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DOE OSTI2024

Quantifying Phospholipids in Organic Samples Using a Hydrophilic Interaction Liquid Chromatography–Inductively Coupled Plasma High-Resolution Mass Spectrometry (HILIC-ICP-HRMS) Method

Here, in this study, a novel method using hydrophilic interaction liquid chromatography (HILIC) coupled with inductively coupled plasma high-resolution mass spectrometry (ICP-HRMS) was introduced for the quantification of phospholipids in oil samples. The method employed a bridged ethyl hybrid (BEH) stationary phase HILIC column with a tetrahydrofuran (THF)/water mobile phase, enhancing the solubility and detection of phospholipids. During the study, a gradient/matrix effect on ICP-HRMS sensitivity was observed and successfully compensated for experimentally, ensuring reliable quantification results. This approach has proven effective for a wide range of different oil samples including vegetable oils, animal fats, and phospholipid supplements. Notably, this method allowed the direct quantification of phospholipids in oil samples, bypassing the need for prior sample preparation methods, such as solid phase extraction (SPE), thereby streamlining the analytical process. The precision, accuracy, and reduced need for extensive sample preparation offered by this method mark a significant advancement in lipids analysis. Its robustness and broad applicability have substantial implications for industries such as food and renewable energy production, where both efficient and accurate lipid identification and quantification are crucial.

09 BIOMASS FUELS↗

DOE OSTI2022

Development of an operando characterization stage for multi-modal synchrotron x-ray experiments

It is widely accepted that micro- and nanoscale inhomogeneities govern the performance of many thin-film solar cell absorbers. These inhomogeneities yield material properties (e.g., composition, structure, and charge collection) that are challenging to correlate across length scales and measurement modalities. The challenge is compounded if a correlation is sought during device operation or in conditions that mimic aging under particular stressors (e.g., heat and electrical bias). Correlative approaches, particularly those based on synchrotron x-ray sources, are powerful since they can access several material properties in different modes (e.g., fluorescence, diffraction, and absorption) with minimal sample preparation. Small-scale laboratory x-ray instruments have begun to offer multi-modality but are typically limited by low x-ray photon flux, low spatial resolution, or specific sample sizes. To overcome these limitations, a characterization stage was developed to enable multi-scale, multi-modal operando measurements of industrially relevant photovoltaic devices. The stage offers compatibility across synchrotron x-ray facilities, enabling correlation between nanoscale x-ray fluorescence microscopy, microscale x-ray diffraction microscopy, and x-ray beam induced current microscopy, among others. Furthermore, the stage can accommodate device sizes up to 25 × 25 mm 2 , offering access to multiple regions of interest and increasing the statistical significance of correlated properties. The stage materials can sustain humid and non-oxidizing atmospheres, and temperature ranges encountered by photovoltaic devices in operational environments (e.g., from 25 to 100 °C). As a case study, we discuss the functionality of the stage by studying Se-alloyed CdTe photovoltaic devices aged in the stage between 25 and 100 °C.

14 SOLAR ENERGY↗

DOE OSTI2022

Synthesis and acoustic properties study of castor‐oil‐based polyurethane foams with the addition of graphene‐oxide‐modified straw fibers

Abstract Polyurethane foam (PUF) can absorb sound by air friction and structural vibrations of cell walls. It is widely used as acoustic material in the automotive industry. According to existing studies, graphene oxide (GO) can improve the acoustic properties of PUF. However, GO tends to coalesce inside PUF. In this paper, straw fibers were modified with different concentrations of GO solution to embed GO on the surface of plant fibers. The GO was dispersed in the PUF using straw fibers. In addition, some studies show that the wrinkled morphology of the GO surface is believed to play a mechanical interlocking role in improving interfacial bonding, thus enhancing the stress transfer between the plant fibers and the polyurethane (PU) matrix and improving the mechanical properties of the PU composites. The acoustic and mechanical properties of the modified PU materials were observed by treating plant fibers with appropriate amounts of GO solution. The experimental study shows that the sample modified with 1 g L −1 GO solution reaches a maximum average sound absorption coefficient of 0.5838 when the straw fiber content reaches 0.5 g, and the sample modified with 2 g L −1 GO solution reaches a maximum transmission loss of 10.5333 when the straw fiber content reaches 1 g. © 2022 Society of Industrial Chemistry.

