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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 OSTI2019

Two-dimensional nuclear magnetic resonance spectroscopy with a microfluidic diamond quantum sensor

Quantum sensors based on nitrogen-vacancy centers in diamond have emerged as a promising detection modality for nuclear magnetic resonance (NMR) spectroscopy owing to their micrometer-scale detection volume and noninductive-based detection. A remaining challenge is to realize sufficiently high spectral resolution and concentration sensitivity for multidimensional NMR analysis of picoliter sample volumes. Here, we address this challenge by spatially separating the polarization and detection phases of the experiment in a microfluidic platform. We realize a spectral resolution of 0.65 ± 0.05 Hz, an order-of-magnitude improvement over previous diamond NMR studies. We use the platform to perform two-dimensional correlation spectroscopy of liquid analytes within an effective ~40-picoliter detection volume. The use of diamond quantum sensors as in-line microfluidic NMR detectors is a major step toward applications in mass-limited chemical analysis and single-cell biology.

Science & Technology - Other Topics↗
DOE OSTI2016

Ultrastructural and Single-Cell-Level Characterization Reveals Metabolic Versatility in a Microbial Eukaryote Community from an Ice-Covered Antarctic Lake

The McMurdo Dry Valleys (MCM) of southern Victoria Land, Antarctica, harbor numerous ice-covered bodies of water that provide year-round liquid water oases for isolated food webs dominated by the microbial loop. Single-cell microbial eukaryotes (protists) occupy major trophic positions within this truncated food web, ranging from primary producers (e.g., chlorophytes, haptophytes, and cryptophytes) to tertiary predators (e.g., ciliates, dinoflagellates, and choanoflagellates). To advance the understanding of MCM protist ecology and the roles of MCM protists in nutrient and energy cycling, we investigated potential metabolic strategies and microbial interactions of key MCM protists isolated from a well-described lake (Lake Bonney). Fluorescence-activated cell sorting (FACS) of enrichment cultures, combined with single amplified genome/amplicon sequencing and fluorescence microscopy, revealed that MCM protists possess diverse potential metabolic capabilities and interactions. Two metabolically distinct bacterial clades ( Flavobacteria and Methylobacteriaceae ) were independently associated with two key MCM lake microalgae ( Isochrysis and Chlamydomonas , respectively). We also report on the discovery of two heterotrophic nanoflagellates belonging to the Stramenopila supergroup, one of which lives as a parasite of Chlamydomonas , a dominate primary producer in the shallow, nutrient-poor layers of the lake. Single-cell eukaryotes called protists play critical roles in the cycling of organic matter in aquatic environments. In the ice-covered lakes of Antarctica, protists play key roles in the aquatic food web, providing the majority of organic carbon to the rest of the food web (photosynthetic protists) and acting as the major consumers at the top of the food web (predatory protists). In this study, we utilized a combination of techniques (microscopy, cell sorting, and genomic analysis) to describe the trophic abilities of Antarctic lake protists and their potential interactions with other microbes. Ultimately, our work reveals that Antarctic lake protists rely on metabolic versatility for their energy and nutrient requirements in this unique and isolated environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

In Situ High-Temperature TEM Observation of Inconel Corrosion by Molten Chloride Salts with N 2 , O 2 , or H 2 O

Here, in situ transmission electron microscopy (TEM) diffraction and imaging techniques are used to monitor and quantify corrosion of Inconel-625 by pure molten chloride salts (MgCl 2 – NaCl – KCl) at 500 °C–800 °C in 1.0 atm inert N 2 or pure O2, or by salts which are controllably hydrated in a high vacuum chamber. The isothermal corrosion rate R in inert N 2 increases from 203 ± 30 μ m year –1 at 700 °C to 463 ± 30 μ m year –1 at 800 °C. An oxygen ambient causes a six-fold increase to R = 1261 ± 170 μ m year –1 at 700 °C. Salt hydration dramatically accelerates corrosion to R > 3 × 10 5 μ m year –1 at 700 °C while it leads to a more moderate R = 95 ± 20 and 486 ± 30 μ m year –1 at 500 °C and 600 °C, respectively. These isothermal corrosion rates indicate that the molten chloride corrosion is significantly accelerated by salt hydration at temperatures above 600 °C, where corrosion is aggravated by increased generation and solubility of corrosive HCl gases. Hence, to reduce rate of corrosion it is important to both avoid incorporation of H 2 O into the system at each stage and ensure proper flushing of the system before increasing the temperature beyond 600 °C. Compositional analysis of the corroded cells indicate that corrosion in O 2 ambient is dominated by oxidation of metals by O 2 gas dissolved in the chloride melt, but corrosion in H 2 O ambients is caused by chlorination of metals by dissolved HCl gas and MgOH + ions. So, to reduce rate of corrosion, steps should be taken to tailor chloride melt compositions that has low solubility for HCl and O 2 . All of our corroded samples exhibit passive-protective oxide layers of Cr, Mg, and Ni. In addition, distinct volatile compounds of Ni, Mo and Cr involving NiCl 2 , (Na,K) 2 MoO 4 and CrO 2 (OH) 2 are detected in N 2 , H 2 O, and O 2 ambients, respectively. We believe that corrosion acceleration can be minimized by minimizing formation of volatile by-products or promoting reactions that could convert these volatile compounds to solid phases, as these volatile compounds led to destruction of protective oxide layers.

