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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Hot Springs and Geysers: Exploring Historical and Modern Impacts of Geothermal Energy Production on Associated Natural Surface Systems and Standardizing Management Practices

Surface thermal features, most notably hot springs and geysers are increasingly being recognized for their importance to ecosystems, indigenous cultures, and in some cases agriculture, recreation, and tourism. Geothermal project development poses a potential risk to these natural features but current regulatory requirements for assessing and managing these risks during exploration, permitting and monitoring are somewhat inconsistent and unpredictable across different geothermal fields. This has resulted in uncertainty and increases in exploration risk for geothermal energy developers that have led to costly project delays, cancellations, or hesitation to commit. Varying regulatory requirements may also influence public perception, fostering confusion, distrust and ultimately opposition to geothermal projects, further contributing to project delays or cancellations. At a time when there is an increasing urgency for reliable baseload clean energy, geothermal is a net-zero, renewable solution that additionally provides access to more equitable and environmentally just clean power. Continued integration of geothermal energy into the national energy roadmap can be facilitated through consistent and predictable permitting, providing regulators the framework they need, developers a clear path forward, and transparency that the public deserves. This project, currently in its beginning phases, seeks to address this important issue by providing a technical basis from which to build a preliminary protocol for assessing and managing potential impacts from new or existing geothermal energy projects to surface thermal features and their associated ecosystems. Development of this preliminary protocol will be informed by (1) a literature review of well-documented case studies in the western U.S. and New Zealand to understand the range of conditions that exemplify geothermal-surface thermal systems; (2) development of generic illustrative conceptual-numerical models to quantify, understand, and predict the first-order controls (e.g., pressure and permeability) on surface flows; and (3) additional independent and scientifically rigorous evaluations of geothermal-surface thermal system case studies from the Basin and Range Province that incorporate publicly available data as well as data provided by industry through data-sharing agreements. Learning from the successes of the process used to develop the Induced Seismicity Management Protocol (ISMP), we ultimately aim to use these initial efforts as a springboard for establishing a surface thermal feature management working group that will work collaboratively to finalize the protocol as well as co-create recommended best practices for implementation. We envision that the working group will primarily be composed of representatives from regulatory entities, government agencies, Tribes, academia, national laboratories, and industry, and will include early and regular engagement with community organizations and environmental groups. This will help ensure broad acceptance and implementation of the protocol, which will facilitate a more consistent, predictable, and standardized regulatory process, and help to ensure that geothermal energy continues to provide a reliable source of clean energy, and a pathway to achieving greater energy equity in the U.S.

Best Practices↗
DOE OSTI2020

A systematic strategy for estimating hERG block potency and its implications in a new cardiac safety paradigm

Introduction: hERG block potency is widely used to calculate a drug's safety margin against its torsadogenic potential. Previous studies are confounded by use of different patch clamp electrophysiology protocols and a lack of statistical quantification of experimental variability. Since the new cardiac safety paradigm being discussed by the International Council for Harmonisation promotes a tighter integration of nonclinical and clinical data for torsadogenic risk assessment, a more systematic approach to estimate the hERG block potency and safety margin is needed. Methods: A cross-industry study was performed to collect hERG data on 28 drugs with known torsadogenic risk using a standardized experimental protocol. A Bayesian hierarchical modeling (BHM) approach was used to assess the hERG block potency of these drugs by quantifying both the inter-site and intra-site variability. A modeling and simulation study was also done to evaluate protocol-dependent changes in hERG potency estimates. Results: A systematic approach to estimate hERG block potency is established. The impact of choosing a safety margin threshold on torsadogenic risk evaluation is explored based on the posterior distributions of hERG potency estimated by this method. The modeling and simulation results suggest any potency estimate is specific to the protocol used. Discussion: This methodology can estimate hERG block potency specific to a given voltage protocol. The relationship between safety margin thresholds and torsadogenic risk predictivity suggests the threshold should be tailored to each specific context of use, and safety margin evaluation may need to be integrated with other information to form a more comprehensive risk assessment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Ensemble Simulations and Experimental Free Energy Distributions: Evaluation and Characterization of Isoxazole Amides as SMYD3 Inhibitors