Yang, Keyao↗

DOE OSTI2021

Microbial drivers of methane emissions from unrestored industrial salt ponds

Wetlands are important carbon (C) sinks, yet many have been destroyed and converted to other uses over the past few centuries, including industrial salt making. A renewed focus on wetland ecosystem services (e.g., flood control, and habitat) has resulted in numerous restoration efforts whose effect on microbial communities is largely unexplored. We investigated the impact of restoration on microbial community composition, metabolic functional potential, and methane flux by analyzing sediment cores from two unrestored former industrial salt ponds, a restored former industrial salt pond, and a reference wetland. We observed elevated methane emissions from unrestored salt ponds compared to the restored and reference wetlands, which was positively correlated with salinity and sulfate across all samples. 16S rRNA gene amplicon and shotgun metagenomic data revealed that the restored salt pond harbored communities more phylogenetically and functionally similar to the reference wetland than to unrestored ponds. Archaeal methanogenesis genes were positively correlated with methane flux, as were genes encoding enzymes for bacterial methylphosphonate degradation, suggesting methane is generated both from bacterial methylphosphonate degradation and archaeal methanogenesis in these sites. These observations demonstrate that restoration effectively converted industrial salt pond microbial communities back to compositions more similar to reference wetlands and lowered salinities, sulfate concentrations, and methane emissions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Directly Probing the Fracture Behavior of Ultrathin Polymeric Films

Understanding fracture mechanics of ultrathin polymeric films is crucial for modern technologies, including semiconductor and coating industries. However, up to now, the fracture behavior of sub-100 nm polymeric thin films is rarely explored due to challenges in handling samples and limited testing methods available. In this work, we report a new testing methodology that can not only visualize the evolution of the local stress distribution through wrinkling patterns and crack propagation during the deformation of ultrathin films but also directly measure their fracture energies. Using ultrathin polystyrene films as a model system, we both experimentally and computationally investigate the effect of the film thickness and molecular weight on their fracture behavior, both of which show a ductile-to-brittle transition. Furthermore, we demonstrate the broad applicability of this testing method in semicrystalline semiconducting polymers. We anticipate our methodology described here could provide new ways of studying the fracture behavior of ultrathin films under confinement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Advances in Nb 3 Sn superconducting radiofrequency cavities towards first practical accelerator applications

Abstract Nb 3 Sn is a promising next-generation material for superconducting radiofrequency cavities, with significant potential for both large scale and compact accelerator applications. However, so far, Nb 3 Sn cavities have been limited to continuous wave accelerating fields <18 MV m −1 . In this paper, new results are presented with significantly higher fields, as high as 24 MV m −1 in single cell cavities. Results are also presented from the first ever Nb 3 Sn-coated 1.3 GHz 9-cell cavity, a full-scale demonstration on the cavity type used in production for the European XFEL and LCLS-II. Results are presented together with heat dissipation curves to emphasize the potential for industrial accelerator applications using cryocooler-based cooling systems. The cavities studied have an atypical shiny visual appearance, and microscopy studies of witness samples reveal significantly reduced surface roughness and smaller film thickness compared to typical Nb 3 Sn films for superconducting cavities. Possible mechanisms for increased maximum field are discussed as well as implications for physics of RF superconductivity in the low coherence length regime. Outlook for continued development is presented.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

In-line measurements of below-the-surface food deformation during drying with an interference-based optical fiber strain sensor

Real-time measurements of food deformation are important for quality control in drying, yet they pose significant challenges. In this study, we developed an interference-based optical fiber strain sensor to enable in-line, continuous, below-the-surface strain measurements in drying of soft food samples. Compared to a strain resolution of 8 × 10 -4 at zero strain and 7.2 × 10 -3 at 0.20 strain reported in our previously published work, the present study achieves markedly improved resolutions of 1.3 × 10 -4 at zero strain and 7.8 × 10 -4 at 0.25 strain, which strains are the lower and higher boundaries of the dynamic range, respectively. This nearly order-of-magnitude improvement is attributed to the unique interference-based sensing mechanism, no need for calibration to convert optical signals to strain, and the system-design-enabled immunity to fiber-disk misalignments and light source intensity fluctuations. To demonstrate the in-line process monitoring, deformation measurements of fresh banana slices and sugar cookie doughs were carried out in a benchtop oven and an industrial-scale hot-air pilot dryer, respectively. In both dryers, strain measurements were continuously measured during the whole drying process at various depths and radii below the sample surfaces, with the strains up to 25%. Computer vision was used only in the benchtop drying to confirm the faithfulness of the fiber sensor measurements and cannot provide below-the-surface measurements. The measured spatiotemporal deformation allowed us to confirm the shell-hardening effect and to determine the speed and location of large deformation changes in the whole drying process, the latter of which is related to the sample cracking. To the best of the authors’ knowledge, this study is the first to report on an interferometry-based fiber sensor to measure food deformation. This sensor and the sensing mechanism have high potential for real-time process monitoring and control to prevent over-drying or cracking during drying processes.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Unsupervised Image-Based Classification of Corrosion Severity in Automobile Engine Connecting Rods

