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DOE OSTI2023

A Bis(imidazole)-based cysteine labeling tool for metalloprotein assembly

Precise metal-protein coordination by design remains a considerable challenge. Polydentate, high-metal-affinity protein modifications, both chemical and recombinant, can enable metal localization. However, these constructs are often bulky, conformationally and stereochemically ill-defined, or coordinately saturated. Here, we expand the biomolecular metal-coordination toolbox with the irreversible attachment to cysteine of bis(1-methylimidazol-2-yl)ethene (“BMIE”), which generates a compact imidazole-based metal-coordinating ligand. Conjugate additions of small-molecule thiols (thiocresol and N-Boc-Cys) with BMIE confirm general thiol reactivity. The BMIE adducts are shown to complex the divalent metal ions Cu ++ and Zn ++ in bidentate (N 2 ) and tridentate (N 2 S*) coordination geometries. Cysteine-targeted BMIE modification (>90% yield at pH 8.0) of a model protein, the S203C variant of carboxypeptidase G2 (CPG2), measured with ESI-MS, confirms its utility as a site-selective bioconjugation method. ICP-MS analysis confirms mono-metallation of the BMIE-modified CPG2 protein with Zn ++ , Cu ++ , and Co ++ . EPR characterization of the BMIE-modified CPG2 protein reveals the structural details of the site selective 1:1 BMIE-Cu ++ coordination and symmetric tetragonal geometry under physiological conditions and in the presence of various competing and exchangeable ligands (H 2 O/HO – , tris, and phenanthroline). An X-ray protein crystal structure of BMIE-modified CPG2-S203C demonstrates that the BMIE modification is minimally disruptive to the overall protein structure, including the carboxypeptidase active sites, although Zn ++ metalation could not be conclusively discerned at the resolution obtained. The carboxypeptidase catalytic activity of BMIE-modified CPG2-S203C was also assayed and found to be minimally affected. Finally, these features, combined with ease of attachment, define the new BMIE-based ligation as a versatile metalloprotein design tool, and enable future catalytic and structural applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

AIMSim : An accessible cheminformatics platform for similarity operations on chemicals datasets

The recent advances in deep learning, generative modeling, and statistical learning have ushered in a renewed interest in traditional cheminformatics tools and methods. Quantifying molecular similarity is essential in molecular generative modeling, exploratory molecular synthesis campaigns, and drug-discovery applications to assess how new molecules differ from existing ones. Further, most tools target advanced users and lack general implementations accessible to the larger community. In this work, we introduce Artificial Intelligence Molecular Similarity (AIMSim), an accessible cheminformatics platform for performing similarity operations on collections of molecules called molecular datasets. AIMSim provides a unified platform to perform similarity-based tasks on molecular datasets, such as diversity quantification, outlier and novelty analysis, clustering, dimensionality reduction, and inter-molecular comparisons. AIMSim implements all major binary similarity metrics and molecular fingerprints and is provided as a Python package that includes support for command-line use as well as a Graphical User Interface for code-free utilization with fully interactive plots.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Imaging Valence Electron Rearrangement in a Chemical Reaction Using Hard X-Ray Scattering

We have observed the signatures of valence electron rearrangement in photoexcited ammonia using ultrafast hard x-ray scattering. Time-resolved x-ray scattering is a powerful tool for imaging structural dynamics in molecules because of the strong scattering from the core electrons localized near each nucleus. Such core-electron contributions generally dominate the differential scattering signal, masking any signatures of rearrangement in the chemically important valence electrons. Ammonia represents an exception to the typically high core-to-valence electron ratio. Here, we measured 9.8 keV x-ray scattering from gas-phase deuterated ammonia following photoexcitation via a 200 nm pump pulse to the 3s Rydberg state. We observed changes in the recorded scattering patterns due to the initial photoexcitation and subsequent deuterium dissociation. Ab initio calculations confirm that the observed signal is sensitive to the rearrangement of the single photoexcited valence electron as well as the interplay between adiabatic and nonadiabatic dissociation channels. The use of ultrafast hard x-ray scattering to image the structural rearrangement of single valence electrons constitutes an important advance in tracking valence electronic structure in photoexcited atoms and molecules.

