Results for “parameter reduction” — Page 42

DOE OSTI2022

Identification of Critical Material Attributes in Lignin Streams Based on Pseudomonas putida Performance

Variability in chemical composition of corn stover feedstocks has been suggested to play a role in biocatalyst performance during the conversion of lignocellulosic biomass to value-added compounds. In previous studies, we investigated the performance of Pseudomonas putida CJ781 - an engineered bacterium that converts aromatic compounds to muconate - on various lignin streams produced from the deacetylation of corn stover, and we found significant differences on muconate production. To better understand the origin of these differences, we down selected twenty-two compounds from literature - that had previously been detected as extractives in lignin streams - and we analyzed their concentrations in 12 lignin streams generated from different feedstocks. P. putida CJ781 was then cultivated in mock lignin streams supplemented with various concentrations of these compounds. Bacterial growth was tracked in microtiter plates and the performance was measured by comparing maximum growth rates among conditions. At maximum concentrations that may be found in lignin streams, sodium was the material attribute that limited growth rate in a greater extent, with a reduction in growth rate by 8 to 37%, depending on the counter ion, with sodium nitrate being the most inhibitory, followed by sodium acetate, sodium chloride, and sodium sulfate. Ammonium acetate was also found to be inhibitory at average concentrations of ammonium in lignin streams, reducing maximum growth rate by 18%. Overall, the data from this study has allowed to down select critical material attributes in lignin streams and process parameters that significantly affect the performance of P. putida and will be used as input to predictive models that aim to reduce risks attributed to feedstock variability in lignocellulosic biorefineries.

biocatalyst↗

DOE OSTI2025

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴× speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously—previously impossible with conventional tools—while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗

DOE OSTI2023

Biocatalytic Membranes for Carbon Capture and Utilization

Innovative carbon capture technologies that capture CO 2 from large point sources and directly from air are urgently needed to combat the climate crisis. Likewise, corresponding technologies are needed to convert this captured CO 2 into valuable chemical feedstocks and products that replace current fossil-based materials to close the loop in creating viable pathways for a renewable economy. Biocatalytic membranes that combine high reaction rates and enzyme selectivity with modularity, scalability, and membrane compactness show promise for both CO 2 capture and utilization. This review presents a systematic examination of technologies under development for CO 2 capture and utilization that employ both enzymes and membranes. CO 2 capture membranes are categorized by their mode of action as CO 2 separation membranes, including mixed matrix membranes (MMM) and liquid membranes (LM), or as CO 2 gas–liquid membrane contactors (GLMC). Because they selectively catalyze molecular reactions involving CO 2 , the two main classes of enzymes used for enhancing membrane function are carbonic anhydrase (CA) and formate dehydrogenase (FDH). Small organic molecules designed to mimic CA enzyme active sites are also being developed. CO 2 conversion membranes are described according to membrane functionality, the location of enzymes relative to the membrane, which includes different immobilization strategies, and regeneration methods for cofactors. Parameters crucial for the performance of these hybrid systems are discussed with tabulated examples. Progress and challenges are discussed, and perspectives on future research directions are provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

A first principles analysis of potential-dependent structural evolution of active sites in Fe-N-C catalysts

Fe-N-C (iron–nitrogen–carbon) electrocatalysts have emerged as potential alternatives to precious metal-based materials for the oxygen reduction reaction (ORR). However, the structure of these materials under electrochemical conditions is not well understood, and their poor stability in acidic environments poses a formidable challenge for successful adoption in commercial fuel cells. To provide molecular-level insights into these complex phenomena, we combine periodic density functional theory (DFT) calculations, exhaustive treatment of coadsorption effects for ORR reaction intermediates, including O and OH, and comprehensive analysis of solvation stabilization effects to construct voltage-dependent ab initio thermodynamic phase diagrams that describe the in situ structure of the active sites. These structures are further linked to activity and stability descriptors that can be compared with experimental parameters such as the half-wave potential for ORR and the onset potential for carbon corrosion and CO 2 evolution. The results indicate that pyridinic Fe sites at zigzag carbon edges, as well as other edge sites, exhibit high activity for ORR compared to sites in the bulk. However, edges neighboring the active sites are prone to instability via overoxidation and consequent site loss. The results suggest that it could be beneficial to synthesize Fe-N-C catalysts with small sizes and large perimeter edge lengths to enhance ORR activity, while voltage fluctuations should be limited during fuel cell operation to prevent carbon corrosion of overoxidized edges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Carrier Mobility Modulation in Cu 2 Se Composites Using Coherent Cu 4 TiSe 4 Inclusions Leads to Enhanced Thermoelectric Performance