Corrosion in engine connecting rods is a critical issue in the automotive industry, potentially leading to catastrophic engine failure, monetary losses, and safety hazards. The labor shortage in the industry further emphasizes the need for fast, accurate, and automated corrosion detection methods to ensure appropriate surface treatments can be applied to restore component integrity. We present an unsupervised image-based framework for classifying corrosion severity in automobile engine connecting rods using short-wave infrared (SWIR) and telecentric grayscale imaging. We employ the structural similarity index measure (SSIM) as a dissimilarity metric and the k-medians clustering algorithm for classification. Our algorithm achieves an overall accuracy of 80.64% for SWIR images, with 100% accuracy in classifying highly corroded samples. For grayscale images, the method attains an overall accuracy of 77.42%, with 90.91% accuracy for highly corroded samples. The method’s ability to work with different imaging modalities and its high accuracy in identifying severe corrosion cases make it a promising tool for automated corrosion assessment in the automotive industry, potentially improving efficiency and safety in engine component maintenance.

42 ENGINEERING↗

DOE OSTI2021

A Computed Tomography Automation Architecture Developed from a Comprehensive Literature Review

This paper presents a literature review on techniques related to the computed tomography procedure that incorporate automation elements in their research investigations or industrial applications. Computed tomography (CT) is a non-destructive testing (NDT) technique in that the imaging and inspection are performed without damaging the sample, allowing for additional or repeated analysis if necessary. The reviewed literature is organized based on the steps associated with a general NDT task in order to define an end-to-end computed tomography automation architecture. The process steps include activities prior to image collection, during the scan, and after the data are collected. It further reviews efforts related to repeating this process based on a previous scan result. By analyzing the multiple existing but disparate efforts found in the literature, we present a framework for fully automating NDT procedures and discuss the remaining technical gaps in the developed framework.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Strategies to Recover Easily-Extractable Rare Earth Elements and Other Critical Metals from Coal Waste Streams and Adjacent Rock Strata Using Citric Acid

Maximum rare earth element (REE) extractability from a sample of Middle Kittanning coal seam underclay was previously demonstrated at ~30% of the total REE content with a citric acid solution (Montross et al., 2020). This report further refines the mechanisms of citrate application for leaching of coal seam underclays using an organic acid lixiviant and evaluates strategies to begin to scale this process to industrially relevant volumes. This study evaluates the suitability of citrate leaching solutions for downstream recovery and separation of the REEs via oxalic acid precipitation. The applicability of citric acid solutions to recover ion-adsorbed metals from clay surfaces was evaluated by leaching a prepared sample of kaolinite with known amounts of ion-adsorbed lanthanum. Citrate systematics was further defined through experiments varying the solution pH. Up-scaling investigations proceeded with percolation leaching columns and stirred tank reactors. Two embodiments were run in percolation leaching: a continuous flow-through process and a multi-stage saturated process. The results showed that in certain limited scenarios, low pH citrate solutions could be used to target REEs mineralized within secondary calcium phosphate minerals. Results from the upscaling attempts encountered difficulties in extraction efficiencies. For the percolation columns, hydrodynamic flow was insufficient to recover the extractable REE content fully. For the stirred barrels, mixing inefficiencies likely inhibited the extractability of the REEs. Oxalic acid precipitation experiments also highlighted difficulties in downstream operations. The REEs were removed from the citrate solution with high efficiency, but were accompanied by equally efficient removal of calcium in orders of magnitude of greater amounts. Overall, for citrate leaching to be effective, future studies will have to: 1) carefully consider the feedstock application (i.e., likely better suited for secondary mineralization of calcium phosphate minerals), and 2) overcome the technical barriers of large-scale processing, such as inefficient hydrodynamic regimes due to small crush sizes needed and difficulties in downstream separation and purification. Alternatively, citrate solutions may be better recommended as leaching amendments to other leaching solutions to enhance REE complexation in the solution.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Effect of moisture ingression on material performance and particle generation in molten salts