Gabalski, Ian [SLAC National Accelerator Laborator↗

DOE OSTI2022

Design and Optimization of Structured Multi-Functional Trapping Catalysts for Conversion of Hydrocarbons and NOx from Diesel and Advanced Combustion Engines

Oxides of nitrogen in the form of nitric oxide (NO) and nitrogen dioxide (NO 2 ) commonly referred to as NOx, is one of the two chemical precursors that lead to ground-level ozone, a ubiquitous air pollutant in urban areas. A major source of NOx is generated by equipment and vehicles powered by diesel engines, which have a combustion exhaust that contains NOx in the presence of excess O 2 . Vehicular emission control catalysts are ineffective in eliminating CO, hydrocarbons, and NOx during engine cold-start when exhaust temperatures are below 200°C. The objective of the project was to develop and demonstrate a multi-functional, catalyzed trap that enables vehicles with advanced combustion strategies to meet Tier 3 emissions standards while achieving the 150 °C challenge for sustained co-oxidation of HCs and CO and ≥90% NO trapping and release during warmup. Specifically, the multi-functional Lean HC+NOx (LHCNT) was developed for application in the exhaust aftertreatment of conventional diesel engines and engines having low temperature combustion (LTC) regimes. Activities included the design and synthesis of adsorbents and catalysts, screening and evaluation. Passive NOx absorbers (PNA), hydrocarbon (HC) traps, and oxidation catalysts (OC) were evaluated for use in series or as integrated devices. Predictive tools were developed utilizing the characterization and analysis of these materials, and an emission system was designed and optimized utilizing the catalyst systems. Microkinetic models were developed for the PNA for the simple NO-only feed and complex feed containing CO, H 2 , and model hydrocarbons (ethylene and dodecane). A first-principles, mechanistic-based model of the PNA was developed which utilized molecular-scale estimates (density functional theory) of energy barriers, mechanistic-based kinetics and realistic treatments of the flow and transport processes. Two new oxidation catalysts were developed (PdCu alloy, mixed copper-ceria-cobalt oxide), both of which significantly lessened the detrimental inhibition by CO on hydrocarbon and NO oxidation. A method for lessening the detrimental impact of CO on PNA activity was developed that involves use of an oxidation catalyst upstream of the PNA. The SwRI Ectolab TM burner system was applied to evaluate the baseline PNA material and confirmed performance comparable to the benchflow PNA studies using simulated exhaust. Spatially-resolved mass spectrometry (SpaciMS) was used to measure the transient spatial profiles of reacting species spanning the length of a three-function LHCNT containing PNA, HCT, and OC. The findings from this study provide diesel vehicle and catalyst companies valuable information to develop more cost effective emission control catalysts which helps to expand the use of more fuel efficient diesel power. The fundamental modeling and experimental tools and findings from this project can be applied to catalyst technologies used in the energy and chemical industries. The project led to 14 publications in the peer-reviewed literature with 2 additional currently under review. Finally, the project also led to training of several doctoral students who were placed in research jobs in industry and academia. Specifically, Mugdha Ambast (UH) has joined Cummins, Kevin Gu (UVa) has joined GM, and Abhay Gupta (UH) is to join Caterpillar.

02 PETROLEUM↗

DOE OSTI2022

Design and Optimization of Structured Multi-Functional Trapping Catalysts for Conversion of Hydrocarbons and NOx from Diesel and Advanced Combustion Engines

