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DOE OSTI2020

Automated, Unmanned Detection and Quantification of Fugitive Methane Emissions

Compressor stations used to move natural gas are one of the largest sources of fugitive methane emissions in the midstream sector, accounting for approximately 50% of all fugitive emissions (Zimmerle et al., 2015). This problem is most widespread at reciprocating compressors (Subramanian et al., 2015) where faulty seals are a key contributor to methane emissions (Johnson et al., 2015). As such, there is a significant need for a robust technology that could provide an early indication of an unexpected emission. Equally important, the technology needs to be able to account for biogenic versus anthropogenic sources of methane. One means of indirectly making this determination, is to leverage optical technologies that can autonomously pinpoint the source of such leaks. This presentation discusses recent work funded by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), focused on the development of an innovative remote sensing technology that can reliably and autonomously detect fugitive methane emissions in near real-time, using computer vision and deep learning. The technology called the Smart Methane Leak Detection (SLED/M) system was initially developed to monitor facilities such as compressor stations in a stationary, pan-tilt-zoom configuration. The system has recently been adapted to monitor facilities from an unmanned aerial system (UAS). The speed and maneuverability of UAS platforms are attractive to leak detection and repair program operators, but introduce several challenges. Many existing methane detection algorithms rely on mostly static backgrounds becoming unusable with motion. In addition, top-down views of fugitive methane emissions present differently in Optical Gas Imagers (OGI) compared to looking across the plume. Our work has focused on overcoming these challenges, enhancing the operators ability to detect methane emissions, and pinpoint their sources. Another recent adaptation to SLED/M is the ability to quantify methane emissions using passive sensors (OGI, thermal camera), environmental conditions, plume modeling, and deep learning. SLED/M advances the state-of-the-art for methane emission detection and quantification by focusing on three key critical criteria for effective methane emission mitigation: (1) autonomy (no need for a human to be in the loop), (2) high reliability (low false alarm rates), and (3) real-time performance. Results from this work will be presented.

03 NATURAL GAS↗

DOE OSTI2025

Time-resolved x-ray absorption spectroscopy probe in ultrafast surface chemistry

To celebrate the scientific achievement of Jo Stöhr, I present here a personal account of the use of x-ray absorption spectroscopy to probe dynamics on surfaces using x-ray lasers. In particular, I will review the investigation of ultrafast processes in adsorbates on surfaces using an optical pump and an x-ray absorption spectroscopy probe. Here, it is shown that it is possible to gain insight into the effects of electronic excitations in metals on adsorbates as well as laser-induced vibrational motions. Furthermore, the ultrafast optical pump allows the detection of the CO precursor state in the desorption channel, species close to the transition state in CO oxidation, and the transient HCO intermediate during CO hydrogenation on Ru(0001).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Mass dependence of halo baryon fractions from the kinetic Sunyaev–Zeldovich effect

ABSTRACT We detect the kinetic Sunyaev–Zeldovich imprint of peculiar motions of galaxy groups and clusters, using the photometric Dark Energy Spectroscopic Instrument Legacy Surveys together with cosmic microwave background (CMB) maps from the Atacama Cosmology Telescope (ACT). We develop a comprehensive forward model based on the AbacusSummit cosmological simulations: Mock galaxy group catalogues and synthetic kinetic Sunyaev–Zeldovich (kSZ) maps are generated, together with a reconstructed peculiar velocity field that allows for photo-z errors, redshift-space distortions, and survey masks. We investigate possible contamination from the cosmic infrared background (CIB), finding that CIB effects are subdominant to the kSZ signal in the relevant ACT frequency channel. We then predict the kSZ signal expected when stacking CMB temperature maps around groups, taking account of their estimated radial velocities. Comparing the model with observations, we are able to constrain the total baryon fraction within haloes, as well as their internal gas profiles. We find evidence for mass dependence of the halo baryon fraction within the virial radius. The gas fraction in massive groups is consistent with the universal baryon fraction, but low-mass groups ($10^{12.5} \lesssim M\, /\, h^{-1}\, \mathrm{M}_\odot \lesssim 10^{14}$) are depleted to $0.38 \pm 0.11$ times the universal baryon fraction. We find this low virial baryon fraction to be consistent with an extended gas profile, for which the total baryon content reaches the universal value well beyond the virial radius. This conclusion is consistent with previous analyses using X-ray, kSZ, and weak lensing, and plausibly reflects energetic feedback processes from the galaxies in these haloes.