Carrier transport engineering in bulk semiconductors using inclusion phases often results in the deterioration of carrier mobility (μ) owing to enhanced carrier scattering at phase boundaries. Here, we show by leveraging the temperature-induced structural transition between the α-Cu 2 Se and β-Cu 2 Se polymorphs that the incorporation of Cu 4 TiSe 4 inclusions within the Cu 2 Se matrix results in a gradual large drop in the carrier mobility at temperatures below 400 K (α-Cu 2 Se), whereas the carrier mobility remains unchanged at higher temperatures, where the β-Cu 2 Se polymorph dominates. The sharp discrepancy in the electronic transport within the α-Cu 2 Se and β-Cu 2 Se matrices is associated with the formation of incoherent α-Cu 2 Se/Cu 4 TiSe 4 interfaces, owing to the difference in their atomic structures and lattice parameters, which results in enhanced carrier scattering. In contrast, the similarity of the Se sublattices between β-Cu 2 Se and Cu 4 TiSe 4 gives rise to coherent phase boundaries and good band alignment, which promote carrier transport across the interfaces. Interestingly, the different cation arrangements in Cu 4 TiSe 4 and β-Cu 2 Se contribute to enhanced phonon scattering at the interfaces, which leads to a reduction in the lattice thermal conductivity. The large reduction in the total thermal conductivity while preserving the high power factor of β-Cu 2 Se in the (1–x)Cu 2 Se/(x)Cu 4 TiSe 4 composites results in an improved ZT of 1.2 at 850 K, with an average ZT of 0.84 (500–850 K) for the composite with x = 0.01. Furthermore, this work highlights the importance of structural similarity between the matrix and inclusions when designing thermoelectric materials with improved energy conversion efficiency.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Lossy Compression: An Online Multi-Stage Technology for High-Fidelity Synchro- Waveform Measurements

Effective real-time monitoring and analysis of distributed grids necessitate the use of synchro-waveform measurements, which capture almost all high-frequency disturbances and transient phenomena. However, due to limitations in high-speed measurements and network bandwidth, it is challenging to transfer all high-fidelity synchro-waveforms losslessly and successfully. To cope with these challenges, a hybrid-based online multi-stage compression algorithm is proposed to significantly improve the compression efficiency for synchro-waveform measurements. Initially, the multiple discrete Wavelet transformation is deployed to deconstruct the waveform components. The delta encoding is further developed to decrease the magnitude. In conjunction with the Lempel-Ziv-Markov chain, the hybrid compression algorithm is implemented to achieve real-time compression for the synchro-waveform measurements. Moreover, an innovative error index that synergizes the time and frequency domain error and correlation is formulated to evaluate the waveform distortion. By integrating compression ratio, suitable parameters can be optimally selected. Finally, the simulation, laboratory experiments, as well as field tests across a spectrum of sampling frequencies and time intervals are conducted to substantiate the efficacy of the proposed method. Here, the outcomes demonstrated that a compression ratio of approximately 15.5 and 17.83 can be reached for 0.5 s and 1 s data under both offline and online scenarios, which equates to a substantial 93.5% to 94.39% reduction in data storage requirements.

High-fidelity synchro-waveform measurements↗

DOE OSTI2023

Stomatal behaviour moderates the water cost of CO 2 acquisition for 21 boreal and temperate species under experimental climate change

Abstract The linkage of stomatal behaviour with photosynthesis is critical to understanding water and carbon cycles under global change. The relationship of stomatal conductance (g s ) and CO 2 assimilation (A net ) across a range of environmental contexts, as represented in the model parameter (g 1 ), has served as a proxy of the marginal water cost of carbon acquisition. We useg 1 to assess species differences in stomatal behaviour to a decade of open‐air experimental climate change manipulations, asking whether generalisable patterns exist across species and climate contexts.A net ‐g s measurements (17 727) for 21 boreal and temperate tree species under ambient and +3.3°C warming, and ambient and ~40% summer rainfall reduction, provided >2700 estimates ofg 1 . Warming and/or reduced rainfall treatments both loweredg 1 because those treatments resulted in lower soil moisture and because stomatal behaviour changed more in warming when soil moisture was low. Species tended to respond similarly, although, in species from warmer and drier habitats, g 1 tended to be slightly higher and to be the least sensitive to the decrease in soil water. Overall, both warming and rainfall reduction consistently made stomatal behaviour more conservative in terms of water loss per unit carbon gain across 21 species and a decade of experimental observation.

