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DOE OSTI2020

MCP-PMT development at Argonne for particle identification

The proposed high-energy high-luminosity polarized Electron-Ion Collider (EIC) demands excellent particle identification over a wide range of particles momenta to achieve the best separation between signal and background particles. Various Cherenkov imaging detector sub-systems are being considered in EIC detector concepts for hadron identification for particles momenta up to 50 GeV/c. One important challenge in this case is to provide a reliable highly pixelated photosensor working in the high radiation and high magnetic field environment. The recently commercialized Large Area Picosecond Photo-Detector (LAPPD) provides a promising low-cost photosensor solution for the various EIC Cherenkov imaging sub-systems. Optimization of the phtosensor design for high magnetic field tolerance, precision timing resolution, and pixelated readout was performed at Argonne National Laboratory with 6 x 6 cm(2) microchannel plate photomultipliers. The techniques and optimized design parameters would be transferrable to industrial partners for low-cost LAPPD production to achieve the demonstrated performance.

atomic layer deposition↗

DOE OSTI2023

A variational encoder–decoder approach to precise spectroscopic age estimation for large Galactic surveys

Constraints on the formation and evolution of the Milky Way Galaxy require multidimensional measurements of kinematics, abundances, and ages for a large population of stars. Ages for luminous giants, which can be seen to large distances, are an essential component of studies of the Milky Way, but they are traditionally very difficult to estimate precisely for a large data set and often require careful analysis on a star-by-star basis in asteroseismology. Because spectra are easier to obtain for large samples, being able to determine precise ages from spectra allows for large age samples to be constructed, but spectroscopic ages are often imprecise and contaminated by abundance correlations. Here we present an application of a variational encoder–decoder on cross-domain astronomical data to solve these issues. The model is trained on pairs of observations from APOGEE and Kepler of the same star in order to reduce the dimensionality of the APOGEE spectra in a latent space while removing abundance information. The low dimensional latent representation of these spectra can then be trained to predict age with just ∼1000 precise seismic ages. We demonstrate that this model produces more precise spectroscopic ages (∼ 22 per cent overall, ∼ 11 per cent for red-clump stars) than previous data-driven spectroscopic ages while being less contaminated by abundance information (in particular, our ages do not depend on [α/M]). We create a public age catalogue for the APOGEE DR17 data set and use it to map the age distribution and the age-[Fe/H]-[α/M] distribution across the radial range of the Galactic disc.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

The impact of nickel concentration and stacking fault energy on deformation mechanisms in high-purity austenitic Fe-Cr-Ni alloys

Understanding how composition affects deformation mechanisms in austenitic stainless steels is essential for developing accurate predictive models of stress-induced failures and stress corrosion cracking. Nickel (Ni), an element classified as a critical element, plays a crucial role in these processes. It is important to examine how Ni concentration influences stacking fault energy (SFE) and, consequently, the deformation mechanisms of austenitic stainless steels. However, in commercial stainless steels, the effects of other alloying elements and impurities can obscure Ni's role, complicating efforts to isolate its impact. Here, in this study, we use two high-purity Fe-Cr-Ni alloys to investigate how Ni concentration and SFE interact to alter deformation mechanisms and induce martensitic transformation. By combining in situ synchrotron X-ray diffraction (XRD) tensile testing and post-mortem electron microscopy with density functional theory simulations, we gain precise insights into these phenomena. We find that the Fe18Cr10Ni (wt%) alloy, with its low SFE, exhibits higher stacking fault probability, deformation-induced martensitic transformation, and a lesser increase in dislocation density with plastic strain. In contrast, the Fe18Cr14Ni (wt%) alloy, with its higher SFE, shows enhanced deformation twinning and greater dislocation density with increasing strain. These findings from high-purity ternary alloys provide valuable insights that can guide the search for alternative elements to replace Ni while achieving similar effects on phase stability and deformation behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2023

An alternative viewpoint on the nuclear structure towards 100 Sn: Lifetime measurements in 105 Sn