14 SOLAR ENERGY↗
DOE OSTI2023

Evaluation of Lithium Metal Anode Volumetric Expansion through Laser Plasma Focused Ion Beam Cross-Sectional Imaging

Lithium metal is an ideal anode for high energy density batteries, however the implementation of lithium metal anodes remains challenging. Beyond the development of highly efficient electrolytes, degradation processes restrict cycle life and reduce practical energy density. Herein lithium volumetric expansion and degradation pathways are studied in half cells through coupling electrochemical analysis with cross-sectional imaging of the intact electrode stack using a cryogenic laser plasma focused ion beam and scanning electron microscope. Here, we find that the volumetric capacity is compromised as early as the first cycle, at best reaching values only half the theoretical capacity (1033 vs 2045 mAh cm -3 ). By the 101st electrodeposition, the practical volumetric capacity decreases to values ranging from 143 to 343 mAh cm -3 .

25 ENERGY STORAGE↗
DOE OSTI2026

ML-based Micro-CT SOFC Microstructure Models (from Kent 2026 Microstructural Augmentation paper)

Overview -------------------------- This repository contains datasets from the manuscript **"Enhanced Generalizability to Deep-Learning Quantification of 3D Microstructural Characteristics through Microstructurally Aware Augmentation of Scarce Data"** (*William F. Kent, Rochan Bajpai, Rachel C. Kurchin, William K. Epting, Harry W. Abernathy, Paul A. Salvador. Submitted 2026*). The methods are also described in the dissertation **Data Intensive Analysis of Solid Oxide Cell Microstructures** (*Doctoral dissertation, Carnegie Mellon University, 2025*). The datasets here are trained convolutional neural network (CNN) models for predicting key microstructural properties of solid oxide cell (SOC) electrodes from low-res, 2-channel 3D images, as well as some helpful code. The parameters for input images are provided in the paper. Sample data is provided in the file `Combined_anode_aug_dual_1k_examples` - that particular data was used to train `anode_all_aug.pth` and will work most accurately with that model. Please familiarize yourself with all caveats on accuracy and applicability, as detailed in the associated paper. Usage -------------------------- The basic usage is as follows, assuming `model_fn` is the path to the .pth file, and `X` is 2-channel input image(s) of the proper dimensions (either one image of shape `[2,12,24,24]`, or a batch of N input images of shape `[N,2,12,24,24]`): from CNN_inferencer import load_model_for_inference model = load_model_for_inference(model_fn) y_predicted = model(X) The model object automatically handles input scaling and output de-scaling based on the way the models were trained - in other words, pass in a 2-channel micro-CT image, and it will output microstructural property values in real units. ## Other model object attributes Note that model has useful attributes other than its forward pass model(X). * `model.output_descaler` - returns the output descaler object. Model does the de-scaling when generating inferences, but you may want to re-use this de-scaler on other values to e.g. compare predictions to ground truth from already-scaled training data. * `model.prop_names` - Gives the property names of the predicted y values, in order. Only exists if there's an output scaler as part of the model object, which there will be in the models provided here. ## Usage with sample data Here is a short script to use with the included sample data. from CNN_inferencer import display_predictions, load_model_for_inference, calculate_mape, parity_plot import h5py import numpy as np model_fn = 'anode_all_aug.pth' data_fn = 'Combined_anode_aug_dual_1k_examples.h5' N_samples = 200 figure_outdir = '.' model = load_model_for_inference(model_fn) with h5py.File(data_fn,'r') as f: XX = f['X'] #These are the 2-channel 3D images yy = f['y'] #These are the ground-truth microstructural properties, but they have been scaled for training - need to de-scale below N = XX.shape[0] #How many images total in the input data file #Run inferences on N_samples random samples from XX. #Run in a batch, much more efficient than one at a time. ii = np.random.choice(N,N_samples,replace=False) ii.sort() y_pred = model(XX[ii]) #Get the original/true (but normalized/scaled) values from the training dataset... #Because they were normalized, they are not in real units yet. So let's also de-scale them using model.output_scaler. y_true = model.output_scaler.transform(yy[ii]) #Let's display actual values for just 5 random ones for i in np.random.choice(N_samples,5,replace=False): display_predictions(y_true[i], y_pred[i], model.prop_names) #Make parity plots for each property (ground truth vs predicted values) #Also label each plot with the mean abs. percent error (MAPE) of the predicted values for i,key in enumerate(model.prop_names): mape = calculate_mape(y_true[:,i], y_pred[:,i]) parity_plot(y_true[:,i], y_pred[:,i], figure_outdir, key, extra_title=f' ({mape:.2f}% MAPE)')