Roper, Finn A [Institute for Astronomy, University↗

DOE OSTI2025

Electro-optic sampling of classical and quantum light

Full characterization of electric-field waveforms in amplitude and phase is achieved across the terahertz to visible spectral range through interaction with an optical pulse shorter than a half-cycle period via the Pockels (linear electro-optic) effect. This technique of electro-optic sampling has become an indispensable tool in various areas, including ultrafast pump-probe, time-domain and frequency-comb spectroscopies, quantum optics, high-harmonic generation, and attosecond science, and holds great promise for further advances. Not only does it enable spectroscopic measurements with record dynamic range and temporal resolution, along with massively parallel real-time spectral data acquisition, but its remarkable sensitivity also allows the detection of vacuum fluctuations, i.e., “zero-point motion” of electric fields, profoundly impacting our understanding of the fundamental laws of nature.

Benea-Chelmus, Ileana-Cristina (ORCID:000000024814↗

DOE OSTI2020

Hydrogen Diffusivity Measurements of YH 1.87 Moderator Material with Incoherent Quasielastic Neutron Scattering

Yttrium hydride is an optimal choice of moderator material for thermal neutron spectrum reactors requiring small core volumes. The Transformation Challenge Reactor (TCR) program at Oak Ridge National Laboratory (ORNL) aims to develop an additively manufactured microreactor core by leveraging recent advances in materials, manufacturing, data analytics, and high-fidelity modeling and simulation. Yttrium hydride was selected as the moderator material for TCR due to its high moderating power, which enables the spatially efficient reactor design and thermal stability that is superior when compared with zirconium hydride. Hydrogen desorption from yttrium hydride is expected at elevated temperatures, posing safety and performance concerns. As a lifetime component in advanced reactors, appropriate strategies to mitigate hydrogen release from yttrium hydride over long-term reactor operation are required. Understanding hydrogen mobility in yttrium hydride provides the scientific basis for developing a hydrogen barrier for hydride moderator and predicting the hydrogen redistribution within the material during various operational conditions. This study investigated the hydrogen motion in YH 1.87 as a function of temperature ranging from 200 to 1,173 K using incoherent quasielastic neutron scattering (IQNS) at the Spallation Neutron Source (SNS). The results are presented and discussed in terms of hydrogen self-diffusion coefficients, activation energy for translational hydrogen motion, and hydrogen jump distances. Based on the IQNS data, YH 1.87 is found to be stable at high temperatures with no translational H motion below 1,023 K within the IQNS detection limits. In the temperature range of 1,073–1,173 K, hydrogen diffusivity in YH 1.87 is $D = 4.57 X 10^{⁻3} [m^2/s] exp (⁻\frac{1.73[eV]}{RT}$). The hydrogen concentration’s dependence on hydrogen diffusivity is also discussed in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Optimal filters for the moving lens effect

We assess the prospects for detecting the moving lens effect using cosmological surveys. The bulk motion of cosmological structure induces a small-scale dipolar temperature anisotropy of the cosmic microwave radiation, centered around halos and oriented along the transverse velocity field. We introduce a set of optimal filters for this signal and forecast that a high significance detection can be made with upcoming experiments. We discuss the prospects for reconstructing the bulk transverse velocity field on large scales using matched filters, finding good agreement with previous work using quadratic estimators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

A Data-Driven Framework for Automated Detection of Aircraft-Generated Signals in Seismic Array Data Using Machine Learning

Abstract Ground motions associated with aircraft overflights can cover a significant portion of the seismic data collected by shallowly emplaced seismometers, such as new nodal and Distributed Acoustic Sensing systems. This article describes the first published framework for automated detection of aircraft on single channel and multichannel seismic data. The seismic data are converted to spectrograms in a sliding time window and classified as aircraft or nonaircraft in each window using a deep convolutional neural network trained with analyst-labeled data. A majority voting scheme is used to convert the output from the sequence of sliding time windows onto a decision time sequence for each channel and to combine the binary classifications on the decision time sequences across multiple channels. Precision, recall, and F-score are used to quantify the detection performance of the algorithm on nodal data using fourfold time-series cross validation. By applying our framework to data from the Sage Brush Flats nodal array in Southern California, we provide a benchmark performance and demonstrate the advantage of using an array of sensors.