Optimization of binding affinities for ligands to their target protein is a primary objective in rational drug discovery. Herein, we report on a collaborative study that evaluates various compounds designed to bind to the SET and MYND domain-containing protein 3 (SMYD3). SMYD3 is a histone methyltransferase and plays an important role in transcriptional regulation in cell proliferation, cell cycle, and human carcinogenesis. Experimental measurements using the scintillation proximity assay show that the distributions of binding free energies from a large number of independent measurements exhibit non-normal properties. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to predict the binding free energies and to provide a detailed chemical insight into the nature of ligand-protein binding. Our results show that the 1-trajectory ESMACS protocol works well for the set of ligands studied here. Although one unexplained outlier exists, we obtain excellent statistical ranking across the set of compounds from the ESMACS protocol and good agreement between calculations and experiments for the relative binding free energies from the TIES protocol. ESMACS and TIES are again found to be powerful protocols for the accurate comparison of the binding free energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Practical Hamiltonian learning with unitary dynamics and Gibbs states

We study the problem of learning the parameters for the Hamiltonian of a quantum many-body system, given limited access to the system. In this work, we build upon recent approaches to Hamiltonian learning via derivative estimation. We propose a protocol that improves the scaling dependence of prior works, particularly with respect to parameters relating to the structure of the Hamiltonian (e.g., its locality k). Furthermore, by deriving exact bounds on the performance of our protocol, we are able to provide a precise numerical prescription for theoretically optimal settings of hyperparameters in our learning protocol, such as the maximum evolution time (when learning with unitary dynamics) or minimum temperature (when learning with Gibbs states). Thanks to these improvements, our protocol has practical scaling for large problems: we demonstrate this with a numerical simulation of our protocol on an 80-qubit system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Traceable random numbers from a non-local quantum advantage

The unpredictability of random numbers is fundamental to both digital security and applications that fairly distribute resources. However, existing random number generators have limitations—the generation processes cannot be fully traced, audited and certified to be unpredictable. The algorithmic steps used in pseudorandom number generators are auditable, but they cannot guarantee that their outputs were a priori unpredictable given knowledge of the initial seed. Device-independent quantum random number generators can ensure that the source of randomness was unknown beforehand, but the steps used to extract the randomness are vulnerable to tampering. Here we demonstrate a fully traceable random number generation protocol based on device-independent techniques. Our protocol extracts randomness from unpredictable non-local quantum correlations, and uses distributed intertwined hash chains to cryptographically trace and verify the extraction process. This protocol forms the basis for a public traceable and certifiable quantum randomness beacon that we have launched. Over the first 40 days of operation, we completed the protocol 7,434 out of 7,454 attempts—a success rate of 99.7%. Each time the protocol succeeded, the beacon emitted a pulse of 512 bits of traceable randomness. The bits are certified to be uniform with error multiplied by actual success probability bounded by 2−64. Further, the generation of certifiable and traceable randomness represents a public service that operates with an entanglement-derived advantage over comparable classical approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Noise-canceling quantum feedback: Non-Hermitian dynamics with applications to state preparation and magic state distillation

Time-continuous quantum measurement allows for the tracking of a quantum system in real time via sequences of short, and individually weak, measurement intervals. Such measurements are necessarily invasive, imparting backaction to the system, and allowing the observer to update their state estimate based on stochastic measurement outcomes. Feedback control then involves real-time interventions by an observer, conditioned on the time-continuous measurement signal that they receive. Here, we consider here diffusive quantum trajectories and focus on the “noise-canceling” subset of feedback protocols that aim to minimize the degree of stochasticity in the dynamics. We derive such a class of feedback operations, showing that under the idealized assumptions of pure states, unit measurement efficiency, and zero time delay in implementing feedback operations, perfectly noise-canceling feedback always exists. We consider the resulting noise-canceled dynamics generated by an effective non-Hermitian Hamiltonian; while non-Hermitian Hamiltonians from continuous monitoring generally describe rare dynamics (accessible by costly postselection), the use of noise-canceling feedback here leads to non-Hermitian dynamics that occur deterministically. We demonstrate this via examples of entangled state preparation and stabilization. We then illustrate the potential for the application of noise cancellation to boost success rates in magic state distillation protocols. We show that adding feedback based on noise cancellation into a time-continuous five-to-one distillation protocol leads to higher probabilities of successful distillation across a range of input errors and increases the threshold on input errors for which the protocol is effective. Our results highlight the efficacy of noise-canceling feedback-aided protocols for quantum state preparation and stabilization tasks.