3D microstructure↗
DOE OSTI2017

In-situ X-Ray Analysis of Rapid Thermal Processing for Thin-Film Solar Cells: Closing the Gap between Production and Laboratory Efficiency

For materials synthesis, it is well known that the material final state may not reach equilibrium and depends on the synthetic process. In particular, processes that quickly remove the available energy from the material may leave it in a metastable state and the metastability may actually impart desirable functional properties. By its very nature, Rapid thermal processing (RTP) is ideally suited to produce such metastable materials. However, metastability and the dynamics of reaching a metastable state are poorly understood, since this is best accomplished through in situ monitoring. In this regard, RTP is particularly challenging as the processing time are very short (seconds to minutes). As a result, there is only poor understanding, and hence use, of RTP in industry. This is potentially a cost-increasing limitation, because RTP can decrease cost by decreasing processing time, and as such, increase throughput and decrease the total thermal budget of processing - a significant cost. RTP is already being used for key processing steps in PV technologies. With silicon wafer PV, it is used for establishing electrical contact between the Ag metal grid and the silicon (known as firing). In this process, a silicon wafer with deposited metal/frit in a grid pattern is heated rapidly to temperatures between 750 and 800 ºC. The processing time when the temperature is held above 600ºC is short (<5 seconds). This process has historically been optimized empirically and it is unclear how the thermal processing affects formation of the final contact between the metal and the silicon. In the case of thin-film PV, RTP has been demonstrated in the process of making absorber layers, i.e. CIGS and CZTS. Use of RTP can reduce the processing time from 10s of minutes to seconds, reducing the thermal budget and increasing the throughput significantly. The conversion from precursor material to final PV material is not well understood, and most of the process optimization is done empirically. Again, the proposed in situ monitoring will provide insight into the conversion process. We have developed a unique instrument for in situ monitoring of the reaction process during RTP. The most fundamental property to monitor is the atomic arrangement (for solids, crystalline structure) and thus we have focused on this property. The chamber was designed to collect X-ray diffraction (XRD) for crystal phase determination, although it has lent insight in the formation of liquids. We designed and constructed both inert (air) and reactive (S/Se) versions of this chamber. We have applied the RTP-XRD methodology to: silicon solar cell electrical contact formation; the reaction sequence for forming CIGS PV thin films from copper selenide and indium gallium selenide precursors; the phase sequence for forming HC(NH2)2PbI3 (FAPbI3) and CH3NH3PbI3 (MAPbI3) hybrid-perovskite PV thin films. The RTP instrument enables real-time collection of X-ray diffraction data with intervals as short as 100 ms, and while heating at ramp rates as high 100 ºCs-1 up to 1200 ºC. The system is portable and can be installed on a synchrotron beamline. The RTP reactor consists of a metallic body (front cap assembly, central block and end cap assembly) that houses a quartz reaction chamber. The sample is secured inside the reaction chamber on a sample holder connected to the front-cap assembly. Modifications of the chamber were made for safely handling sulfur and selenium vapor environments. A Se/S source holder was added to generate a Se/S over pressure in the chamber on heating and the entrance window is made wider in order to accommodate the detachable additional holder. Se/S are toxic in nature and therefore a proper Se/S trapping is used before releasing the gases to exhaust. Screen-printing provides an economically attractive means for making Ag electrical contacts to Si solar cells, but the use of Ag substantiates a significant manufacturing cost, and the glass frit used in the paste to enable contact formation contains Pb. To achieve optimal electrical performance and to develop pastes with alternative, abundant, and non-toxic materials requires understanding the contact formation process during firing. We use the RTP-XRD chamber during firing of Ag-Si contacts to reveal the reaction sequence for contact formation. The