Geochemistry & Geophysics↗

DOE OSTI2021

Large Adaptive Optics Survey for Substellar Objects around Young, Nearby, Low-mass Stars with Robo-AO

We present results from the Large Adaptive optics Survey for Substellar Objects, where the goal is to directly image new substellar companions (<70 M {sub Jup}) at wide orbital separations (≳50 au) around young (≲300 Myr), nearby (<100 pc), low-mass (≈0.1–0.8 M{sub ⊙}) stars. We report on 427 young stars imaged in the visible (i') and near-infrared (J or H ) simultaneously with Robo-AO on the Kitt Peak 2.1 m telescope and later the Maunakea University of Hawaii 2.2 m telescope. To undertake the observations, we commissioned a new infrared camera for Robo-AO that uses a low-noise high-speed SAPHIRA avalanche photodiode detector. We detected 121 companion candidates around 111 stars, of which 62 companions are physically associated based on Gaia DR2 parallaxes and proper motions, another 45 require follow-up observations to confirm physical association, and 14 are background objects. The companion separations range from 2 to 1101 au and reach contrast ratios of 7.7 mag in the near-infrared compared to the primary. The majority of confirmed and pending candidates are stellar companions, with ~5 being potentially substellar and requiring follow-up observations for confirmation. We also detected a 43 ± 9 M {sub Jup} and an 81 ± 5 M {sub Jup} companion that were previously reported. We found 34 of our targets have acceleration measurements detected using Hipparcos–Gaia proper motions. Of those, 58{sub -14}{sup +12}% of the 12 stars with imaged companion candidates have significant accelerations (χ{sup 2}>11.8), while only 23{sub -6}{sup +11}% of the remaining 22 stars with no detected companion have significant accelerations. The significance of the acceleration decreases with increasing companion separation. These young accelerating low-mass stars with companions will eventually yield dynamical masses with future orbit monitoring.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment

The occurrence of supercooled liquid water in mixed-phase cloud (MPC) affects their cloud microphysical and radiative properties. The prevalence of MPCs in the mid- and high latitudes translates these effects to significant contributions to Earth’s radiative balance and hydrological cycle. The current study develops and assesses a radar-only, moment-based phase partition technique for the demarcation of supercooled liquid water volumes in arctic, MPC conditions. The study utilizes observations from the Ka band profiling radar, the collocated high spectral resolution lidar, and ambient temperature profiles from radio sounding deployments following a statistical analysis of 5.5 years of data (January 2014–May 2019) from the Atmospheric Radiation Measurement observatory at the North Slope of Alaska. The ice/liquid phase partition occurs via a per-pixel, neighborhood-dependent algorithm based on the premise that the partitioning can be deduced by examining the mean values of locally sampled probability distributions of radar-based observables and then compare those against the means of climatologically derived, per-phase probability distributions. Analyzed radar observables include linear depolarization ratio (LDR), spectral width, and vertical gradients of reflectivity factor and radial velocity corrected for vertical air motion. Results highlight that the optimal supercooled liquid water detection skill levels are realized for the radar variable combination of spectral width and reflectivity vertical gradient, suggesting that radar-based polarimetry, in the absence of full LDR spectra, is not as critical as Doppler capabilities. The cloud phase masking technique is proven particularly reliable when applied to cloud tops with an Equitable Threat Score (ETS) of 65%; the detection of embedded supercooled layers remains much more uncertain (ETS = 27%).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Single-atom heat engine as a sensitive thermal probe

We propose employing a quantum heat engine as a sensitive probe for thermal baths. In particular, we study a single-atom Otto engine operating in an open thermodynamic cycle. Owing to its cyclic nature, the engine is capable of translating small temperature differences between two baths into a macroscopic oscillation in a flywheel. We present analytical and numerical modeling of the quantum dynamics of the engine and estimate it to be capable of detecting temperature differences as small as 2 μK. This sensitivity can be further improved by utilizing quantum resources such as squeezing of the ion motion. The proposed scheme does not require quantum state initialization and is able to detect small temperature differences in a wide range of base temperatures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Microcam: A Low Power and Privacy Preserving Multi-modal Platform for Occupancy Detection (Final Report)