Karmakar, Tathagata [University of California, Ber↗
DOE OSTI2022

Quantum advantages for Pauli channel estimation

We show that entangled measurements provide an exponential advantage in sample complexity for Pauli channel estimation, which is both a fundamental problem and a practically important subroutine for benchmarking near-term quantum devices. The specific task we consider is to simultaneously learn all the eigenvalues of an n-qubit Pauli channel to ±ε precision. We give an estimation protocol with an n-qubit ancilla that succeeds with high probability using only O(n/ε 2 ) copies of the Pauli channel, while proving that any ancilla-free protocol (possibly with adaptive control and channel concatenation) would need at least Ω(2 n/3 ) rounds of measurement. We further study the advantages provided by a small number of ancillas. For the case that a k-qubit ancilla (k≤n) is available, we obtain a sample complexity lower bound of Ω(2 (n-k)/3 ) for any nonconcatenating protocol, and a stronger lower bound of Ω(n 2n-k ) for any nonadaptive, nonconcatenating protocol, which is shown to be tight. We also show how to apply the ancilla-assisted estimation protocol to a practical quantum benchmarking task in a noise-resilient and sample-efficient manner, given reasonable noise assumptions. Our results provide a practically interesting example for quantum advantages in learning and also bring insights for quantum benchmarking.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Toward improved quantum simulations and sensing with trapped two-dimensional ion crystals via parametric amplification

Improving coherence is a fundamental challenge in quantum simulation and sensing experiments with trapped ions. Here we discuss, experimentally demonstrate, and estimate the potential impacts of two different protocols that enhance, through motional parametric excitation, the coherent spin-motion coupling of ions obtained with a spin-dependent force. The experiments are performed on two-dimensional crystal arrays of approximately 100 9 ⁢Be + ions confined in a Penning trap. By modulating the trapping potential at close to twice the center-of-mass mode frequency, we squeeze the motional mode and enhance the spin-motion coupling while maintaining spin coherence. With a stroboscopic protocol, we measure 5.4 ± 0.9 dB of motional squeezing below the ground-state motion, from which theory predicts a 10-dB enhancement in the sensitivity for measuring small displacements using a recently demonstrated protocol [K. A. Gilmore et al., Science 373, 673 (2021)]. With a continuous squeezing protocol, we measure and accurately calibrate the parametric coupling strength. Theory suggests this protocol can be used to improve quantum spin squeezing, limited in our system by off-resonant light scatter. Finally, we illustrate numerically the trade-offs between strong parametric amplification and motional dephasing in the form of center-of-mass frequency fluctuations for improving quantum spin squeezing in our setup.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Remote Entanglement via Adiabatic Passage Using a Tunably Dissipative Quantum Communication System

Effective quantum communication between remote quantum nodes requires high fidelity quantum state transfer and remote entanglement generation. Recent experiments have demonstrated that microwave photons, as well as phonons, can be used to couple superconducting qubits, with a fidelity limited primarily by loss in the communication channel. Adiabatic protocols can overcome channel loss by transferring quantum states without populating the lossy communication channel. In this work, we present a unique superconducting quantum communication system, comprising two superconducting qubits connected by a 0.73 m-long communication channel. Significantly, we can introduce large tunable loss to the channel, allowing exploration of different entanglement protocols in the presence of dissipation. When set for minimum loss in the channel, we demonstrate an adiabatic quantum state transfer protocol that achieves 99% transfer efficiency as well as the deterministic generation of entangled Bell states with a fidelity of 96%, all without populating the intervening communication channel, and competitive with a qubit-resonant mode-qubit relay method. We also explore the performance of the adiabatic protocol in the presence of significant channel loss, and show that the adiabatic protocol protects against loss in the channel, achieving higher state transfer and entanglement fidelities than the relay method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Quantum Criticality Under Imperfect Teleportation