Plant Sciences↗

DOE OSTI2024

Process damping identification using Bayesian learning and time domain simulation

Process damping can provide improved machining productivity by increasing the stability limit at low spindle speeds. However, existing methods for identifying process damping models experimentally require specialized setups and/or multiple cutting tests. While the phenomenon is well known, the modeling challenges limit pre-process parameter selection that leverages the potential increases in material removal rates. This paper proposes a physics-informed Bayesian method that can identify the cutting force and process damping models from a limited set of test cuts without requiring direct measurements of cutting force or vibration. The method uses time domain simulation to incorporate process damping and provide a basis for test selection. Here, new strategies for efficient sampling and dimensionality reduction are applied to lower computation time and minimize the effect of model error. The proposed method is demonstrated and the identified cutting and damping force coefficients are compared to values obtained using machining tests and least-squares fitting.

42 ENGINEERING↗

DOE OSTI2024

Microwave-assisted catalytic gasification of mixed plastics and corn stover for low tar, hydrogen-rich syngas production

The challenge for efficient management of post-consumer plastic and biomass waste has grown over the past few decades due to their dramatic increases. In comparison to conventional gasification, microwave-assisted co-gasification of plastics and corn stover offers many benefits, including increased H 2 yield and gas components compared to unfavorable char/tar. Nonetheless, for future commercialization of the process and ease of product separation, further reduction of the undesirable tar is necessary, which can be achieved over the catalytic route. Here, in this work, we studied the catalytic effect of magnetite for microwave-assisted co-gasification of corn stover and plastic to make syngas with higher H 2 and lower tar selectivity over non-catalytic conditions. A 1:1:1 ratio of plastic-corn stover-magnetite was used to evaluate the reaction parameters such as temperature, space velocity, heating media, and catalytic cycles under gasification conditions. In comparison with the microwave non-catalytic route, a 100% increase in the total H 2 yield with 76% higher H 2 production efficiency (mmol/kWh) was achieved in the presence of the magnetite catalyst, while reducing the overall tar formation from 9% to 2%. When magnetite was reduced in situ during the reaction, it coupled with microwave and delivered oxygen radicals that cracked down plastic and corn stover intermediates generated from the synergistic effect under microwave heating. Soon after the oxygen transfer process initiated, magnetite reached its final oxidation state consisting of microwave-active Fe and Fe 3 C phases that continued coupling with microwaves along with the generated graphitic carbon to maintain the heat necessary to further reduce the generated tar and make additional gaseous products, as confirmed by XRD, Raman, and TGA analyses.

08 HYDROGEN↗

DOE OSTI2024

In-Situ Bioleaching of Manganese by Dissimilatory Reduction

This report describes the development of a biological leaching process for recovery of manganese from low-grade ores, with a high degree of selectivity against contaminants such as iron. This results in the production of manganese that is suitable for battery manufacture and other electrical applications. The leaching process makes use of a community of metal reducing organisms that solubilize manganese at a pH of approximately 4.5. These organisms are nourished by simple organic molecules such as acetate that are generated by decomposition of biomass. A series of long-term laboratory experiments were carried out to determine the necessary operating parameters, followed by construction of a small pilot plant processing approximately 100 kg of ore. This pilot unit was operated for two years, demonstrating the ability to consistently produce high-grade manganese at a commercially viable rate.