Heating, ventilation, and air conditioning (HVAC) consumes a significant portion of the energy used in buildings. Much of this is wasted energy, used when buildings are either not occupied at all, or occupied well under their maximum design conditions. This project has focused on residential occupancy detection to autonomously control HVAC systems and save energy. Limitations of existing occupancy sensors include one or more of the following: (i) they employ sensors or algorithms that are not able to detect stationary occupants; (ii) they cannot classify the source of the motion (such as a pet); (iii) depending on the camera resolution and employed algorithms, they do not allow for embedded or onboard computation, and require external or cloud-based processing; (iv) many algorithms developed for camera-based systems are sensitive to lighting changes, and thus prone to missed detections or false alarms; (v) Most existing systems depend on adjustment of settings for different scenarios, complicating self-commissioning; (vi) they cannot provide high enough accuracy; (vii) they are costly; (viii) they are not battery-powered, thus limiting ease of use and installation. In this project, Syracuse University and its partner SRI have developed a low-cost, high accuracy, standalone residential occupancy sensing platform, referred to as the MicroCam, to address all of the aforementioned challenges. MicroCam can operate on typical alkaline batteries without relying on the “cloud” or external computing resources, and consists of low-power, Artificial Intelligence (AI)-based, IoT platforms. Each platform has multi-modal sensors and can process motion, audio and video data, and send binary occupancy result to a lead platform. All sensor data is processed locally on platforms, and the only transmitted data is the binary occupancy state. In addition, preliminary work has been done on images wherein occupants are not discernable. Thus, MicroCam is a standalone solution preserving privacy of the occupants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Observation of Undulator Radiation Generated by a Single Electron Circulating in a Storage Ring and Possible Applications

An experimental study into the undulator radiation, generated by a single electron was carried out at the Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab. The individual photons were detected by a Single Photon Avalanche Diode (SPAD) at an average rate of 1 detection per 300 revolutions in the ring. The detection events were continuously recorded by a picosecond event timer for as long as 1 minute at a time. The collected data were used to test if there is any deviation from the classically predicted Poissonian photostatistics. It was motivated by the observation * of sub-Poissonian statistics in a similar experiment. The observation * could be an instrumentation effect related to low detection efficiency and long detector dead time. In our experiment, the detector (SPAD) has a much higher efficiency (65%) and a much lower dead time. In addition, we show that the collected data (recorded detection times) can be used to study the synchrotron motion of a single electron and infer some parameters of the ring. For example, by comparing the results of simulation and measurement for the synchrotron motion we were able to estimate the magnitude of the RF phase jitter.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Discovery of an Ultra-faint Stellar System near the Magellanic Clouds with the DECam Local Volume Exploration Survey

We report the discovery of a new ultra-faint stellar system found near the Magellanic Clouds in the DECam Local Volume Exploration Survey. This new system, DELVE J0155−6815 (DELVE 2), is located at a heliocentric distance of D ⊙ = 71 ± 4 kpc, which places it at a 3D physical separation of 12 ± 3 kpc from the center of the Small Magellanic Cloud and from the center of the Large Magellanic Cloud (LMC). DELVE 2 is identified as a resolved overdensity of old (τ > 13.3 Gyr) and metal-poor ( dex) stars with a projected half-light radius of and an absolute magnitude of . The size and luminosity of DELVE 2 are consistent with both the population of recently discovered ultra-faint globular clusters and the smallest ultra-faint dwarf galaxies. However, its photometrically derived age and metallicity would place it among the oldest and most metal-poor globular clusters in the Magellanic system. In the absence of spectroscopic measurements of the system’s metallicity dispersion and internal kinematics, we are unable to conclusively classify this system at this time. DELVE 2 is detected in Gaia DR2 with a clear proper-motion signal, with multiple blue horizontal-branch stars near the centroid of the system with proper motions consistent with the systemic mean. We measure the system proper motion to be = mas yr−1. We compare the spatial position and proper motion of DELVE 2 with simulations of the accreted satellite population of the LMC and find that it is very likely to be associated with the LMC.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Astrometric Membership Tests for the Zinn–Newell–Gibson UV-bright Stars in Galactic Globular Clusters