This report summarizes activities conducted to understand and mitigate the negative consequences that moisture ingressions have upon the operations of pyroprocessing equipment. The objectives of the work conducted in FY25 were to characterize (1) the physicochemical properties of particles generated as a result of moisture ingressions, and (2) the corrosion of relevant structural materials with the introduction of moisture. Compositional and morphological analyses of the generated particles were conducted through a suite of characterization technologies, including X-ray diffraction, microscopy, and particle size analysis. The results gathered this year were compared to those obtained in FY24 when studies with oxygen ingressions were conducted on CeCl 3 -LiCl-KCl and UCl 3 -LiCl-KCl systems. Investigations involving performance evaluations of industrially relevant structural alloys were also conducted under moisture ingress conditions. In-line electrochemical monitoring of the bulk salt was augmented with microscopy of alloy samples to quantify the concentration and accumulation of corrosion products in the bulk salt. The results reported in this work provide a more holistic understanding of the effects of atmospheric ingressions on molten chloride salt chemistry such that effective redox control strategies may be implemented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

PACT Center: Perovskite PV Accelerator for Commercializing Technologies (Final Technical Report)

The Perovskite PV Accelerator for Commercializing Technologies (PACT) center was established in July 2021 as a national resource to accelerate the commercialization of perovskite photovoltaic (PV) technology in the United States. Since its inception, PACT has been led by Sandia National Laboratories (Sandia) in partnership with the National Laboratory of the Rockies (NLR), formerly known as NREL. From FY20-FY23, Los Alamos National Laboratory (LANL), CFV Labs, Black & Veatch (B&V), and the Electric Power Research Institute (EPRI) were part of the project team. LANL brought expertise in perovskite PV device designs and processing, CFV Labs (now GroundWork Renewables) provided initial indoor and outdoor measurement hardware technology, B&V led the initial effort on perovskite PV bankability, and EPRI worked on reviewing testing standards, identifying commercialization gaps, and helping to run PACT’s Industry Advisory Board, a group including representatives from commercial testing labs, independent engineering firms, insurance companies, state regulators, and electric utilities. To source perovskite PV module samples, PACT contracted with the University of North Carolina (UNC), the University of Toledo, the University of Washington, and SLAC/Stanford University to provide a steady stream of research-grade perovskite mini modules, enabling protocol development in advance of commercial module availability. The project period ran from July 1, 2021, through December 31, 2025, including a No Cost Extension. Starting in FY25, the project was continued as a Core Capability in the Lab Call portfolio and continues at a reduced budget with only Sandia and NLR as funded recipients. Notably, starting in FY25 PACT expanded its scope beyond MHP modules to accept all emerging PV mini module technologies for testing, including organic PV (OPV) and all-thin-film tandems, with the aim of supporting commercialization across the broader emerging PV ecosystem. With this change in scope the program was renamed the PV Accelerator for Commercializing Technologies, dropping perovskite from the name.

14 SOLAR ENERGY↗

DOE OSTI2025

ORBITaL-Net: A labeled training library for large-scale building feature extraction

Over the course of several years, nearly 1.5 million building outlines have been created from approximately 128,000 training tiles covering roughly 7,000 km 2 of very high-resolution multispectral overhead imagery, primarily dated between 2010 and 2020. This dataset, dubbed the Oak Ridge Building Image and TrAining Label Net (ORBITaL-Net), is designed for machine learning applications and is global in scope, with samples drawn from 72 countries across North America, South America, Africa, Europe, and Asia. ORBITaL-Net captures a great diversity in geographic setting, structural characteristics, land use (urban and rural), terrain, and imagery conditions. While the labeled building outlines are themselves valuable, the dataset’s true strength lies in the pairing of these labels with corresponding reference imagery, which is being released for open source use. Similar to SpaceNet and Replicable AI For Microplanning (ramp), this building outline dataset will allow the larger computer vision community from academia, government, and industry the opportunity to develop robust, scalable, and generalizable geospatial machine learning techniques. Unlike SpaceNet and ramp, which offer high resolution labels and imagery primarily for large urban cities, ORBITaL-Net is not focused on training samples from heavily populated areas but instead aims to capture the innate variability of conditions present in both the physical environment and imagery collections.