This work aims at presenting an alternative approach to the long standing problem of the B(E2) values in Sn isotopes in the vicinity of the N=Z double-magic nucleus 100 Sn, until now predominantly measured with relativistic and intermediate-energy Coulomb excitation reactions. The direct measurement of the lifetime of low-lying excited states in odd-even Sn isotopes provides a new and precise guidance for the theoretical description of the nuclear structure in this region. Lifetime measurements have been performed in 105 Sn for the first time with the coincidence Recoil Distance Doppler Shift technique. The lifetime results for the $7/2^+_1$ first excited state and the $11/2^+_1$ state, $2^+ (^{104}$Sn) Ⓧ $v1g_{7/2}$ multiplet member, are discussed in comparison with state-of-the-art shell model and mean field calculations, highlighting the crucial contribution of proton excitation across the core of 100 Sn. The reduced transition probability B(E2) of the $11/2^+_1$ core-coupled state points out an enhanced staggering with respect to the B(E2; $2^+_1$ → $0^+_1$) in the even-mass 104 Sn and 106 Sn isotopes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Reversible Electron-Beam Patterning of Colloidal Nanoparticles at Fluid Interfaces

The directed self-assembly of colloidal nanoparticles (NPs) using external fields guides the formation of sophisticated hierarchical materials but becomes less effective with decreasing particle size. As an alternative, electron-beam-driven assembly offers a potential avenue for targeted nanoscale manipulation, yet remains poorly controlled due to the variety and complexity of beam interaction mechanisms. Here, we investigate the beam–particle interaction of silica NPs pinned to the fluid–vacuum interface of ionic liquid droplets. In these experiments, scanning electron microscopy of the droplet surface resolves NP trajectories over space and time while simultaneously driving their reorganization. With this platform, we demonstrate the ability to direct particle transport and create transient, reversible colloidal patterns on the droplet surface. By tuning the beam voltage, we achieve precise control over both the strength and sign of the beam–particle interaction, with low voltages repelling particles and high voltages attracting them. This response stems from the formation of well-defined solvent flow fields generated from trace radiolysis of the ionic liquid, as determined through statistical analysis of single-particle trajectories under varying solvent composition. Altogether, electron-beam-guided assembly introduces a versatile strategy for nanoscale colloidal manipulation, offering new possibilities for the design of dynamic, reconfigurable systems with applications in adaptive photonics and catalysis.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Additive Manufacturing of Porous Ceramics With Foaming Agent

The macro-porous ceramics has promising durability and thermal insulation performance. As porous ceramics find more and more applications across many industries, a cost-effective and scalable additive manufacturing technique for fabricating macro-porous ceramics is highly desirable. Herein, we reported a facile additive manufacturing approach to fabricate porous ceramics and control the printed porosity. Several printable ceramic inks were prepared, and the foaming agent was added to generate gaseous bubbles in the ink, followed by the direct ink writing and the ambient-pressure and room-temperature drying to create the three-dimensional geometries. In this work, a set of experimental studies were performed to optimize the printing quality. The results revealed the optimal process parameters for printing the foamed ceramic ink with a high spatial resolution and fine surface quality. Varying the concentration of the foaming agent enables the controllability of the structural porosity. The maximum porosity can reach 85%, with a crack-free internal porous structure. The tensile tests showed that the printed macro-porous ceramics possessed enhanced durability with the addition of fiber. With a high-fidelity three-dimensional (3D) printing process and the precise controllability of the porosity, we showed that the printed samples exhibited a remarkably low thermal conductivity and durable mechanical strength.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Photon Detection System Calibration for DUNE

Photon Detection System Calibration for DUNE Not scheduled 20m Conference Center (University of California, Irvine) Poster New Technologies for Neutrino Physics Poster session Speaker Denis Torres (South Dakota School of Mines and Technology) Description The Deep Underground Neutrino Experiment (DUNE) is a long baseline neutrino oscillation experiment that relies on a precise Photon Detection System (PDS) to provide accurate timing information, enhance sensitivity to low-energy and non-beam events, and support detector performance studies in liquid argon time projection chambers. Achieving these goals requires a well-understood and stable optical calibration strategy that operates reliably under cryogenic conditions. In this poster, I will present PDS calibration studies performed in ProtoDUNE, focusing on the characterization of the ultraviolet (UV) light calibration system and key optical components in the light-delivery chain. I will discuss measurements of optical fiber transmission, SMA-to-SMA connector and feedthrough interface losses, and diffuser assemblies, emphasizing wavelength dependence, attenuation, and performance under cryogenic thermal cycling and stability tests. These studies provide quantitative inputs for understanding light transport, uniformity, and long-term reliability of the PDS in large-scale liquid argon detectors, and they directly inform calibration strategies for the DUNE Far Detector.