25 ENERGY STORAGE↗

DOE OSTI2025

Structural evolution and magnetic hardness of (Sm,Zr)(Fe,Co,Ti) 12 alloy particles via reduction-diffusion

The quest for achieving high coercivity in Sm(Fe,Co,Ti) 12 alloys, despite their inherent strong magnetocrystalline anisotropy, has posed significant challenges. Recently, (Sm,Zr)(Fe,Co,Ti) 12 monocrystalline particles have exhibited coercivity μ 0 H c > 1.2 T, showcasing promising prospects and significant potential for both manufacturing and research endeavors. This study delves into the structural evolution of (Sm,Zr)(Fe,Co,Ti) 12 (1:12) alloy particles made via the calciothermic reduction-diffusion synthesis process as influenced by the molar ratios of Ca atoms to O 2- ions (Ca/O), annealing time and annealing temperature. Critical insight that informs conditions to optimize the magnetic response is gained via systematic experimentation and advanced electron microscopy. Complex structural features, including core-shell morphologies and intricate multiphase compositions within individual particles, are unveiled. An optimal Ca/O ratio of 1.30 produces particles with a coercivity up to μ 0 H c = 1.63 T, while higher Ca/O ratios induce the formation of a Sm-rich TbCu 7 -type (1: 7 ) phase, which only partially transforms into the desired 1:12 phase during annealing. Persistent remnants of the 1:7 phase locally impact atomic structure, particle morphology, and coercivity. Furthermore, these findings underscore the complex interplay between synthesis parameters, resulting structures, and magnetic properties, informing the design and optimization of high-performance permanent magnets comprised of the (1:12) compound.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Enhancing Sterile Neutrino Oscillation Sensitivities using SBND-PRISM at the Short-Baseline Neutrino Programme

The Short-Baseline Neutrino (SBN) Programme at Fermilab is comprised of two detectors, SBND and ICARUS, placed at $110$\,m and $600$\,m along the Booster Neutrino Beam at Fermilab. The key physics aim of the programme is to definitively test the sterile neutrino hypothesis, a proposed fourth flavour of neutrino that may explain certain experimental anomalies seen regarding standard model neutrino oscillations. To be able to detect the existence of sterile neutrinos, the uncertainties of the programme must be well constrained. To enable this, a robust analysis must be constructed that can consistently identify the correct values of systematic parameters and generate accurate predictions of what the neutrino energy spectrum at ICARUS should look like. SBND's design allows for the introduction of a technique called PRISM. In PRISM, the detector is divided into regions of different off axis angles from the beam, forming different samples where systematics impact each one in a distinct way. This allows any fits performed to obtain a better understanding of the correct value of the systematic parameters. The first analysis included in this thesis focuses on the improvements seen to the sensitivity of SBN to sterile oscillation parameters when using a PRISM configuration instead of treating SBND as a single whole. Focusing on the $5\sigma$ exclusion contour from the $\numu$ disappearance channel using three PRISM samples, an improvement on the order of $30$\,\% is seen, extending the parameter space for which the null hypothesis can be excluded. This thesis also presents a series of mock data studies comparing the abilities of SBND and PRISM analyses, concluding that in the case of simple changes between Monte Carlo (MC) and data, PRISM produces predictions of the ICARUS event rate spectrum that are more accurate and have smaller uncertainties. When moving to more realistic mock data, using