Geography↗

DOE OSTI2022

Effects of Mechanical Recycling on Carbon Fiber-Based Hybrid Composites

Carbon fiber (CF) reinforced composites are high-performing, highly utilized material systems historically used in aerospace. As the cost of CF decreases, other industries, such as automotive and energy generation, seek to adopt CF composites into their applications. A sudden increase in CF demand may create supply chain issues if the adoption happens without scaling up of the CF production. A solution for reducing the reliance on CF is to substitute some portion of the CF content with another fiber type without significantly reducing the material properties. When multiple reinforcing fillers are introduced into a composite system, the materials system is often referred to as a hybrid composite and in this case a CF-based hybrid composite. To further relieve reliance on CF and with sustainable manufacturing becoming more prominent in industry, mechanical recycling can be employed to replace all or a percentage of the virgin material content. Utilizing recycled content in place of virgin content will further aid in reducing the reliance on virgin CF and decrease overall material costs. Here, the effects of utilizing mechanically recycled feedstocks on the mechanical properties of injection molded samples are explored to understand the feasibility of re-manufacturing recycled CF-based hybrid composites. By determining the mechanical properties and mechanisms in which the properties change through varying recycled content, the assessment of how the material will perform in other manufacturing processes can be inferred. As a result, industry will gain better insight into utilizing mechanically recycled feedstocks to reduce their reliance on the CF supply chain.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Bioactivity Profiling of Chemical Mixtures for Hazard Characterization

Abstract The assessment and regulation of chemical toxicity to protect human health and the environment are done one chemical at a time and seldom at environmentally relevant concentrations. However, chemicals are found in the environment as mixtures, and their toxicity is largely unknown. Understanding the hazard posed by chemicals within the mixture is critical to enforce protective measures. Here, we demonstrate the application of bioactivity profiling of environmental water samples using the sentinel and ecotoxicology model species Daphnia to reveal the biomolecular response induced by exposure to real-world mixtures. We exposed a Daphnia strain to 30 sampled waters of the Chaobai River and measured the gene expression response profiles. Using a multiblock correlation analysis, we establish correlations between chemical mixtures identified in 30 water samples with gene expression patterns induced by these chemical mixtures. We identified 80 metabolic pathways putatively activated by mixtures of inorganic ions, heavy metals, polycyclic aromatic hydrocarbons, industrial chemicals, and a set of biocides, pesticides, and pharmacologically active substances. Our data-driven approach discovered both known bioactivity signatures with previously described modes of action and new pathways linked to undiscovered potential hazards. This study demonstrates the feasibility of reducing the complexity of real-world mixture toxicity to characterize the biomolecular effects of a defined number of chemical components based on gene expression monitoring of the sentinel species Daphnia.

Engineering↗

DOE OSTI2023

2022 American Conference on Neutron Scattering (ACNS 2022)

The 11th American Conference on Neutron Scattering (ACNS 2022) will be held on June 5-9, 2022, in Boulder, CO. The Conference will provide essential information on the breadth and depth of current neutron-related research worldwide. Hosted by the Neutron Scattering Society of America, this year’s Conference will feature a combination of invited and contributed talks, poster sessions, and tutorials. Topics of the conference are: Advances in Neutron Facilities, Instrumentation and Software: Developments in sources, instrumentation, sample environments and control software. Hard Condensed Matter: Magnetism, correlated metals, quantum/topological materials, superconductors, ferroelectrics, multiferroics, glasses, and disorder phenomena. Submissions outlining examples of neutron scattering in industrial and engineering applications involving hard condensed matter systems are also encouraged. Soft Matter: Neutron studies of soft materials and related fields including in situ and in operando studies. Polymers, surfactants, emulsions, gels, nanoparticles, colloidal suspensions and more. Submissions of computational studies or applications of machine learning beneficial to neutron scattering experiments, as well as examples of neutron scattering in industrial and engineering applications are strongly encouraged. Biology, Biophysics and Biotechnology: Neutron studies of biological and biologically relevant systems. Proteins, bio membranes, biological assemblies, natural materials, nucleic acids, drug-delivery platforms and biomedical systems. Submissions of computational studies or applications of machine learning beneficial to biological neutron scattering experiments, as well as examples of neutron scattering in applied research involving biological systems, are strongly encouraged. Materials Chemistry and Energy: Neutron-based studies of functional materials and materials for energy applications. Examples include porous materials such as metal organic frameworks (MOFs), zeolites; phosphors; novel pigments; electrolytes; catalysts; ionic conductors/cathode materials; photovoltaic materials (hybrid perovskites); thermoelectrics; magnetocalorics/electrocalorics. Structural Materials and Engineering: Neutron scattering studies of materials and engineering processes including structural materials, concrete and metals, as well as engineering processes including combustion, corrosion, additive manufacturing, and others. Neutron Physics: Fundamental physical studies of the neutron and related areas. Emerging Applications in Neutron Scattering: Machine Learning and Data Science: Advances in computing power have contributed to rapidly evolving machine learning and data science fields that can be leveraged to the benefit of the neutron scattering community. The purpose of this session is to highlight recent advances in machine learning and data science and to serve as the foundation of a parallel data and computation track highlighting computation advances and applications in neutron scattering throughout the conference.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Rooftop Photovoltaics and Electric Vehicle Co-Adoption: Attitudes, Norms, Diffusion, and Economics

