material are also studied, and different semiconducting systems are obtained. The potential of THD-C for energy storage in metal-based batteries, hydrogen storage, and catalysis is also investigated, and we find a superior performance in comparison to graphite and other allotropes. The quantum confinement effect is investigated by constructing nanoribbons and nanotubes of various sizes. For ribbons, we find that tailor-made electronic and magnetic properties can be obtained and explored in potential spintronic devices. Additionally, we observe that nanotubes are conducting irrespective of their chirality and can potentially be used for capture, storage, and separation of industrially relevant small gas molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Novel Low-Temperature Electrolyte Using Isoxazole as the Main Solvent for Lithium-Ion Batteries

A novel electrolyte system with an excellent low temperature performance for lithium-ion batteries (LIBs) has been developed and studied. It was discovered for the first time, in this work, that when isoxazole (IZ) was used as the main solvent, the ionic conductivity of the electrolyte for LIBs is more than doubled in a temperature range between -20 and 20 °C compared to the baseline electrolyte using ethylene carbonate–ethyl methyl carbonate as solvents. To solve the problem of solvent cointercalation into the graphite anode and/or electrolyte decomposition, the lithium difluoro(oxalato)borate (LiDFOB) salt and fluoroethylene carbonate (FEC) additive were used to form a stable solid electrolyte interphase on the surface of the graphite anode. Benefitting from the high ionic conductivity at low temperature, cells using a new electrolyte with 1 M LiDFOB in FEC/IZ (1:10, vol %) solvents demonstrated a very high reversible capacity of 187.5 mAh g -1 at -20 °C, while the baseline electrolyte only delivered a reversible capacity of 23.1 mAh g -1 .

25 ENERGY STORAGE↗
DOE OSTI2021

Enabling High-Temperature and High-Voltage Lithium-Ion Battery Performance through a Novel Cathode Surface-Targeted Additive

We report lithium-ion batteries (LIBs) are being used in locations and applications never imagined when they were first conceived. To enable this broad range of applications, it has become necessary for LIBs to be stable to an ever broader range of conditions, including temperature and energy. Unfortunately, while negative electrodes have received a great deal of focus in electrolyte development, stabilization of positive electrodes remains an elusive target. Here, we report a novel additive that shows the ability to protect positive electrodes against elevated temperatures and voltages. This additive can be used in small quantities, and its targeted behavior allows it to remain functional in complex electrolyte packages. This can prove an effective approach to targeting specific aspects of cell performance.

25 ENERGY STORAGE↗
DOE OSTI2020

A Novel Approach to Modeling Biomass Pyrolysis in a Fluidized Bed Reactor

A novel approach to simulating biomass pyrolysis in a fluidized bed of mostly inert material is presented. The bed is assumed to be externally heated, although simulation of autothermal operation with partial oxidation of the products is a future objective. Combining pyrolysis reaction kinetics developed by the CRECK Modeling Group and a previously published component properties model, material and energy balances are closed by tracking the residence time of biomass particles without regard for their exact spatial distribution. The model is used to simulate a pilot-scale fluidized bed pyrolysis process being developed at Iowa State University, and model predictions are compared with experimental results for red oak and corn stover feedstocks. The results are in general agreement, with the model typically predicting more noncondensable gas and less low-boiling liquid products. The differences are ascribed to the limitations of the kinetics model. This model provides a rigorous energy balance for fluidized bed pyrolysis processes that can be incorporated into commercial flowsheet models with the capacity for future addition of partial oxidation reactions and implementation of improved kinetics models.

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

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗
DOE OSTI2022

SimELIT: A Novel GUI-Based Comprehensive Ion Trajectory Simulation Software for Mass Spectrometry

Ion trajectory simulation in mass spectrometry systems from injection to detection is technically challenging but very important for better understanding the ion dynamics in instrument development. Here, in this work, we present SimELIT (Simulator of Eulerian and Lagrangian Ion Trajectories), a novel ion trajectory simulation platform. SimELIT is built upon a suite of multiphysics solvers compiled into OpenFOAM (an open-source numerical solver library particularly used for computational mechanics), with a simple web-based graphical user interface (GUI) allowing users to define the details of OpenFOAM cases and run simulations. SimELIT is a modular program and can provide extensions of physics (e.g., gas flows, electrodynamic fields) and thus enable ion trajectory simulations from the ion source to detector. The current version (SimELIT) provides two numerical solvers for ion trajectory simulations–(1) a Lagrangian particle tracker in vacuum and (2) a Eulerian ion density solver in background gas in the presence of electric fields. Here, we describe the architecture of SimELIT, including its use of Docker and the React Framework, and demonstrate the computation of ion trajectories of multiple m/z values in a static/linear voltage drop in vacuum (across a 1 m long flight tube). Further, the drift motion of ions under 1 Torr pressure conditions in a static background (N 2 ) gas through a 20 V/cm static electric field is shown. The results produced from SimELIT were compared with SIMION and theoretical estimates. In addition, we report the computation of ion trajectories in electrodynamic fields within a planar FAIMS device operating at atmospheric pressure.

97 MATHEMATICS AND COMPUTING↗