different models to create the mock data than were used for the MC, the postfit predictions at ICARUS had a smaller difference between the postfit and mock data reconstructed energy spectra across all mock data samples tested. Finally, a covariance matrix defined by the maximum discrepancy between the postfit and mock data spectra at ICARUS from each of the SBND and PRISM fits across all the samples was constructed. The resultant $1\sigma$ fractional error induced by this bias systematic on the postfit spectrum has a smaller magnitude for PRISM than SBND, with the improvements ranging from $2.21$\,\% to $6.26$\,\% depending on the mock data samples. This summarises the reduction in systematic error when using PRISM instead of treating SBND as a single detector. *************************************** AUTHOR = Slater, Bethany University of Liverpool b.slater2@liverpool.ac.uk TITLE = Enhancing Sterile Neutrino Oscillation Sensitivities using SBND-PRISM at the Short-Baseline Neutrino Programme PAGES = 218 NOTE = Ph.D. University of Liverpool March 2026 ABSTRACT = The Short-Baseline Neutrino (SBN) Programme at Fermilab is comprised of two detectors, SBND and ICARUS, placed at $110$\,m and $600$\,m along the Booster Neutrino Beam at Fermilab. The key physics aim of the programme is to definitively test the sterile neutrino hypothesis, a proposed fourth flavour of neutrino that may explain certain experimental anomalies seen regarding standard model neutrino oscillations. To be able to detect the existence of sterile neutrinos, the uncertainties of the programme must be well constrained. To enable this, a robust analysis must be constructed that can consistently identify the correct values of systematic parameters and generate accurate predictions of what the neutrino energy spectrum at ICARUS should look like. SBND's design allows for the introduction of a technique called PRISM. In PRISM, the detector is divided into regions of different off axis angles from the beam, forming different samples where systematics impact each one in a distinct way. This allows any fits performed to obtain a better understanding of the correct value of the systematic parameters. The first analysis included in this thesis focuses on the improvements seen to the sensitivity of SBN to sterile oscillation parameters when using a PRISM configuration instead of treating SBND as a single whole. Focusing on the $5\sigma$ exclusion contour from the $\numu$ disappearance channel using three PRISM samples, an improvement on the order of $30$\,\% is seen, extending the parameter space for which the null hypothesis can be excluded. This thesis also presents a series of mock data studies comparing the abilities of SBND and PRISM analyses, concluding that in the case of simple changes between Monte Carlo (MC) and data, PRISM produces predictions of the ICARUS event rate spectrum that are more accurate and have smaller uncertainties. When moving to more realistic mock data, using different models to create the mock data than were used for the MC, the postfit predictions at ICARUS had a smaller difference between the postfit and mock data reconstructed energy spectra across all mock data samples tested. Finally, a covariance matrix defined by the maximum discrepancy between the postfit and mock data spectra at ICARUS from each of the SBND and PRISM fits across all the samples was constructed. The resultant $1\sigma$ fractional error induced by this bias systematic on the postfit spectrum has a smaller magnitude for PRISM than SBND, with the improvements ranging from $2.21$\,\% to $6.26$\,\% depending on the mock data samples. This summarises the reduction in systematic error when using PRISM instead of treating SBND as a single detector.