Entanglement, measurement, and classical communication together enable teleportation of quantum states between distant parties, in principle, with perfect fidelity. To what extent do correlations and entanglement of a many-body wave function transfer under teleportation protocols? We address this question for the case of an imperfectly teleported quantum critical wave function, focusing on the ground state of a critical Ising chain. We demonstrate that imperfections, e.g., in the entangling gate adopted for a given protocol, effectively manifest as weak measurements acting on the otherwise pristinely teleported critical state. Armed with this perspective, we leverage and further develop the theory of measurement-altered quantum criticality to quantify the resilience of critical-state teleportation. We identify classes of teleportation protocols for which imperfection (i) preserves both the universal long-range entanglement and correlations of the original quantum critical state, (ii) weakly modifies these quantities away from their universal values, and (iii) obliterates long-range entanglement altogether while preserving power-law correlations, albeit with a new set of exponents. We also show that mixed states describing the average over a series of sequential imperfect teleportation events retain pristine power-law correlations due to a “built-in” decoding algorithm, though their entanglement structure measured by the negativity depends on errors similarly to individual protocol runs. These results may allow one to design teleportation protocols that optimize against errors—highlighting a potential practical application of measurement-altered criticality. Published by the American Physical Society 2024

Physics↗
DOE OSTI2020

Open-Source Framework for Data Storage and Visualization of Real-Time Experiments

Digital real time simulators (DRTS) are increasingly being used for the evaluation of power hardware and controller hardware in the laboratory prior to field deployment. Although DRTS are capable of simulating large models in real-time, it is challenging to visualize the results of large models without overdrawing or confounding the viewer. This paper provides an open-source framework for users to visualize their DRTS-based hardware-in-the-loop (HIL) experimental results in real-time. This proposed framework can be used by experimental test beds that can push data through an internet protocol based network. The proposed framework includes three main components. First, it includes the DRTS that generates and pushes the data to a relay. Second, it includes an application that serves multiple purposes, from data storage, testing, and translation of the data to a publisher/subscriber protocol. Finally, it includes libraries and applications that can be used to visualize the data by subscribing to the relay. This framework is available in open source, and it is tested using the HIL platform developed for testing advanced distribution management systems.

advanced distribution management systems↗
DOE OSTI2021

Reliable Power Rating of Perovskite PV Modules

As the perovskite technology is ramping up into commercialization, reliable and accurate power rating of large-size perovskite modules becomes a prominent aspect for its future deployment in the PV market. It is known that the performance calibration of perovskite PV devices is very challenging due to its complex dynamic response during a conventional current-voltage (IV) measurement. PV researchers have previously proposed several steady-state performance calibration methods to reliably extract PV efficiencies, but mostly focus on small area research-type cells. In this paper, we emphasize the importance of reliable performance calibration on large-size perovskite modules. Extending the NREL Cell and Module Performance (CMP) group's steady-state performance calibration protocol (i.e., Asymptotic P MAX Scan) for perovskite cells to modules, we justify the necessity of reporting steady-state efficiencies for perovskite cells and discuss the challenges of applying this protocol to modules. We also present our protocol for Maximum Power Point Tracking (MPPT), which is a technique often used for performance calibration of perovskite cells and modules, and show a comparison between MPPT and Asymptotic P MAX . Using MPPT we demonstrate the interplay between metastability and degradation in perovskite modules, and emphasize the necessity to develop preconditioning protocols for stabilizing these devices. Our aim is to promote development of consensus protocols for performance calibration of perovskite modules, and to advance their credible power ratings, which will be beneficial to the growth of perovskite technology in the PV market.

perovskite↗
DOE OSTI2022

Organic matter concentration and composition of experimentally burned open air and muffle furnace vegetation chars across differing burn severity and feedstock types from Pacific Northwest, USA (v4).