Oxides of nitrogen in the form of nitric oxide (NO) and nitrogen dioxide (NO 2 ) commonly referred to as NOx, is one of the two chemical precursors that lead to ground-level ozone, a ubiquitous air pollutant in urban areas. A major source of NOx is generated by equipment and vehicles powered by diesel engines, which have a combustion exhaust that contains NOx in the presence of excess O 2 . Vehicular emission control catalysts are ineffective in eliminating CO, hydrocarbons, and NO x during engine cold-start when exhaust temperatures are below 200°C. The objective of the project was to develop and demonstrate a multi-functional, catalyzed trap that enables vehicles with advanced combustion strategies to meet Tier 3 emissions standards while achieving the 150 °C challenge for sustained co-oxidation of HCs and CO and ≥90% NO trapping and release during warmup. Specifically, the multi-functional Lean HC+NOx (LHCNT) was developed for application in the exhaust aftertreatment of conventional diesel engines and engines having low temperature combustion (LTC) regimes. Activities included the design and synthesis of adsorbents and catalysts, screening and evaluation. Passive NOx absorbers (PNA), hydrocarbon (HC) traps, and oxidation catalysts (OC) were evaluated for use in series or as integrated devices. Predictive tools were developed utilizing the characterization and analysis of these materials, and an emission system was designed and optimized utilizing the catalyst systems. Microkinetic models were developed for the PNA for the simple NO-only feed and complex feed containing CO, H 2 , and model hydrocarbons (ethylene and dodecane). A first-principles, mechanistic-based model of the PNA was developed which utilized molecular-scale estimates (density functional theory) of energy barriers, mechanistic-based kinetics and realistic treatments of the flow and transport processes. Two new oxidation catalysts were developed (PdCu alloy, mixed copper-ceria-cobalt oxide), both of which significantly lessened the detrimental inhibition by CO on hydrocarbon and NO oxidation. A method for lessening the detrimental impact of CO on PNA activity was developed that involves use of an oxidation catalyst upstream of the PNA. The SwRI Ectolab TM burner system was applied to evaluate the baseline PNA material and confirmed performance comparable to the benchflow PNA studies using simulated exhaust. Spatially-resolved mass spectrometry (SpaciMS) was used to measure the transient spatial profiles of reacting species spanning the length of a three-function LHCNT containing PNA, HCT, and OC. The findings from this study provide diesel vehicle and catalyst companies valuable information to develop more cost effective emission control catalysts which helps to expand the use of more fuel efficient diesel power. The fundamental modeling and experimental tools and findings from this project can be applied to catalyst technologies used in the energy and chemical industries. The project led to 14 publications in the peer-reviewed literature with 2 additional currently under review. Finally, the project also led to training of several doctoral students who were placed in research jobs in industry and academia. Specifically, Mugdha Ambast (UH) has joined Cummins, Kevin Gu (UVa) has joined GM, and Abhay Gupta (UH) is to join Caterpillar.

42 ENGINEERING↗

DOE OSTI2020

Atomic Force Microscopy-Based Force Spectroscopy and Multiparametric Imaging of Biomolecular and Cellular Systems

During the last three decades, a series of key technological improvements turned atomic force microscopy (AFM) into a nanoscopic laboratory to directly observe and chemically characterize molecular and cell biological systems under physiological conditions. In this work, we review key technological improvements that have established AFM as an analytical tool to observe and quantify native biological systems from the micro- to the nanoscale. Native biological systems include living tissues, cells, and cellular components such as single or complexed proteins, nucleic acids, lipids, or sugars. We showcase the procedures to customize nanoscopic chemical laboratories by functionalizing AFM tips and outline the advantages and limitations in applying different AFM modes to chemically image, sense, and manipulate biosystems at (sub)nanometer spatial and millisecond temporal resolution. We further discuss theoretical approaches to extract the kinetic and thermodynamic parameters of specific biomolecular interactions detected by AFM for single bonds and extend the discussion to multiple bonds. Finally, we highlight the potential of combining AFM with optical microscopy and spectroscopy to address the full complexity of biological systems and to tackle fundamental challenges in life sciences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Covalent Linkage and Macrocylization Preserve and Enhance Synergistic Interactions in Catalytic Amyloids