findings show that between 500 ºC and 650 ºC PbO in the frit etches the SiNx antireflective-coating on the solar cell, exposing the Si surface. Then, above 650 ºC, Ag+ dissolves into the molten glass frit – key for enabling deposition of metallic Ag on the emitter surface and precipitation of Ag nanocrystals within the glass. This clarifies contact formation mechanisms and can be used to suggest approaches for development of inexpensive, nontoxic solar cell contacting pastes. We used the RTP/XRD chamber to study the formation of CuInGaS/Se (CIGS) PV films by in-situ selenization of pre-deposited metal stacks and annealing of pre-deposited Cu-In-Ga-Se precursors. During the metal stack selenization, we observed that Se first reacts with the metals and forms selenides. We observed formation of intermetallics such as Cu2In and binary selenides during heating. On further annealing in a Se atmosphere, CuInSe2 and CuGaSe2 forms which on heating up to 550 °C reacts further to form the CIGS phase. On prolonged exposure to 550 °C for more than 5 mins or higher temperature, we see separation into Ga-rich and Ga-depleted CIGS phases. On introducing a holding step at 400 °C for 10 min during the annealing ramp, the CIGS phase (forms between 500-550 °C), appears to be less prone to decomposition into high-Ga and low-Ga phases during holding at peak temperature. Lead halide perovskites have emerged as successful optoelectronic materials with high photovoltaic power conversion efficiencies and low material cost. However, substantial challenges remain in the scalability, stability and fundamental understanding of the materials. We demonstrated the application of radiative thermal annealing, an easily scalable processing method, for synthesizing formamidinium lead iodide (FAPbI3) perovskite solar absorbers. Devices fabricated from films formed via radiative thermal annealing have equivalent efficiencies to those annealed using a conventional hotplate. By coupling results from in situ x-ray diffraction using a radiative thermal annealing system with device performances, we mapped the processing phase space of FAPbI3 and corresponding device efficiencies. Our map of processing-structure-performance space suggests the commonly used FAPbI3 annealing time, 10 min at 170 °C, can be significantly reduced to 40 s at 170 °C without affecting the photovoltaic performance. Applying the Johnson-Mehl-Avrami model to the decomposition into PbI2, the activation energy was determined. We also presented a well-controlled, manufacturing relevant annealing method, radiative thermal annealing, for the methylammonium lead triiodide films formed by solvent engineering process, with dimethylformamide (DMF) and dimethyl sulfoxide as solvent and diethyl ether as the antisolvent. Radiative thermal annealing can produce high quality perovskite films, evidenced by high efficiency solar cell devices, in a shorter time than the widely-used hotplate annealing. Using in-situ x-ray diffraction during the radiative annealing, we show that the role of the antisolvent is not to form an intermediate compound (a methylammonium iodide, lead iodide, and dimethyl sulfoxide compound) by washing of the main solvent (DMF) but to achieve a pin-hole free, uniform film of methylammonium lead iodide. We find that having the intermediate compound does not guarantee a high quality (pin-hole free) perovskite film. Our study was extended to reveal the effect of annealing environment, annealing temperature profile, and deposition substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Fuel Cell Electric Vehicle Driving and Fueling Behavior

The objectives of this project are to validate hydrogen fuel cell electric vehicles in real-world settings and to identify the current status and evolution of the technology. The analysis objectively assesses progress toward targets and market needs defined by the U.S. Department of Energy and stakeholders, provides feedback to hydrogen research and development, and publishes results for key stakeholder use and investment decisions. Fiscal year 2018 objectives focused on analysis and reporting of fuel cell electric vehicle driving range, fuel economy, drive and fill behaviors, durability, fill performance, and fuel cell performance. This report specifically addresses the topics of driving range, fuel economy, drive and fill behaviors, and fill performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Hydrogen Fuel Cell Electric Vehicle Tunnel Safety Study