The overall objectives of the project were to (1) Identify personal and social norms, peer effects, demographics and contextual factors (such as household energy expenditures, experience with outages, charging infrastructure availability) that may facilitate or hinder Solar-EV co-adoption; (2) outline strategies for the design of programs and practices that will enable reasoned RPV and EV adoption and their co-adoption; and (3) assemble a dataset comprised of survey responses of RPV-EV co-adopters, RPV-only adopters, EV-only adopters, and non-adopters. These objectives were only partially fulfilled given the decision to terminate the project. The research team was able to complete the semi-structured interviews, the core BY1 task and summarize the results below. As well, once the team learned of the research project’s fate, it sought and obtained the DOE SETO Technical Manager’s approval to repurpose funds for BY2 tasks to the extent feasible. Rather than invest further resources in expanding the pool of potential survey respondents and having no budget to survey, the research team repurposed funds subject and undertook a more limited (geographically) survey, but also expanded to it to include contingent valuation questions. The analysis of the survey data will necessarily be delayed given the lack of budget support, although some information on the respondent sample is in the results. Given a lack of attention to co-adoption previously, the insights generated in this project should assist decision-makers and industry actors in the development of programs and practices that enable reasoned RPV adoption and EV adoption and their co-adoption.

14 SOLAR ENERGY↗

DOE OSTI2026

Portable and Cost-Effective Device for Reliable Detection of Counterfeit and Non-compliant Refrigerants in Diverse Applications

Counterfeit refrigerants pose significant challenges to safety, system reliability, and operational effectiveness due to their harmful contaminants or incompatible chemical compositions. Utilizing these noncompliant products can lead to reduced efficiency, equipment failures, and expensive repairs. Additionally, heightened demand for alternative refrigerants during the industry's transition has created supply gaps, enabling counterfeit products to proliferate. Accurate detection and analysis tools are therefore essential to verify refrigerant authenticity and ensure system integrity in diverse applications. This paper presents the development of a portable device designed for reliable identification and detailed analysis of refrigerant composition. By integrating precision gas sampling, controlled pressure regulation, and automated sensor technology, the device not only detects deviations from standard refrigerant properties but also provides a comprehensive composition breakdown. Pre-calibrated sensors measure the refrigerant gas to identify specific concentrations and contaminants, with an intuitive LED-based indicator system ensuring quick interpretation of results. The user-friendly interface enables operators to select refrigerant types for targeted testing, further enhancing accuracy and usability for field technicians. Comprehensive testing was conducted on mildly flammable A2L refrigerants, showcasing the device’s robustness and adaptability in analyzing composition and detecting discrepancies. The device demonstrated consistent accuracy across a range of refrigerant samples, affirming its reliability in diverse operational environments. Its design minimizes contamination risks during sampling and provides detailed composition results within 90 seconds, ensuring efficient and precise analysis. With a projected price point under $150, the proposed solution delivers affordability alongside its lightweight portability and straightforward operation. Unlike complex and costly alternatives, such as gas chromatography systems, this device provides an accessible option for technicians, customs personnel, and industry operators in need of quick and effective refrigerant verification. Compatible with both current formulations and emerging refrigerant technologies, the device addresses critical counterfeit detection needs across a range of applications. By delivering accurate composition analysis and counterfeit identification, this innovation enhances system performance, safety, and operational reliability in crucial industries.

Cheekatamarla, Praveen [ORNL] (ORCID:0000000248827↗