In 1972, Zinn, Newell, & Gibson (ZNG) published a list of 156 candidate UV-bright stars they had found in 27 Galactic globular clusters (GCs), based on photographs in the U and V bands. UV-bright stars lie above the horizontal branch (HB) and blueward of the asymptotic giant branch (AGB) and red giant branch in the clusters’ color–magnitude diagrams. They are in rapid evolutionary phases—if they are members and not unrelated bright foreground stars. The ZNG list has inspired numerous follow-up studies, aimed at understanding late stages of stellar evolution. However, the ZNG candidates were presented only in finding charts, and celestial coordinates were not given. Using my own collection of CCD frames in u and V, I have identified all of the ZNG objects, and have assembled their coordinates, parallaxes, and proper motions from the recent Gaia Early Data Release 3 (EDR3). Based on the Gaia astrometry, I have determined which objects are probable cluster members (45% of the sample). For the members, using photometry from EDR3, I have assigned the stars to various evolutionary stages, including luminous post-AGB stars, and stars above the HB. I point out several ZNG stars of special interest that have still, to my knowledge, never been studied in detail. This study is an adjunct to a forthcoming survey of the Galactic GCs in the uBVI photometric system, designed for detection of low-gravity stars with large Balmer discontinuities.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Stress-Induced Structural Transformations in Au Nanocrystals

Nanocrystals can exist in multiply twinned structures like icosahedron or single crystalline structures like cuboctahedron. Transformations between these structures can proceed through diffusion or displacive motion. Experimental studies on nanocrystal structural transformations have focused on high-temperature diffusion-mediated processes. Limited experimental evidence of displacive motion exists. We report structural transformation of 6 nm Au nanocrystals under nonhydrostatic pressure of 7.7 GPa in a diamond anvil cell that is driven by displacive motion. X-ray diffraction and transmission electron microscopy were used to detect the structural transformation from multiply twinned to single crystalline. Single crystalline nanocrystals were recovered after unloading, then quickly reverted to the multiply twinned state after dispersion in toluene. Furthermore, the dynamics of recovery was captured using TEM which showed surface recrystallization and rapid twin boundary motion. Molecular dynamics simulations showed that twin boundaries are unstable due to defects nucleated from the interior of the nanocrystal.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2020

Unraveling intrinsic correlation effects with angle-resolved photoemission spectroscopy

Interaction effects can change materials properties in intriguing ways, and they have, in general, a huge impact on electronic spectra. In particular, satellites in photoemission spectra are pure many-body effects, and their study is of increasing interest in both experiment and theory. However, the intrinsic spectral function is only a part of a measured spectrum, and it is notoriously difficult to extract this information, even for simple metals. Our joint experimental and theoretical study of the prototypical simple metal aluminum demonstrates how intrinsic satellite spectra can be extracted from measured data using angular resolution in photoemission. A nondispersing satellite is detected and explained by electron–electron interactions and the thermal motion of the atoms. Additional nondispersing intensity comes from the inelastic scattering of the outgoing photoelectron. The ideal intrinsic spectral function, instead, has satellites that disperse both in energy and in shape. Theory and the information extracted from experiment describe these features with very good agreement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Phase control of nonlinear Breit-Wheeler pair creation

Electron-positron pair creation occurs throughout the universe in the environments of extreme astrophysical objects, such as pulsar magnetospheres and black hole accretion disks. The difficulty of emulating these environments in the laboratory has motivated the use of ultrahigh-intensity laser pulses for pair creation. Here we show that the phase offset between a laser pulse and its second harmonic can be used to control the relative transverse motion of electrons and positrons created in the nonlinear Breit-Wheeler process. Analytic theory and particle-in-cell simulations of a head-on collision between a two-color laser pulse and electron beam predict that with an appropriate phase offset, the electrons will drift in one direction and the positrons in the other. The resulting current may provide a collective signature of nonlinear Breit-Wheeler, while the spatial separation resulting from the relative motion may facilitate isolation of positrons for subsequent applications or detection. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