Slater, Bethany [Liverpool U.]↗

DOE OSTI2026

Enhancing Sterile Neutrino Oscillation Sensitivities using SBND-PRISM at the Short-Baseline Neutrino Programme

The Short-Baseline Neutrino (SBN) Programme at Fermilab is comprised of two detectors, SBND and ICARUS, placed at $110$\,m and $600$\,m along the Booster Neutrino Beam at Fermilab. The key physics aim of the programme is to definitively test the sterile neutrino hypothesis, a proposed fourth flavour of neutrino that may explain certain experimental anomalies seen regarding standard model neutrino oscillations. To be able to detect the existence of sterile neutrinos, the uncertainties of the programme must be well constrained. To enable this, a robust analysis must be constructed that can consistently identify the correct values of systematic parameters and generate accurate predictions of what the neutrino energy spectrum at ICARUS should look like. SBND's design allows for the introduction of a technique called PRISM. In PRISM, the detector is divided into regions of different off axis angles from the beam, forming different samples where systematics impact each one in a distinct way. This allows any fits performed to obtain a better understanding of the correct value of the systematic parameters. The first analysis included in this thesis focuses on the improvements seen to the sensitivity of SBN to sterile oscillation parameters when using a PRISM configuration instead of treating SBND as a single whole. Focusing on the $5\sigma$ exclusion contour from the $\numu$ disappearance channel using three PRISM samples, an improvement on the order of $30$\,\% is seen, extending the parameter space for which the null hypothesis can be excluded. This thesis also presents a series of mock data studies comparing the abilities of SBND and PRISM analyses, concluding that in the case of simple changes between Monte Carlo (MC) and data, PRISM produces predictions of the ICARUS event rate spectrum that are more accurate and have smaller uncertainties. When moving to more realistic mock data, using different models to create the mock data than were used for the MC, the postfit predictions at ICARUS had a smaller difference between the postfit and mock data reconstructed energy spectra across all mock data samples tested. Finally, a covariance matrix defined by the maximum discrepancy between the postfit and mock data spectra at ICARUS from each of the SBND and PRISM fits across all the samples was constructed. The resultant $1\sigma$ fractional error induced by this bias systematic on the postfit spectrum has a smaller magnitude for PRISM than SBND, with the improvements ranging from $2.21$\,\% to $6.26$\,\% depending on the mock data samples. This summarises the reduction in systematic error when using PRISM instead of treating SBND as a single detector. *************************************** AUTHOR = Slater, Bethany University of Liverpool b.slater2@liverpool.ac.uk TITLE = Enhancing Sterile Neutrino Oscillation Sensitivities using SBND-PRISM at the Short-Baseline Neutrino Programme PAGES = 218 NOTE = Ph.D. University of Liverpool March 2026 ABSTRACT = The Short-Baseline Neutrino (SBN) Programme at Fermilab is comprised of two detectors, SBND and ICARUS, placed at $110$\,m and $600$\,m along the Booster Neutrino Beam at Fermilab. The key physics aim of the programme is to definitively test the sterile neutrino hypothesis, a proposed fourth flavour of neutrino that may explain certain experimental anomalies seen regarding standard model neutrino oscillations. To be able to detect the existence of sterile neutrinos, the uncertainties of the programme must be well constrained. To enable this, a robust analysis must be constructed that can consistently identify the correct values of systematic parameters and generate accurate predictions of what the neutrino energy spectrum at ICARUS should look like. SBND's design allows for the introduction of a technique called PRISM. In PRISM, the detector is divided into regions of different off axis angles from the beam, forming different samples where systematics impact each one in a distinct way. This allows any fits performed to obtain a better understanding of the correct value of the systematic parameters. The first analysis included in this thesis focuses on the improvements seen to the sensitivity of SBN to sterile oscillation parameters when using a PRISM configuration instead of treating SBND as a single whole. Focusing on the $5\sigma$ exclusion contour from the $\numu$ disappearance channel using three PRISM samples, an improvement on the order of $30$\,\% is seen, extending the parameter space for which the null hypothesis can be excluded. This thesis also presents a series of mock data studies comparing the abilities of SBND and PRISM analyses, concluding that in the case of simple changes between Monte Carlo (MC) and data, PRISM produces predictions of the ICARUS event rate spectrum that are more accurate and have smaller uncertainties. When moving to more realistic mock data, using different models to create the mock data than were used for the MC, the postfit predictions at ICARUS had a smaller difference between the postfit and mock data reconstructed energy spectra across all mock data samples tested. Finally, a covariance matrix defined by the maximum discrepancy between the postfit and mock data spectra at ICARUS from each of the SBND and PRISM fits across all the samples was constructed. The resultant $1\sigma$ fractional error induced by this bias systematic on the postfit spectrum has a smaller magnitude for PRISM than SBND, with the improvements ranging from $2.21$\,\% to $6.26$\,\% depending on the mock data samples. This summarises the reduction in systematic error when using PRISM instead of treating SBND as a single detector.