This dataset represents results from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and feedstock materials. The dataset provides both solid and dissolved phase bulk concentration and organic matter characterization data from experimentally generated chars. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. This data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), fourteen burn table videos, burn table video metadata and three folders containing (A) data; (B) metadata and protocols; and (C) photos. The folder names and the file name of the data package readme include a version number which will be updated with future iterations of this data package. The data folder includes (1) solid carbon and solid nitrogen; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and total dissolved nitrogen (TN); (3) pH; (4) thermocouple time series temperature; (5) methods codes; (6) installation methods; (7) excitation emissions matrix (EEM) methods information; (8) a folder of excitation emissions matrix (EEM) fluorescence and absorbance spectra in dissolved organic matter and EEMs processing instructions; (9) solid state carbon-13 and solution state phosphorus nuclear magnetic resonance (13-C NMR and 31-P NMR) data and methods; (10) benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (11) FTICR-MS methods; (12) Inductively coupled plasma (ICP) data for total calcium, magnesium, iron, aluminum, potassium, phosphorus, sodium, and sulfur along with sodium hydroxide-ethylenediaminetetraacetic acid (sodium hydroxide-EDTA) extractable calcium, magnesium, iron, aluminum, potassium, phosphorus, and sulfur; (13) a folder of phosphorus, carbon, and nitrogen X-ray absorption near edge structure (P-XANES, N-XANES, C-XANES) data for samples and standards; (14) P-XANES, N-XANES, C-XANES methods; (15) molybdate reactive phosphorus; and (16) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains .txt data files and a subfolder containing instruments for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. The metadata and protocols folder includes (1) international geo-sample number (IGSN) mapping file (2) burn and laboratory metadata; (3) burn protocol; (4) laboratory protocol; (5) vegetation collection metadata; and (6) vegetation collection protocol. The folder contains photos of the solid chars. All files are .csv, .txt, .pdf, .jpg, .jpeg, .R, .ref, or .mp4. The data package was originally published October 2022 (v1). It was updated April 2023 (v2; new data files), September 2023 (v3; new and corrected data files), and September 2024 (v4; new and added/updated files). Metadata files were also updated to reflect these changes. See the change history section in the readme for more details.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Considerations for using Privacy Preserving Machine Learning Techniques for Safeguards

In international nuclear safeguards, the International Atomic Energy Agency (IAEA) is tasked with inspecting and verifying nuclear facilities and their activities. Data analytics and machine learning to support inspections require large amounts of data that nuclear facility operators may consider proprietary or sensitive, so the IAEA may not have full access. Allowing computation over private data without compromising its security therefore has value for safeguards inspections and analysis. Privacy-preserving machine learning (PPML) consists of security-focused techniques that allow data analytics and machine learning algorithms to run on sensitive data without revealing it. This includes ideas like homomorphic encryption (HE), secure multiparty computation (SMPC), and secure enclaves. HE allows algorithms and mathematical operations to be conducted directly on the encrypted data instead of first decrypting it. With SMPC, multiple entities collaboratively compute over distributed data such that no party is able to directly view any others’ original data. Secure enclaves allow computation to take place in a separate and heavily blocked-off section of a CPU. Techniques like these allow for several potential use cases in which the security of data is essential. With SMPC, machine learning models can be trained over the input data from multiple entities, resulting in a model that all users can benefit from without leaking the input data from any particular entity. With SMPC or a zero-knowledge proof (ZKP), an algorithm returning some single answer or truth value can be run on someone else’s data without ever needing to see that data, potentially allowing for verification or proof of some underlying question. HE can allow for outsourcing computation on data to a hostile or untrusted environment. Although most of the research in this field resides within the health and financial domains, tools from PPML may have similar applications in nuclear safeguards. Allowing the IAEA to compute over proprietary information, such as process models and raw sensor data using PPML techniques, provides the baseline for running complex analytics without needing direct unencrypted access to the underlying data, maintaining its privacy. Important limitations to consider for these techniques include the efficiency and level of security required. The security of HE and SMPC come at the cost of speed—the significant amount of overhead means that algorithms implemented in these protocols and encryption schemes are slower than when run on plaintext. Additionally, several important parameters determine what techniques or protocols are used based on the security requirements. SMPC protocols may need to be selected for resistance against a party that attempts to deviate from the protocol to distort the result or gain access to additional information, and a protocol secure against these attacks may further increase the overhead of the algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Systems Engineering Analysis of National Ignition Facility Industrial Controls Systems and Safety Interlock Systems Remote Input/Output Networking Migration from ControlNet to EtherNet/IP

