Hydrogen Contaminant Detector Transition to Production (HCD-TTP II)
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Moscoso, Jerome↗
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Native Top-Down Mass Spectrometry Characterization of Model Integral Membrane Protein Bacteriorhodopsin
Bacteriorhodopsin (bR) from Halobacterium salinarum has been a model system for structural biology and is a structural template for the characterization of membrane G-protein couple receptors (GPCRs) in particular. Here, in this study, wild-type bacteriorhodopsin and two single-residue mutants were characterized by native top-down mass spectrometry (nTD-MS) with Orbitrap-based high-energy collision dissociation (HCD) and electron capture dissociation (ECD). After in-source dissociation ejected the membrane protein from detergent micelles, high-resolution native MS measurement allowed for identification of multiple proteoforms as well as lipid-bound forms. Further top-down MS measurements by HCD produced a large number of product ions for in-depth sequencing and unambiguous localization of post-translational modifications. For the first time, native TD-MS with ECD was used to characterize an integral membrane protein. ECD yielded fragments originating from all helices and loop regions, even accessing a sequence stretch that HCD could not. Combining HCD and ECD fragmentation patterns significantly enhanced the sequence coverage of bR. We propose bR to be a model analyte for testing nTD-MS performance for membrane proteins.
crystal cleavage↗
Heavy Duty Hydrogen: Reference Station, Fueling Performance Test Device Concepts, and Station Capacity Model (CRADA Final Report)
This project will provide valuable information on (1) reference station design, (2) exploration of design concepts for a fueling performance test device, and (3) modeling of station capacity. The work applies to heavy-duty (HD) hydrogen fueling stations with large dispensing capacity and high flowrates servicing HD hydrogen trucks such as class 8 trucks in long haul applications. Additionally, a 4th area will provide near-real-time verification of fuel quality with on-site hydrogen contaminant detectors (HCDs) for use at both light-duty (LD) and HD stations. The work leverages national lab capabilities including staff and equipment at SNL, NLR, and ANL with collaboration and funding cost share from California agencies (CEC, SCAQMD, and GO-Biz). This project will provide tools and information that lead to more efficient design, acceptance, and commissioning of these larger capacity, higher flowrate stations serving HD applications. The HCD work will benefit both LD and HD stations. Note: The 4th area (HCD) mentioned above continued outside of this CRADA and will not be included in this report. There are no tasks included in this CRADA for HCD and the summary text for it should have been removed prior to this CRADA contract execution but remained in error and is included here for completeness.
08 HYDROGEN↗
Automated Label‐Free Assay for Viral Detection and Inhibitor Screening via Biomembrane‐Functionalized Microelectrode Arrays
Most virus infection assays have indirect readout such as virus number following entry (e.g., PCR, cell lysis). While effective, these technologies are labor‐intensive, require specialized environments (e.g., sterile or RNA‐free), and detect later‐stage viral events like lysis or cell death, lacking sensitivity to early fusion events. To address these limitations, we present biologically relevant 2D membrane materials, host‐cell‐derived supported lipid bilayers (hcd‐SLBs), integrated with organic microelectrode arrays (OMEAs) for detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) fusion. By overexpressing angiotensin‐converting enzyme 2 (ACE2) receptors on the native membranes, the platform functions as a viral sensor capable of detecting virus pseudo particles (VPPs) through the late pathway. Additionally, hcd‐SLBs extracted from human lung epithelium expressing native ACE2 detect fusion events through the early pathway. The platform's utility as a drug‐screening tool is demonstrated by testing antibodies targeting either the ACE2 on the host membrane or the viral spike (S) proteins. To enhance the throughput, microfluidics are integrated for automation and OMEAs are incorporated within each channel, miniaturizing the testing units. This system supports high‐throughput data generation, automation, and scalability, providing an efficient platform for viral fusion detection that advances the study of pathogen‐host interactions and accelerates antiviral drug discovery.