Torres Muñoz, Denis [South Dakota Sch. Mines Tech.↗

DOE OSTI2021

The HETDEX Instrumentation: Hobby–Eberly Telescope Wide-field Upgrade and VIRUS

The Hobby–Eberly Telescope (HET) Dark Energy Experiment (HETDEX) is undertaking a blind wide-field low-resolution spectroscopic survey of 540 deg 2 of sky to identify and derive redshifts for a million Ly α -emitting galaxies in the redshift range 1.9 < z < 3.5. The ultimate goal is to measure the expansion rate of the universe at this epoch, to sharply constrain cosmological parameters and thus the nature of dark energy. A major multiyear Wide-Field Upgrade (WFU) of the HET was completed in 2016 that substantially increased the field of view to 22' diameter and the pupil to 10 m, by replacing the optical corrector, tracker, and Prime Focus Instrument Package and by developing a new telescope control system. The new, wide-field HET now feeds the Visible Integral-field Replicable Unit Spectrograph (VIRUS), a new low-resolution integral-field spectrograph (LRS2), and the Habitable Zone Planet Finder, a precision near-infrared radial velocity spectrograph. VIRUS consists of 156 identical spectrographs fed by almost 35,000 fibers in 78 integral-field units arrayed at the focus of the upgraded HET. VIRUS operates in a bandpass of 3500–5500 Å with resolving power R ≃ 800. VIRUS is the first example of large-scale replication applied to instrumentation in optical astronomy to achieve spectroscopic surveys of very large areas of sky. This paper presents technical details of the HET WFU and VIRUS, as flowed down from the HETDEX science requirements, along with experience from commissioning this major telescope upgrade and the innovative instrumentation suite for HETDEX.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Beacon-based precision navigation and timing (PNT) system

Beacon-based Precision Navigation and Timing (PNT) may use a constellation of space vehicles (e.g., small, low cost satellites) coupled to a network of ground stations and a network of beacons. Such a system be provided at a cost that is approximately 100 times lower than GPS both to build and to operate. The resulting system may also provide fast acquisition, improved SNR, improved anti-jam and anti-spoofing capabilities, and six-inch scale location determination, making it applicable to both existing PNT applications and enabling new applications.

Judd, Stephen↗

DOE OSTI2021

Realization of a high luminosity muon beam at the Jefferson Lab

The proton is the major component of the visible matter of our universe, so being able to determine its fundamental properties, such as its charge radius, is of vital importance. In recent years, several experiments have been performed for the accurate measurement of the proton radius with different experimental techniques. The main and most common are based on two different techniques: ep scattering and Lamb shift spectroscopy of regular hydrogen atoms. The latter can also be performed on muonic hydrogen atoms with a significant improvement in accuracy. Recent measurements that use this method have highlighted a discrepancy between the results obtained with the diffusion of electrons and those obtained with the spectroscopic technique leading to the so-called ?proton radius puzzle?. The explanation of why this difference between the measured values exists is still a matter of discussion. The last attempt to address the puzzle was the PRad Experiment. It was performed with a unique experimental setup that gave the scientists an excellent control on the systematic errors that are usually present in electron-proton scattering experiments. This has significantly increased the precision of the measurement, bringing it in the same area as the spectroscopic ones done on muonic hydrogen atoms, which are considered the most precise. However, to solve the puzzle once and for all, even more precise electron scattering measurements are needed. Alternatively, new methods can be used, such as eg. muon-proton scattering at low transferred momenta in order to lower the systematic errors that comes with the measurement. This thesis tries to address this problem by studying the set up of an intense muon beam at the Jefferson Laboratory (JLab) that can be used to carry out a high-precision m ? p scattering experiment. Using Montecarlo simulations I studied the muon production resulting from the interaction of the primary electron beam with the beam-dump at JLab Hall-A. The simulations were performed using the FLUKA package via the FLAIR graphical interface. In this study, I modified an existing geometry (built for the ?Beam Dump eXperiment?) and performed several studies in order to optimize the muon beam parameters. In order to estimate the beam intensity, I studied the muon generation and transportation through the concrete bunker surrounding the Hall-A beam-dump. Detailed studies on muon attenuation and dispersion at different depth allowed me to track the beam profile in space and momentum as a function of the distance from the beam-dump. Last, but not least, I studied a possible tagging system for the muon beam. The tagging system will allow us to know with good precision (O(1=1000)) the energy of each muon of the beam. Based on the results obtained, I created an event generator that incorporates the detailed description of the muon beam (energy, position, emittance) useful to define and optimize the experimental setup for a future measurement of the proton radius at the JLab.