Several jurisdictions with critical tunnel infrastructure have expressed the need to understand the risks and implications of traffic incidents in tunnels involving hydrogen fuel cell vehicles. A risk analysis was performed to estimate what scenarios were most likely to occur in the event of a crash. The results show that the most likely consequence is no additional hazard from the hydrogen, although some factors need additional data and study to validate. This includes minor crashes and scenarios with no release or ignition. When the hydrogen does ignite, it is most likely a jet flame from the pressure relief device release due to a hydrocarbon fire. This scenario was considered in detailed modeling of specific tunnel configurations, as well as discussion of consequence concerns from the Massachusetts Department of Transportation. Localized concrete spalling may result where the jet flame impinges the ceiling, but this is not expected to occur with ventilation. Structural epoxy remains well below the degradation temperature. The total stress on the steel structure was significantly lower than the yield stress of stainless steel at the maximum steel temperature even when the ventilation was not operational. As a result, the steel structure will not be compromised. It is important to note that the study took a conservative approach in several factors, so observed temperatures should be lower than predicted by the models.

08 HYDROGEN↗
DOE OSTI2021

Bifacial update: field results

This conference presentation provides an overview of interim test results and findings from PVEL's DOE-funded bifacial study, including monthly comparisons of bifacial and monofacial yield by manufacturer and cell type and an analysis of bifacial gain versus irradiance.

Erion-Lorico, Tristan↗
DOE OSTI2024

Reversible Methane Electrochemical Reactors as Efficient Energy Storage for Fossil Power

The overall objective of the project was to conduct a comprehensive Research & Development (R&D) program to demonstrate the suitability and future advancement and integration of reversible methane protonic ceramic electrochemical reactors (PCERs) as an efficient Energy Storage System (ESS) with fossil fuel power plants. Fundamental process and system models are developed to conduct a preliminary conceptual study and investigate the power plant system integration requirements, performance requirements, and technical and non-technical gaps for eventual implementation at system level. Technology maturation requirements is also investigated through identifying the critical technical elements and networking with industrial technology developers and end-users.

08 HYDROGEN↗
DOE OSTI2025

System Analysis of an Internal Combustion Engine (ICE) - Solid Oxide Fuel Cell (SOFC) Hybrid Cycle

The variability of renewable energy sources poses challenges for reliable grid operation. Conventional thermal power sources, though reliable, often lack operational flexibility. Hybrid energy systems that integrate Solid Oxide Fuel cells (SOFC) with Internal Combustion Engines (ICE) offer a promising solution by achieving relatively higher efficiency and grid-following capability. This study investigates performance of a 100-kW pressurized SOFC-ICE hybrid cycle. In this configuration, unutilized SOFC fuel is used to drive the engine, with a turbocharger providing air supply and an external reformer generating syngas. System components were numerically modeled using MATLAB/SIMULINK for the SOFC and reformer, and EBSILON® for the ICE and balance of plant. Parametric studies varied fuel utilization (70-90%), reformer temperature (600 – 1000K), anode off-gas recirculation (0 – 70%), and current density (0.2 – 0.55 A/cm2). Results show that the SOFC and ICE operate as thermally independent topping and bottoming cycles, achieving peak efficiency of 62% under optimized conditions.

hybrid↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Utilizing CellBox to Describe Varied Dynamical Systems

CellBox is a hybrid modeling framework that integrates machine-learning approaches with explicit mathematical modeling to determine the behavior of dynamical systems, intended for determining the complex interactions of molecule and phenotype within a cellular environment using perturbation/response-based data. The original work utilized analysis of a melanoma cell line, SK-Mel-133, which we sought to expand to and evaluate effectiveness in describing other nonlinear systems both within and outside of biology. We evaluated with two models. One model is based upon the free-fall of an object under a velocity-dependent drag force; this produced inherent perturbation/response data. The other model is based upon a form of mass-action molecular kinetics; for this, we ran the simulation to steady state in each species for each perturbation and select the steady state as input for CellBox. We determined that CellBox, outside of its original use case, can still strongly predict even non-biological dynamical systems in the small-perturbation regime, with r = 0.99977 to 0.85123, p < 0.05 for freefall. However, CellBox cannot accurately predict behavior within large-perturbation regimes, p >> 0.05 for freefall. In addition, we performed a naïve comparison of CellBox network structure to known network structure in the mass-action model to assess accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Omics-Lethal Human Viruses, West Nile Experiment WDC011