Biology↗
Modeling of the high column density systems in the Lyman-Alpha forest
The Lyman-α forests observed in the spectra of high-redshift quasars can be used as a tracer of the cosmological matter density to study baryon acoustic oscillations (BAO) and the Alcock-Paczynski effect. Extraction of cosmological information from these studies requires modeling of the forest correlations. While the models depend most importantly on the bias parameters of the intergalactic medium (IGM), they also depend on the numbers and characteristics of high-column-density systems (HCDs) ranging from Lyman-limit systems with column densities log N HI /1cm -2 > 17 to damped Lyman-α systems (DLAs) with log N HI /1cm -2 > 20.2. These HCDs introduce broad damped absorption characteristic of a Voigt profile. Consequently they imprint a component on the power spectrum whose modes in the radial direction are suppressed, leading to a scale-dependent bias. Using mock data sets of known HCD content, we test a model that describes this effect in terms of the distribution of column densities of HCDs, the Fourier transforms of their Voigt profiles and the bias of the halos containing the HCDs. Our results show that this physically well-motivated model describes the effects of HCDs with an accuracy comparable to that of the ad-hoc models used in published forest analyses. We also discuss the problems of applying the model to real data, where the HCD content and their bias is uncertain.
Lyman alpha forest↗
Safeguards by Design Table Top Exercises Final Report (FY 2023)
This University Engagement project challenged engineering students at universities, that do not have bachelor’s degree programs in nuclear engineering but do have research reactors and some nuclear engineering coursework, to develop capacity in Safeguards by Design concepts through the application of Tabletop Exercises. This University Engagement project was part of the U. S. Department of Energy’s (DOE) National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation, Office of International Nuclear Safeguards, Next Generation Safeguards Initiative (NGSI), Human Capital Development (HCD): University Engagement Program. This program exposed university students with Mechanical Engineering majors and Nuclear Engineering minors to the concepts of international nuclear safeguards. In FY22, three teams at the University of Rhode Island and two teams at the University of Texas Austin participated in researching, designing, building, and testing projects to support international nuclear safeguards measurements or verification. The projects involved engaging in activities at the university’s research reactors. All the projects engaged students with prototyping a design and/or tool for application at the Universities’ reactor. However, for FY23, the direction of the HCD project had changed to implementing a Tabletop Exercise in Safeguards by Design (SBD). A Tabletop Exercise was not executed during FY23, but relationships with both Universities was maintained and how to integrate the exercise into the curriculum of both programs was determined.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Subject-specific multi-scale modeling of the fate of inhaled aerosols
Determining the fate of inhaled aerosols in the respiratory system is essential in assessing the potential toxicity of inhaled airborne materials, responses to airborne pathogens, or in improving inhaled drug delivery. The availability of high-resolution clinical lung imaging and advances in the reconstruction of lung airways from CT images have led to the development of subject-specific in-silico 3D models of aerosol dosimetry, often referred to as computational fluid-particle-dynamics (CFPD) models. As CFPD models require extensive computing resources, they are typically confined to the upper and large airways. These models can be combined with lower-dimensional models to form multiscale models that predict the transport and deposition of inhaled aerosols in the entire respiratory tract. Understanding where aerosols deposit is only the first of potentially several key events necessary to predict an outcome, being a detrimental health effect or a therapeutic response. To that end, multiscale approaches that combine CFPD with physiologically-based pharmacokinetics (PBPK) models have been developed to evaluate the absorption, distribution, metabolism, and excretion (ADME) of toxic or medicinal chemicals in one or more compartments of the human body. CFPD models can also be combined with host cell dynamics (HCD) models to assess regional immune system responses. Here, this paper reviews the state of the art of these different multiscale approaches and discusses the potential role of personalized or subject-specific modeling in respiratory health.