Fulci, Antonino↗

DOE OSTI2023

Enhancing Oxygen Stability in Low-Cobalt Layered Oxide Cathode Materials by Three-Dimensional Targeted Doping

In this project, we propose to develop a new concept and a generic platform that can lead to the greatly enhanced stabilization of all high-energy cathode materials, and in particular high-nickel (Ni) and low-cobalt (Co) oxides. The new concept is a 3D doping technology that hierarchically combines surface and bulk doping. We will use surface doping to stabilize the surface of primary particles and also introduce dopants in the bulk to further enhance oxygen stability, conductivity, and structural stability in low-Co oxides under high voltage and deep discharging operating conditions. This new concept not only will deliver a low-cost, high-energy cathode but also will provide a generic method that can stabilize all high-energy cathodes. The proposed novel 3D doping approach is poised to resolve some longstanding challenges in fundamental doping effects on battery materials as well as to reduce Li-ion batteries’ cost and improve their safety, energy density, and lifetime. To tackle this problem, we have formed a highly complementary multi-university/national labs/industry team to enable a doping-central and systematic investigation of low-Co materials and create a knowledge base for many electrode materials to be used in advanced electric vehicles. The successful execution of the proposed project relies on five components that can be carried out by the complementary team members: (1) a theoretical investigation of the surface and bulk stabilizing dopants (Persson), (2) a precise synthesis of materials with targeted doping (Lin and Xin), (3) development of electrolytes for high-Ni low-Co oxides (Xu), (4) multi-scale characterization of the structures and their interfaces by scanning transmission electron microscopy (SEM) and synchrotron X-ray imaging and spectroscopy tools (Xin and Lin), and (5) pouch cell-level integration (Fan). The UCI-led project will enable a doping-central and systematic investigation of low-Co materials and create a knowledge base for many electrode materials to be used in advanced electric vehicles.

25 ENERGY STORAGE↗

DOE OSTI2022

The EBLM project – IX. Five fully convective M-dwarfs, precisely measured with CHEOPS and TESS light curves

ABSTRACT Eclipsing binaries are important benchmark objects to test and calibrate stellar structure and evolution models. This is especially true for binaries with a fully convective M-dwarf component for which direct measurements of these stars’ masses and radii are difficult using other techniques. Within the potential of M-dwarfs to be exoplanet host stars, the accuracy of theoretical predictions of their radius and effective temperature as a function of their mass is an active topic of discussion. Not only the parameters of transiting exoplanets but also the success of future atmospheric characterization relies on accurate theoretical predictions. We present the analysis of five eclipsing binaries with low-mass stellar companions out of a subsample of 23, for which we obtained ultra-high-precision light curves using the CHEOPS satellite. The observation of their primary and secondary eclipses are combined with spectroscopic measurements to precisely model the primary parameters and derive the M-dwarfs mass, radius, surface gravity, and effective temperature estimates using the PYCHEOPS data analysis software. Combining these results to the same set of parameters derived from TESS light curves, we find very good agreement (better than 1 per cent for radius and better than 0.2 per cent for surface gravity). We also analyse the importance of precise orbits from radial velocity measurements and find them to be crucial to derive M-dwarf radii in a regime below 5 per cent accuracy. These results add five valuable data points to the mass–radius diagram of fully convective M-dwarfs.