The self-assembly of short peptides into catalytic amyloid-like nanomaterials has proven to be a powerful tool in both understanding the evolution of early proteins and identifying new catalysts for practically useful chemical reactions. Here we demonstrate that both parallel and antiparallel arrangements of beta-sheets can accommodate metal ions in catalytically productive coordination environments. Moreover, synergistic relationships, identified in catalytic amyloid mixtures, can be captured in macrocyclic and sheet-loop-sheet species, that offer faster rates of assembly and provide more complex asymmetric arrangements of functional groups, thus paving the way for future designs of amyloid-like catalytic proteins. Finally, our findings show how initial catalytic activity in amyloid assemblies can be propagated and improved in more-complex molecules, providing another link in a complex evolutionary chain between short, potentially abiotically produced peptides and modern-day enzymes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Role of Tensile Stress in DNA Nanoresonators for Epigenetic Studies

The evaluation of epigenetic features such as DNA methylation is becoming increasingly important in many biochemical processes like gene expression and transcription as well as in several diseases like schizophrenia or diabetes. Here, in this work, we report that self-assembled nanomechanical resonators entirely composed of DNA molecules can be used to explore gross changes in DNA methylation levels (0–25–50%), while careful control of tensile stress is needed to reduce the variability of resonance frequency for rigorous quantification. The effect of the tensile stress retained by the suspended DNA nanoresonators on the application of the technique is extensively explored using a combination of laser Doppler vibrometry and atomic force spectroscopy. DNA nanoresonators are real-time, label-free sensors and could avoid chemical functionalization and sample amplification. Therefore, they may represent in the future a key complementary routine tool for global DNA methylation analysis needed to evaluate the consequences of environmental stresses on the human genome.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Advances in Multiscale Modeling of Lignocellulosic Biomass

Applications and associated processing technologies of lignocellulosic biomass are becoming more important as we endeavor to meet societal demand for fuels, chemicals, and materials from renewable resources. Meanwhile, the rapidly expanding availability and capabilities of high-performance computing present an unprecedented opportunity to accelerate development of technologies surrounding lignocellulose utilization. In order to realize this potential, suitable modeling frameworks must be constructed that effectively capture the multiscale complexity and tremendous variety exhibited by lignocellulosic materials. In our assessment of previous endeavors towards this goal, several important shortcomings have been identified: (1) the lack of multiscale integration strategies that capture emergent properties and behaviors spanning different length scales, and (2) the inability of many modeling approaches to effectively capture the variability and diversity of lignocellulose that arise from both natural and process-induced sources. In this perspective, we survey previous modeling approaches for lignocellulose and simulations processes involving its chemical and mechanical transformation, and suggest opportunities for future development to enhance the utility of computational tools to address barriers to widespread adoption of a renewable bioeconomy.

09 BIOMASS FUELS↗

DOE OSTI2022

Using an Explainable Machine Learning Approach to Characterize Earth System Model Errors: Application of SHAP Analysis to Modeling Lightning Flash Occurrence

Abstract Computational models of the Earth System are critical tools for modern scientific inquiry. Efforts toward evaluating and improving errors in representations of physical and chemical processes in these large computational systems are commonly stymied by highly nonlinear and complex error behavior. Recent work has shown that these errors can be effectively predicted using modern Artificial Intelligence (A.I.) techniques. In this work, we go beyond these previous studies to apply an explainable A.I. technique to not only predict model errors but also move toward understanding the underlying reasons for successful error prediction. We use XGBoost classification trees and SHapley Additive exPlanations analysis to explore the errors in the prediction of lightning occurrence in the NASA Goddard Earth Observing System model, a widely used Earth System Model. This explainable error prediction system can effectively predict the model error and indicates that the errors are strongly related to convective processes and the characteristics of the land surface.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Soil, Foodstuffs, and Biota Program [Slides]

We use several environmental monitoring tools to assess ecosystem health and in part, risk to human health. Generally, the concentrations of chemicals we observe are below background and screening levels. All of our monitoring data are available in Intellus, and our analyses and results are reported in the Annual Site Environmental Report. Our program is only one of several monitoring programs at LANL, others include air, surface water, ground water, canyon sediments. We strive to improve the program by incorporating new monitoring techniques, monitoring new locations, monitoring new chemicals of interest, and by using robust statistical analyses.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Process in manufacturing high efficiency AlGaAs/GaAs solar cells by MO-CVD