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus (WNVMT) and mutant (WNVE218A) virus infection. Sample data was obtained from primary mouse myeloid dendritic cells for mRNA expression analysis. See Experiment WDC010 (GSE74628) for corresponding independent biological replicate study. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Untargeted GC-MS Metabolic Profiling of Anaerobic Gut Fungi Reveals Putative Terpenoids and Strain-Specific Metabolites

Background/Objectives: Anaerobic gut fungi (Neocallimastigomycota) are biotechnologically relevant, lignocellulose-degrading microbes with under-explored biosynthetic potential for secondary metabolites. Untargeted metabolomic profiling with gas chromatography–mass spectrometry (GC-MS) was applied to two gut fungal strains, Anaeromyces robustus and Caecomyces churrovis, to establish a foundational metabolomic dataset to identify metabolites and provide insights into gut fungal metabolic capabilities. Methods: Gut fungi were cultured anaerobically in rumen-fluid-based media with a soluble substrate (cellobiose), and metabolites were extracted using the Metabolite, Protein, and Lipid Extraction (MPLEx) method, enabling metabolomic and proteomic analysis from the same cell samples. Samples were derivatized and analyzed via GC-MS, followed by compound identification by spectral matching to reference databases, molecular networking, and statistical analyses. Results: Distinct metabolites were identified between A. robustus and C. churrovis, including 2,3-dihydroxyisovaleric acid produced by A. robustus and maltotriitol, maltotriose, and melibiose produced by C. churrovis. C. churrovis may polymerize maltotriose to form an extracellular polysaccharide, like pullulan. GC-MS profiling potentially captured sufficiently volatile products of proteomically detected, putative non-ribosomal peptide synthetases and polyketide synthases of A. robustus and C. churrovis. The triterpene squalene and triterpenoid tetrahymanol were putatively identified in A. robustus and C. churrovis. Their conserved, predicted biosynthetic genes—squalene synthase and squalene tetrahymanol cyclase—were identified in A. robustus, C. churrovis, and other anaerobic gut fungal genera. Conclusions: This study provides a foundational, untargeted metabolomic dataset to unmask gut fungal metabolic pathways and biosynthetic potential and to prioritize future efforts for compound isolation and identification.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Microwave Flow Cytometric Detection and Differentiation of Escherichia coli

Label-free measurement and analysis of single bacterial cells are essential for food safety monitoring and microbial disease diagnosis. We report a microwave flow cytometric sensor with a microstrip sensing device with reduced channel height for bacterial cell measurement. Escherichia coli B and Escherichia coli K-12 were measured with the sensor at frequencies between 500 MHz and 8 GHz. The results show microwave properties of E. coli cells are frequency-dependent. A LightGBM model was developed to classify cell types at a high accuracy of 0.96 at 1 GHz. Thus, the sensor provides a promising label-free method to rapidly detect and differentiate bacterial cells. Nevertheless, the method needs to be further developed by comprehensively measuring different types of cells and demonstrating accurate cell classification with improved machine-learning techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A chemical probe of CARM1 alters epigenetic plasticity against breast cancer cell invasion

CARM1 is a cancer-relevant protein arginine methyltransferase that regulates many aspects of transcription. Its pharmacological inhibition is a promising anti-cancer strategy. Here SKI-73 (6a in this work) is presented as a CARM1 chemical probe with pro-drug properties. SKI-73 (6a) can rapidly penetrate cell membranes and then be processed into active inhibitors, which are retained intracellularly with 10-fold enrichment for several days. These compounds were characterized for their potency, selectivity, modes of action, and on-target engagement. SKI-73 (6a) recapitulates the effect of CARM1 knockout against breast cancer cell invasion. Single-cell RNA-seq analysis revealed that the SKI-73(6a)-associated reduction of invasiveness acts by altering epigenetic plasticity and suppressing the invasion-prone subpopulation. Interestingly, SKI-73 (6a) and CARM1 knockout alter the epigenetic plasticity with remarkable difference, suggesting distinct modes of action for small-molecule and genetic perturbations. We therefore discovered a CARM1-addiction mechanism of cancer metastasis and developed a chemical probe to target this process.

60 APPLIED LIFE SCIENCES↗