60 APPLIED LIFE SCIENCES↗
Ultra-stable trimetallic phosphide heterostructure with regulated electronic structure for overall water splitting at high current densities
Developing ultra-stable electrocatalysts for highly efficient overall water splitting at high current density (HCD) is critical for renewable hydrogen/oxygen production in the industry. However, the most active electrocatalysts for large current-driven water splitting are seriously handicapped by insufficient electrical contact kinetics due to the intensive bubble overflow. Herein, we demonstrate the ultra-stable trimetallic phosphides of NiFeP/NiCoP catalysts on a hydrophilic Ni foam skeleton via a corrosion-hydrothermal-phosphating strategy. The optimized NiFeP/NiCoP catalyst stabilizes for 600 h at -1 A cm -2 for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline solution, and it only needs low overpotentials of 237 and 314 mV to drive HER and OER at 1 A cm -2 , respectively. As expected, the optimized NiFeP/NiCoP electrode maintains 1000 h at 0.5 A cm -2 for water splitting, ranking among the top performers among reported catalysts. Such excellent performance could be attributed to the fast electron transfer for electrochemical reactions, the electron-deficient Fe/Ni sites contribute to forming robust metal oxyhydroxide during OER, and electron-rich Co sites facilitate H adsorption during HER. In conclusion, the findings present a highly promising candidate for ultra-stable non-noble metal electrocatalysts, offering a viable option for hydrogen/oxygen supply for fuel cells and metal-air batteries.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Dual-Gated Structures for Lossless Ion Manipulations-Ion Mobility Orbitrap Mass Spectrometry Platform for Combined Ultra-High-Resolution Molecular Analysis
High-resolution ion mobility spectrometry-mass spectrometry (HR-IMS-MS) instruments have enormously advanced the ability to characterize complex biological mixtures. Unfortunately, HR-IMS and HR-MS measurements are typically performed independently due to mismatches in analysis time scales. Here we overcome this limitation by using a dual-gated ion injection approach to couple an 11-meter path length structures for lossless ion manipulations (SLIM) module to a Q-Exactive Plus Orbitrap MS. The dual-gate setup was implemented by placing one ion gate before the SLIM module and a second ion gate after. The dual-gated ion injection approach allowed the new SLIM-Orbitrap platform to simultaneously perform an 11-meter SLIM separation, Orbitrap mass analysis using the highest selectable mass resolution setting (up to 140k), and high-energy collision induced dissociation (HCD) in ~25 minutes over an $m/z$ range of ~1500 amu. The SLIM-Orbitrap was initially characterized using a mixture of standard phosphazene cations and demonstrated an average SLIM CCS resolving power (Rp CCS ) of ~218 and SLIM peak capacity of ~156 while simultaneously obtaining high mass resolutions. SLIM-Orbitrap analysis with fragmentation was then performed on mixtures of standard peptides and two reverse peptides (SDGRG 1+ , GRGDS 1+ , Rp CCS = 305) to demonstrate the utility of combined HR-IMS-MS/MS measurements for peptide identification. Our new HR-IMS-MS/MS capability was further demonstrated by analyzing a complex lipid mixture and showcasing SLIM separations on isobaric lipids. In conclusion, this new SLIM-Orbitrap platform demonstrates a critical new capability for proteomics and lipidomics applications, and the high-resolution multimodal data obtainable with this system establishes the foundation for reference-free identification of unknown ion structures.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Detection of Br and I as atomic anions using liquid sampling – atmospheric pressure glow discharge/Orbitrap mass spectrometry
The quantification and determination of halogen isotope composition is essential in many fields including geochemistry and nuclear forensics. Detection of the halogen elements is commonly attempted with inductively coupled plasma mass spectrometry (ICP-MS) however, there are multiple challenges faced. Most significantly this includes very poor ionization efficiency and the potential for isobaric interferences from either matrix or plasma species. Thus, sensitivity and accuracy are often limiting issues. Here a liquid sampling-atmospheric pressure glow discharge (LS-APGD) ionization source is coupled with an ultrahigh resolution Orbitrap MS to perform halogen detection of bromine and iodine as initial analytes. This facilitates simple and sensitive detection of these elements as atomic anions from simple aqueous salt solutions. Collision-induced dissociation (CID) and higher-energy collisional dissociation (HCD) energies were optimized to produce the maximum response of Br − and I − . The LS-APGD conditions were optimized using a design of experiments (DOE) approach for Br − and I − concurrently. Response curves for Br − and I − solutions determined limit of detection (LOD) values of 50 pg and 5 pg, respectively, in 20 μL aliquots. The curves indicated response factors of 0.67 for 79 Br − and 0.90 for 127 I − . Br isotope ratios were determined with precision between 0.7 and 7.3% RSD, with the isotope ratios determined with precision 0.8% RSD at concentrations above the limit of quantification. Preliminary tests were conducted to evaluate the effect of different cations (Na + , K + , and Mg 2+ ) on Br − responses, with no discernible impacts observed on the halogen signal responses. This study demonstrates the potential use of the LS-APGD-Orbitrap-MS for the detection of multiple halogens while avoiding interferences, minimizing sample preparation, and overcoming ionization barriers.