Sebastian, D. (ORCID:0000000222149258)↗

DOE OSTI2026

Improved Spectral Classification of Local K/M Dwarfs in SDSS Surveys. I. Chemodynamic Validation and Metallicity Calibration

An examination of 109,276 spectra of low-mass stars in the Sloan Digital Sky Survey (SDSS) data archive, collected pre-2010, provides a broad collection of K/M (sub)dwarfs tracing the local (d ≲ 250 pc) population of the thin-disk, thick-disk, and halo, based on 3D kinematics. These populations have distinct metallicities and kinematics, which should be reflected in lower-mass members. One complication is measuring metallicities of M dwarfs from low-resolution spectroscopy or photometry alone remains a challenge, even with the availability of Gaia data. To better characterize physical parameters of low-mass stars observed by SDSS, we define a set of 536 improved, empirical K/M dwarf classification templates to more accurately determine spectral subtypes (K5.5–M8.5) and morphology classes (MCs) (0.5–12.5). We select the best-fit template to every archival SDSS spectrum in the range 5000–8000 Å based on minimum χ 2 value. We then use secondary metallicity estimators to calibrate the most likely [Fe/H] values corresponding to the assigned MC. We confirm that the most metal-rich K/M dwarfs have thin-disk kinematics, and we observe the known effect of Galactic radial metallicity migration, which we confirm is strongly imprinted in the chemodynamics of the local disk M dwarfs. Confirmation of these chemodynamic trends validates the precision of our improved templates for estimating [Fe/H] for M (sub)dwarfs, notably at the low-metallicity end (–3 < [Fe/H] < –1). Substructure in the chemodynamics of the most metal-poor K/M subdwarfs begins to distinguish between local Gaia-Enceladus and local in situ halo objects. This methodology opens the door to use the ubiquitous, local K/M (sub)dwarfs to trace local Galactic chemodynamics with the highest possible resolution.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference

Efficient machine learning implementations optimized for inference in hardware have wide-ranging benefits, depending on the application, from lower inference latency to higher data throughput and reduced energy consumption. Two popular techniques for reducing computation in neural networks are pruning, removing insignificant synapses, and quantization, reducing the precision of the calculations. In this work, we explore the interplay between pruning and quantization during the training of neural networks for ultra low latency applications targeting high energy physics use cases. Techniques developed for this study have potential applications across many other domains. We study various configurations of pruning during quantization-aware training, which we term quantization-aware pruning, and the effect of techniques like regularization, batch normalization, and different pruning schemes on performance, computational complexity, and information content metrics. We find that quantization-aware pruning yields more computationally efficient models than either pruning or quantization alone for our task. Further, quantization-aware pruning typically performs similar to or better in terms of computational efficiency compared to other neural architecture search techniques like Bayesian optimization. Surprisingly, while networks with different training configurations can have similar performance for the benchmark application, the information content in the network can vary significantly, affecting its generalizability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Ultra-low loss visible light waveguides for integrated atomic, molecular, and quantum photonics

Atomic, molecular and optical (AMO) visible light systems are the heart of precision applications including quantum, atomic clocks and precision metrology. As these systems scale in terms of number of lasers, wavelengths, and optical components, their reliability, space occupied, and power consumption will push the limits of using traditional laboratory-scale lasers and optics. Visible light photonic integration is critical to advancing AMO based sciences and applications, yet key performance aspects remain to be addressed, most notably waveguide losses and laser phase noise and stability. Additionally, a visible light integrated solution needs to be wafer-scale CMOS compatible and capable of supporting a wide array of photonic components. While the regime of ultra-low loss has been achieved at telecommunication wavelengths, progress at visible wavelengths has been limited. Here, we report the lowest waveguide losses and highest resonator Qs to date in the visible range, to the best of our knowledge. We report waveguide losses at wavelengths associated with strontium transitions in the 461 nm to 802 nm wavelength range, of 0.01 dB/cm to 0.09 dB/cm and associated intrinsic resonator Q of 60 Million to 9.5 Million, a decrease in loss by factors of 6x to 2x and increase in Q by factors of 10x to 1.5x over this visible wavelength range. Additionally, we measure an absorption limited loss and Q of 0.17 dB/m and 340 million at 674 nm. This level of performance is achieved in a wafer-scale foundry compatible Si 3 N 4 platform with a 20 nm thick core and TEOS-PECVD deposited upper cladding oxide, and enables waveguides for different wavelengths to be fabricated on the same wafer with mask-only changes per wavelength. These results represent a significant step forward in waveguide platforms that operate in the visible, opening up a wide range of integrated applications that utilize atoms, ions and molecules including sensing, navigation, metrology and clocks.