The ControlNet industrial communications protocol and modules used in the Industrial Control System (ICS) and Safety Interlock System (SIS) at the National Ignition Facility (NIF) are no longer necessary and the ICS and SIS would be better served by migrating the communications structure to use EtherNet/Industrial Protocol (IP) and EtherNet bridge modules instead. By the admission of the vendor of ControlNet hardware, Rockwell Automation, in literature by Bill Petro [1], “Moving forward, customers will be able to optimize their asset utilization better using EtherNet/IP protocol than with ControlNet.” The NIF is one of the key elements of the Inertial Confinement Fusion (ICF) program at Lawrence Livermore National Laboratory (LLNL), a federally funded research and development center (FFRDC). The NIF contains the systems and provides the operational capacity to perform ICF, high energy density (HED), and discovery science experiments utilizing 192 individual beamlines, a host of diagnostics, and all the industrial systems required to facilitate these beamlines and diagnostics. The industrial systems are governed by the ICS and SIS, with the ICS providing control and the SIS providing monitoring and permissives. Construction on the NIF began in 1997 and was certified complete in 2009 and, as a result, the ICS and SIS were developed during this time using the tools that were available then. This includes the communications structure and protocols for these systems, much of which was, and still is, ControlNet. ControlNet, particularly during the time that the ICS and SIS were being built, has several attractive features. ControlNet hardware is exclusive to Rockwell Automation, which was the automation hardware chosen for the ICS and SIS. One feature that could be considered an advantage or a disadvantage depending on the communication needs of the system is that ControlNet also utilizes no active network components, excluding repeaters which are not always necessary. According to the architect of the ICS system at the NIF, Gordon Lau, one of the most attractive features of the ControlNet protocol during development of the ICS and SIS was that it is deterministic, providing timing of data transfer that is executed exactly as it is defined by the developer.

42 ENGINEERING↗
DOE OSTI2023

Rapid AI-based Dissection of Ashes using Raman and XRF Spectroscopy (RADAR-X)