Manufacturing technology for mass producing high efficiency GaAs solar cells is discussed. A progress using a high throughput MO-CVD reactor to produce high efficiency GaAs solar cells is discussed. Thickness and doping concentration uniformity of metal oxide chemical vapor deposition (MO-CVD) GaAs and AlGaAs layer growth are discussed. In addition, new tooling designs are given which increase the throughput of solar cell processing. To date, 2cm x 2cm AlGaAs/GaAs solar cells with efficiency up to 16.5% were produced. In order to meet throughput goals for mass producing GaAs solar cells, a large MO-CVD system (Cambridge Instrument Model MR-200) with a susceptor which was initially capable of processing 20 wafers (up to 75 mm diameter) during a single growth run was installed. In the MR-200, the sequencing of the gases and the heating power are controlled by a microprocessor-based programmable control console. Hence, operator errors can be reduced, leading to a more reproducible production sequence.

Yeh, Y. C. M.↗

NASA NTRS1992

Chemical vapor deposition modeling for high temperature materials

The formalism for the accurate modeling of chemical vapor deposition (CVD) processes has matured based on the well established principles of transport phenomena and chemical kinetics in the gas phase and on surfaces. The utility and limitations of such models are discussed in practical applications for high temperature structural materials. Attention is drawn to the complexities and uncertainties in chemical kinetics. Traditional approaches based on only equilibrium thermochemistry and/or transport phenomena are defended as useful tools, within their validity, for engineering purposes. The role of modeling is discussed within the context of establishing the link between CVD process parameters and material microstructures/properties. It is argued that CVD modeling is an essential part of designing CVD equipment and controlling/optimizing CVD processes for the production and/or coating of high performance structural materials.

Goekoglu, Sueleyman↗

NASA NTRS1992

Chemical vapor deposition modeling for high temperature materials

Gokoglu, Suleyman A.↗

NASA NTRS2000

Amino Acid Chemistry as a Link Between Small Solar System Bodies and Carbonaceous Chondrites

Establishing chemical links between meteorites and small solar system bodies, such as comets and asteroids, provides a tool for investigating the processes that occurred during the formation of the solar system. Carbonaceous meteorites are of particular interest, since they may have seeded the early Earth with a variety of prebiotic organic compounds including amino acids, purines and pyrimidines, which are thought to be necessary for the origin of life. Here we report the results of high-performance liquid chromatography (HPLC) based amino acid analyses of the acid-hydrolyzed hot water extracts from pristine interior pieces of the CI carbonaceous chondrites Orgueil and Ivuna and the CM meteorites Murchison and Murray. We found that the CI meteorites Orgueil and Ivuna contained high abundances of beta-alanine and glycine, while only traces of other amino acids like alanine, alpha-amino-n-butryic acid (ABA) and alpha-aminoisobutyric acid (AIB) were detected in these meteorites. Carbon isotopic measurements of beta-alanine and glycine in Orgueil by gas chromatography combustion-isotope ratio mass spectrometry clearly indicate an extraterrestrial origin of these amino acids. The amino acid composition of Orgueil and Ivuna was strikingly different from the CM chondrites Murchison and Murray. The most notable difference was the high relative abundance of B-alanine in Orgueil and Ivuna compared to Murchison and Murray. Furthermore, AIB, which is one of the most abundant amino acids found in Murchison and Murray, was present in only trace amounts in Orgueil and Ivuna. Our amino acid data strongly suggest that the CI meteorites Orgueil and Ivuna came from a different type of parent body than the CM meteorites Murchison and Murray, possibly from an extinct comet. It is generally thought that carbonaceous meteorites are fragments of larger asteroidal bodies delivered via near Earth objects (NEO). Orbital and dynamic studies suggest that both fragments of main belt asteroids and comets replenish the NEO population, therefore extinct comets may contribute up to half of all NEO's. A comparison of an amino acid analysis of a returned NEO sample to CI and CM carbonaceous chondrites would help establish a link between small solar system bodies and meteorites. Based on our amino acid measurements of CI and CM chondrites, amino acid chemistry can be included as an additional set of criteria to constrain the nature of meteorite parent bodies.