Lang, Dehlia A. [Clemson University, SC (United St↗
Hydrogen Detection Strategies to Support H2@SCALE - The NREL Sensor Laboratory
Hydrogen represents a major pathway to decarbonize and stabilize the national and international energy industry and select manufacturing markets. To facilitate the development of hydrogen markets, the US Department of Energy initiated H2@Scale to bring together stakeholders to advance affordable hydrogen production, transport, storage, and utilization to increase revenue opportunities in multiple energy sectors. One major impediment to hydrogen implementation is cost. To expedite the use of hydrogen in energy and other markets, the United States announced in 2021 the Hydrogen Shot, which seeks to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). As the cost of hydrogen drops, new applications will emerge that will require unique configurations of existing equipment and infrastructure, and eventually lead to advances in the generation and utilization of hydrogen. As the hydrogen economy expands, sensors and detection methods will need to adapt to changing infrastructure demands to address the primary targets of health & safety, emissions monitoring, and process control. The NREL Sensor Laboratory is playing a pivotal role in advancing the use of hydrogen sensors and detection methodologies in each of these categories to support DOE's mission for safe and efficient utilization in emerging markets. Health & safety monitors are required to ensure that operators and facilities can react to unintended hydrogen releases, either as GH2, LH2, or as a constituent of blends (e.g., natural gas or ammonia). Current detection methodologies focus on safety applications to detect near its lower flammable limit (4 vol %), and typically include point sensors in applications such as fixed or mobile detectors (e.g., personal gas monitors). Methodologies amenable for area detection include acoustic, emerging optical imaging methods, and flame detectors. Comparable detection strategies can be utilized for emissions monitoring and quantization, however few methods can simultaneously cover both low (emissions) and high (health & safety) levels. Deployment of emission level detectors will be required to 1) reduce product loss through small but potentially significant leaks from an environmental or cost perspective, 2) reduce downtime of high demand systems by early identification of eminent system failures (leaks through pump or compressor seals indicative of impending failure), and 3) address potential emission monitoring requirements that may be set by regulating bodies. The first two points should be adopted by industry to reduce the cost-of-goods-sold. The third main category for hydrogen detection relates to process control and may be advantageous for many existing applications. Two main applications are emerging. For example, the purity requirements for hydrogen that is dispensed from refueling systems for hydrogen fuel cell electric vehicles (FCEV) is rigorously regulated by the Standard SAE J2719, which prescribes maximum allowable levels of multiple impurities in the hydrogen fuel and must be verified by a regulatory body. Hydrogen contaminant detectors (HCD) integrated to the fueling station can assure this compliance. HCDs must be able operate in 100% H2 backgrounds and be able to distinguish between multiple contaminants at low ppm to low ppb levels. Secondly, as a strategy to decarbonize the natural gas grid, there are proposals to blend hydrogen with natural gas. This blending will affect transport applications (pipeline infrastructure), stationary combustion systems (turbines), and consumer and commercial appliances. In the short-term, hydrogen levels up to 20% are proposed. Variations in the hydrogen level can have dramatic impact on the combustion process and on the potential response of safety sensors. These mixtures may be regulated so that the concentration at a delivery point must be monitored with high precision. However, routine maintenance may introduce background gases such as ambient air (with water) or maintenance gases (introduced with welding processes or adhesive outgassing.) Therefore, the detection methodology must be robust enough to recover or respond to various contaminants. Several reviews can be found in literature addressing sensing and detection technologies, including their limitations and applications. However, for most applications, limitations can be alleviated by combining various detection techniques either through system integration or implementation of machine learning methods (artificial intelligence). In this presentation, we will discuss several applications, highlight their current approach for hydrogen detection, and suggest detection strategies to supplement their limitations.
ENERGY STORAGE,HYDROGEN↗
Hydrogen Contaminant Detector
This presentation describes fiscal year 2022 status and accomplishments for NREL's Hydrogen Contaminant Detector project.
analyzer↗