Waste-to-energy (WTE) facilities incinerate ~35 million tons of municipal solid waste annually in the United States. The incineration process reduces the mass and the volume of the waste fraction by over 75 and 95%, respectively. The fraction left after incineration remains as ash residues and is referred to as WTE ash, compromising of bottom and fly ash. In the United States, ~10 million tons of WTE ashes are generated annually and predominantly landfilled because of the lack of secondary end-use pathways. This incurs a significant financial burden (landfilling costs) on U.S. WTE facilities and also results in the loss of materials to the landfill. The primary objective of this research is to understand better the elemental and mineralogical composition of WTE ashes from diverse origins and find composition dependent upcycling pathways for diverting these ashes from landfills. This primary objective was addressed through three research tasks –(Task I) An AI-led Multi-Modal Approach for Compositional Analysis, (Task II) Developing a Dissolution-Based Test for Real Time Analysis, and (Task III) Establishing composition-dependent end uses. The chemical composition of WTE ash is dependent on two factors, i.e., the input waste composition and the operational parameters of a WTE facility (combustion conditions). Amongst these two factors, the input waste composition will likely show spatial and temporal variation. As a result, the chemical composition of WTE ash will also fluctuate. To understand the spatial and temporal variation in WTE ash composition, in Task I, we collected 128 ash samples (62 bottom ash and 66 fly ash samples) from 11 WTE facilities located in 11 U.S. states and characterized them via X-ray Fluorescence, powder X-ray Diffraction, and Raman Spectroscopy. The findings from this extensive characterization work indicated that the key elements in WTE fly ashes are Ca, Cl (greater than 10 wt. %), Si, S, K, Zn ( between 1 and 10 wt. %), Mg, Al, P, Ti, Fe, Cu, Br, and Pb (between 0.1 and 1 wt. %). Similarly, the key elements in WTE bottom ash fraction finer than 45μm are Ca (greater than 10 wt. %), Mg, Al, Si, S, Cl, K, Ti, Fe, Zn (between 1 and 10 wt. %), P, V, Cr, Mn, Cu, Br, and Pb (between 0.1 and 1 wt. %). Here, we note that the dominant fraction of WTE bottom ash is the coarse fraction. The coarse WTE bottom ash fraction (rich in silicon) was not characterized in this study because of excessive grinding requirements and their unsuitability as a supplementary cementitious material due to their coarse nature. The elements in WTE bottom ashes are present as calcite, anhydrite, vaterite, hydroxyapatite, quartz, bassanite, gehlenite, akermanite, hydrocalumite, and portlandite. Similarly, the mineralogical species present in WTE fly ashes are calcium chloride hydroxide, halite, calcite, anhydrite, sylvite, hydrocalumite, vaterite, hannebachite, quartz, and bassanite. Temporal variation in ash composition may also result in significant fluctuations in chemical compositions. Therefore, a WTE facility may need to monitor the ash composition (elemental and mineralogical composition) in real time. In Task I, we evaluated the possibility of using a portable X-ray fluorescence (XRF) spectrometer to monitor the elemental composition in real-time. Specifically, we collected XRF data on identical specimens via a portable XRF spectrometer (low-end) and a lab-based benchtop XRF spectrometer (high-end). The collected data was used to train an A.I. algorithm (portable XRF data as an input and benchtop XRF data as an output) to predict accurate elemental composition using portable XRF data. Finally, we developed a 2-minute photobleaching protocol to monitor the mineralogical characteristics of WTE ashes via Raman spectroscopy. Overall, the activities in Task I improved our understanding of ash composition and developed techniques to monitor elemental and mineralogical composition in near real-time. Based on the findings of Task I, we find that WTE ashes exhibit wide variability in mineralogy. For ICP-based elemental analysis, all the mineralogical species in WTE ashes must be brought into solution. This is traditionally accomplished with acid digestion using a combination of multiple acids. However, acid digestion with multiple acids is time-consuming and often fails to ensure complete digestion of the ash matrix. To address this limitation, in Task II, we developed an alkali-fusion-based digestion protocol using a combination of lithium tetraborate, lithium metaborate, and their combinations as possible alkali fluxes for digesting WTE ashes entirely and rapidly. The validity of the developed method was evaluated on two standard ash specimens, i.e., SRM 1633c coal fly ash and BCR-176R incineration fly ash specimen. The findings suggest that the developed protocol can ensure complete digestion of elements such as Al, Ba, Ca, Cr, Cu, Mg, Mn, P, Sr, V, Zn, Be, K, and rare earth elements. The recent changes in the energy market towards renewables and increased metal recycling have resulted in reduced supplies of supplementary cementitious materials (coal fly ash and slag). Therefore, in Task III, we evaluated the possibility of employing WTE ashes as SCMs. As the chemical composition of WTE ashes varies temporally (on an hourly basis), there was also a need to develop tests that can evaluate the suitability of material to act as supplementary cementitious material rapidly, i.e., in a few minutes. Therefore, in Task II, we also developed a rapid test to assess the suitability of a material to act as an SCM in 5 minutes. This represents a significant advance over the state-of-the-art R 3 test, which takes ~144 hours. This test was initially validated on amorphous aluminosilicates, such as calcined clays, and could be extended to evaluate other industrial by-products, such as WTE ashes. In Task III, we evaluated the possibility of employing WTE ashes for two applications, i.e., as an SCM and a lime substitute for clay stabilization. The findings from Task I indicated that WTE ashes are enriched in chlorine and, therefore, cannot be used directly as an SCM due to corrosion-related risks and altered hydration kinetics. Accordingly, we developed an ash treatment protocol to reduce the solubility of chlorine-containing species in WTE ashes. The developed treatment protocol also immobilized lead in certain mineral forms. As a result of the treatment, WTE ashes can be used as SCMs without any corrosion or heavy metal leaching concerns. The second application examined in this study was clay stabilization. WTE ashes are calcium-rich and can be an adequate lime replacement for clay stabilization. Our findings reveal that the sum of the concentrations of Ca(OH) 2 and CaClOH controls the clay stabilization capability of WTE ashes. In summary, in this work, we evaluated the elemental and mineralogical characteristics of U.S. WTE ashes from diverse origins and developed tests to evaluate the chemical characteristics of these ashes in real time through a portable XRF and a benchtop Raman spectrometer. Based on the chemical characteristics of these ashes, we developed an ash treatment process to enable the use of WTE ashes as an SCM and also evaluated the possibility of employing these ashes for clay stabilization. Overall, the findings from this work enables the diversion of WTE ashes from landfills for multiple end-uses, i.e., as an SCM or a lime substitute for clay stabilization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advancing Development of Emissions Detection (Final Report)