Glavin, Daniel P.↗

NASA NTRS2011

The New Meteor Radar at Penn State: Design and First Observations

In an effort to provide new and improved meteor radar sensing capabilities, Penn State has been developing advanced instruments and technologies for future meteor radars, with primary objectives of making such instruments more capable and more cost effective in order to study the basic properties of the global meteor flux, such as average mass, velocity, and chemical composition. Using low-cost field programmable gate arrays (FPGAs), combined with open source software tools, we describe a design methodology enabling one to develop state-of-the art radar instrumentation, by developing a generalized instrumentation core that can be customized using specialized output stage hardware. Furthermore, using object-oriented programming (OOP) techniques and open-source tools, we illustrate a technique to provide a cost-effective, generalized software framework to uniquely define an instrument s functionality through a customizable interface, implemented by the designer. The new instrument is intended to provide instantaneous profiles of atmospheric parameters and climatology on a daily basis throughout the year. An overview of the instrument design concepts and some of the emerging technologies developed for this meteor radar are presented.

Urbina, J.↗

NASA NTRS2014

Methods for Prediction of High-Speed Reacting Flows in Aerospace Propulsion

Research to develop high-speed airbreathing aerospace propulsion systems was underway in the late 1950s. A major part of the effort involved the supersonic combustion ramjet, or scramjet, engine. Work had also begun to develop computational techniques for solving the equations governing the flow through a scramjet engine. However, scramjet technology and the computational methods to assist in its evolution would remain apart for another decade. The principal barrier was that the computational methods needed for engine evolution lacked the computer technology required for solving the discrete equations resulting from the numerical methods. Even today, computer resources remain a major pacing item in overcoming this barrier. Significant advances have been made over the past 35 years, however, in modeling the supersonic chemically reacting flow in a scramjet combustor. To see how scramjet development and the required computational tools finally merged, we briefly trace the evolution of the technology in both areas.

Drummond, J. Philip↗

NASA NTRS2017

Developing Model Benchtop Systems for Microbial Experimental Evolution

Understanding how microbes impact an ecosystem has improved through advances of molecular and genetic tools, but creating complex systems that emulate natural biology goes beyond current technology. In fact, many chemical, biological, and metabolic pathways of even model organisms are still poorly characterized. Even then, standard laboratory techniques for testing microbial impact on environmental change can have many drawbacks; they are time-consuming, labor intensive, and are at risk of contamination. By having an automated process, many of these problems can be reduced or even eliminated. We are developing a benchtop system that can run for long periods of time without the need for human intervention, involve multiple environmental stressors at once, perform real-time adjustments of stressor exposure based on current state of the population, and minimize contamination risks. Our prototype device allows operators to generate an analogue of real world micro-scale ecosystems that can be used to model the effects of disruptive environmental change on microbial ecosystems. It comprises of electronics, mechatronics, and fluidics based systems to control, measure, and evaluate the before and after state of microbial cultures from exposure to environmental stressors. Currently, it uses four parallel growth chambers to perform tests on liquid cultures. To measure the population state, optical sensors (LED/photodiode) are used. Its primary selection pressure is UV-C radiation, a well-studied stressor known for its cell- and DNA-damaging effects and as a mutagen. Future work will involve improving the current growth chambers, as well as implementing additional sensors and environmental stressors into the system. Full integration of multiple culture testing will allow inter-culture comparisons. Besides the temperature and OD sensors, other types of sensors can be integrated such as conductivity, biomass, pH, and dissolved gasses such as CO and O. Additional environmental stressor systems like temperature (extreme heat or cold), metal toxicity, and other forms of radiation will increase the scale and testing range.

Developing↗