Chauhan, Nitesh↗

DOE OSTI2024

Analysis and Benchmarking of feature reduction for classification under computational constraints

Abstract Machine learning is most often expensive in terms of computational and memory costs due to training with large volumes of data. Current computational limitations of many computing systems motivate us to investigate practical approaches, such as feature selection and reduction, to reduce the time and memory costs while not sacrificing the accuracy of classification algorithms. In this work, we carefully review, analyze, and identify the feature reduction methods that have low costs/overheads in terms of time and memory. Then, we evaluate the identified reduction methods in terms of their impact on the accuracy, precision, time, and memory costs of traditional classification algorithms. Specifically, we focus on the least resource intensive feature reduction methods that are available in Scikit-Learn library. Since our goal is to identify the best performing low-cost reduction methods, we do not consider complex expensive reduction algorithms in this study. In our evaluation, we find that at quadratic-scale feature reduction, the classification algorithms achieve the best trade-off among competitive performance metrics. Results show that the overall training times are reduced 61%, the model sizes are reduced 6×, and accuracy scores increase 25% compared to the baselines on average with quadratic scale reduction.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Selective single-atom adsorption for precision separation of lead ions in tap water via capacitive deionization

Capacitive deionization (CDI) offers a cost-effective and low-energy method for selective removal of Pb 2+ from drinking water. Modifying CDI electrode surfaces with functional groups presents a versatile approach to enhancing selective ion adsorption capacity. However, a comprehensive understanding of the selectivity and removal efficiency of Pb 2+ among diverse functional groups remains unexplored. Here, we investigated the effects of different functional groups (-SH, -COOH, and -NH 2 ) attached to the graphene oxide (GO) electrode surfaces on Pb 2+ selectivity and removal efficiency. Surprisingly, GO-COOH demonstrated single-atom adsorption of Pb 2+ , displaying superior removal efficiency and selectivity compared with -SH and -NH 2 , although -SH possesses significant chelation capability for Pb 2+ . Both density functional theory (DFT) calculations and X-ray pair distribution function (PDF) analyses confirmed that Pb 2+ exhibits a theoretically higher affinity to -COOH. Further, this research deepens our understanding of the interactions between functional groups and heavy metal ions, enabling selective and rapid separation of target cations for water purification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning

Quantifying methane emissions is essential for meeting near-term climate goals and is typically carried out using methane concentrations measured downwind of the source. One major source of methane that is important to observe and promptly remediate is fugitive emissions from oil and gas production sites but installing methane sensors at the thousands of sites within a production basin is expensive. In recent years, relatively inexpensive metal oxide sensors have been used to measure methane concentrations at production sites. Current methods used to calibrate metal oxide sensors have been shown to have significant shortcomings, resulting in limited confidence in methane concentrations generated by these sensors. To address this, we investigate using machine learning (ML) to generate a model that converts metal oxide sensor output to methane mixing ratios. To generate test data, two metal oxide sensors, TGS2600 and TGS2611, were collocated with a trace methane analyzer downwind of controlled methane releases. Over the duration of the measurements, the trace gas analyzer’s average methane mixing ratio was 2.40 ppm with a maximum of 147.6 ppm. The average calculated methane mixing ratios for the TGS2600 and TGS2611 using the ML algorithm were 2.42 ppm and 2.40 ppm, with maximum values of 117.5 ppm and 106.3 ppm, respectively. A comparison of histograms generated using the analyzer and metal oxide sensors mixing ratios shows overlap coefficients of 0.95 and 0.94 for the TGS2600 and TGS2611, respectively. Overall, our results showed there was a good agreement between the ML-derived metal oxide sensors’ mixing ratios and those generated using the more accurate trace gas analyzer. This suggests that the response of lower-cost sensors calibrated using ML could be used to generate mixing ratios with precision and accuracy comparable to higher priced trace methane analyzers. This would improve confidence in low-cost sensors’ response, reduce the cost of sensor deployment, and allow for timely and accurate tracking of methane emissions.

03 NATURAL GAS↗