This document is the final report to the U.S. Department of Energy (DOE for contract DE-FE0031873) awarded to Colorado State University (CSU). CSU and partners at Harrisburg University of Science and Technology, University of Texas Arlington, and University of Texas at Austin organized several testing rounds to provide knowledge focused on advancing the detection capabilities of emissions monitoring devices. With this funding opportunity the research group began by establishing the Advancing the Development of Emission Detection (ADED) program, with the goal focused on enhancing the accuracy, reliability, and field applicability of methane detection technologies. This effort aimed to address the critical challenges of identifying and quantifying methane emissions while enabling industry stakeholders to meet regulatory compliance and environmental sustainability goals. The program engaged with industry, government, and technology stakeholders to promote adoption and consensus on testing techniques for methane detection solutions. Methane, a potent greenhouse gas, contributes significantly to global warming, and the oil and natural gas (O&G) sector is a primary source of methane emissions. Regulatory measures such as leak detection and repair (LDAR) programs have been implemented to address emissions. However, traditional LDAR approaches, reliant on handheld and component-level measurements, are resource-intensive. To address these limitations and move with evolving regulations, advanced methane technologies are emerging. These solutions include ground-based sensors, mobile systems (e.g., drones, vehicles, and aircraft), and satellite-based platforms. They offer innovative capabilities for autonomous monitoring, larger spatial coverage, and emission quantification using methods such as tracer gas techniques and inverse modeling with Gaussian plume analysis. The ADED program began with creating protocols for methane controlled release (CR) testing these continuous monitoring (CM) and survey technologies that detect and monitor methane emissions at O&G facilities. The protocols were then implemented throughout testing of CM and survey devices at CSU’s Methane Emissions Technology Evaluation Center (METEC) facility from 2021 through 2024. As apart of the protocol, solutions that tested under the ADED program installed their solutions at METEC, documented their system under test, and provided detection reports to the METEC team for analysis. The METEC team would provide the solutions with analyzed reports of their emissions and ground truth data of the releases conducted during their testing session. Under the ADED program, CMs were also tested at O&G facilities for a six week test run of challenge release (ChR) releases. The findings from the ADED program underscore the critical role of collaborative research and innovation in tackling methane emissions, offering a pathway for the oil and gas sector to achieve significant environmental and economic benefits. Results from METEC testing saw improvement of performance and accuracy across all solutions over the extent of the ADED experiments. The results also showed a variance in CM solution performance between CRs and ChRs. That variance pushed the team to further analyze the differences between CR testing environments and field conditions. With the drive from regulations and that variance in field conditions, the ADED team began designing a new CR testing protocol and additions to the METEC testing facility. The METEC team is furthering the progress made through the ADED program with awarded funding from DE-FE0032276. This funding pushes the development of METEC’s addition with new equipment, allowing for an updated facility layout. METEC still facilitates for traditional facilities, with a legacy pad, while expanding an new design based on how O&G infrastructure has Final Report - Contract Number: DE-FE0031873 been changed over the last decade. Throughout the ADED program the team has also been working with international partners to ensure staying in the trend globally. International partners have been essential in moving the new protocol forward to implement into CR testing at the METEC facility in Spring 2025.

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