Slater, Bethany [Liverpool U.]↗

DOE OSTI2026

Enhancing Sterile Neutrino Oscillation Sensitivities using SBND-PRISM at the Short-Baseline Neutrino Programme

The Short-Baseline Neutrino (SBN) Programme at Fermilab is comprised of two detectors, SBND and ICARUS, placed at $110$\,m and $600$\,m along the Booster Neutrino Beam at Fermilab. The key physics aim of the programme is to definitively test the sterile neutrino hypothesis, a proposed fourth flavour of neutrino that may explain certain experimental anomalies seen regarding standard model neutrino oscillations. To be able to detect the existence of sterile neutrinos, the uncertainties of the programme must be well constrained. To enable this, a robust analysis must be constructed that can consistently identify the correct values of systematic parameters and generate accurate predictions of what the neutrino energy spectrum at ICARUS should look like. SBND's design allows for the introduction of a technique called PRISM. In PRISM, the detector is divided into regions of different off axis angles from the beam, forming different samples where systematics impact each one in a distinct way. This allows any fits performed to obtain a better understanding of the correct value of the systematic parameters. The first analysis included in this thesis focuses on the improvements seen to the sensitivity of SBN to sterile oscillation parameters when using a PRISM configuration instead of treating SBND as a single whole. Focusing on the $5\sigma$ exclusion contour from the $\numu$ disappearance channel using three PRISM samples, an improvement on the order of $30$\,\% is seen, extending the parameter space for which the null hypothesis can be excluded. This thesis also presents a series of mock data studies comparing the abilities of SBND and PRISM analyses, concluding that in the case of simple changes between Monte Carlo (MC) and data, PRISM produces predictions of the ICARUS event rate spectrum that are more accurate and have smaller uncertainties. When moving to more realistic mock data, using different models to create the mock data than were used for the MC, the postfit predictions at ICARUS had a smaller difference between the postfit and mock data reconstructed energy spectra across all mock data samples tested. Finally, a covariance matrix defined by the maximum discrepancy between the postfit and mock data spectra at ICARUS from each of the SBND and PRISM fits across all the samples was constructed. The resultant $1\sigma$ fractional error induced by this bias systematic on the postfit spectrum has a smaller magnitude for PRISM than SBND, with the improvements ranging from $2.21$\,\% to $6.26$\,\% depending on the mock data samples. This summarises the reduction in systematic error when using PRISM instead of treating SBND as a single detector. *************************************** AUTHOR = Slater, Bethany University of Liverpool b.slater2@liverpool.ac.uk TITLE = Enhancing Sterile Neutrino Oscillation Sensitivities using SBND-PRISM at the Short-Baseline Neutrino Programme PAGES = 218 NOTE = Ph.D. University of Liverpool March 2026 ABSTRACT = The Short-Baseline Neutrino (SBN) Programme at Fermilab is comprised of two detectors, SBND and ICARUS, placed at $110$\,m and $600$\,m along the Booster Neutrino Beam at Fermilab. The key physics aim of the programme is to definitively test the sterile neutrino hypothesis, a proposed fourth flavour of neutrino that may explain certain experimental anomalies seen regarding standard model neutrino oscillations. To be able to detect the existence of sterile neutrinos, the uncertainties of the programme must be well constrained. To enable this, a robust analysis must be constructed that can consistently identify the correct values of systematic parameters and generate accurate predictions of what the neutrino energy spectrum at ICARUS should look like. SBND's design allows for the introduction of a technique called PRISM. In PRISM, the detector is divided into regions of different off axis angles from the beam, forming different samples where systematics impact each one in a distinct way. This allows any fits performed to obtain a better understanding of the correct value of the systematic parameters. The first analysis included in this thesis focuses on the improvements seen to the sensitivity of SBN to sterile oscillation parameters when using a PRISM configuration instead of treating SBND as a single whole. Focusing on the $5\sigma$ exclusion contour from the $\numu$ disappearance channel using three PRISM samples, an improvement on the order of $30$\,\% is seen, extending the parameter space for which the null hypothesis can be excluded. This thesis also presents a series of mock data studies comparing the abilities of SBND and PRISM analyses, concluding that in the case of simple changes between Monte Carlo (MC) and data, PRISM produces predictions of the ICARUS event rate spectrum that are more accurate and have smaller uncertainties. When moving to more realistic mock data, using different models to create the mock data than were used for the MC, the postfit predictions at ICARUS had a smaller difference between the postfit and mock data reconstructed energy spectra across all mock data samples tested. Finally, a covariance matrix defined by the maximum discrepancy between the postfit and mock data spectra at ICARUS from each of the SBND and PRISM fits across all the samples was constructed. The resultant $1\sigma$ fractional error induced by this bias systematic on the postfit spectrum has a smaller magnitude for PRISM than SBND, with the improvements ranging from $2.21$\,\% to $6.26$\,\% depending on the mock data samples. This summarises the reduction in systematic error when using PRISM instead of treating SBND as a single detector.

Slater, Bethany [Liverpool U.]↗

DOE OSTI2023

An uncertainty-aware strategy for plasma mechanism reduction with directed weighted graphs

In this work, we present a framework for the analysis and reduction of plasma mechanisms by means of weighted directed graphs, in which reactions and species are both treated as nodes. The methodology consists of two distinct analyses. The first, which is qualitative, relies on graph spatializations via force-directed algorithms to discover the predominant global patterns in the chemical model. The second ranks the reactions based on their shortest paths' lengths from/to the species of interest and their relative contributions to the power balance. Further, this quantitative investigation enables a strategy for mechanism reduction that is fully automatized, as it does not require any expert knowledge, highly effective, as it generates reduced mechanisms that are highly accurate while relying on a small number of processes, and easily interpretable, as the algorithm justifies the importance of the retained reactions by outputting their related chemical pathways. Additionally, the work proposes a methodology extension that employs ensembles of graphs to improve the robustness of the reduced mechanism to reaction parameter uncertainties. The approach, here tested for steady-state predictions of a plasma system characterizing negative hydrogen ion sources, is general and can be used in a wide variety of applications outside the particular nuclear fusion context demonstrated in this work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments

Included are results from shear reactivation experiments on laboratory faults pre-loaded close to failure and reactivated by the injection of fluid into the fault. The sample comprises a single-inclined-fracture (SIF) transecting a cylindrical sample of Westerly granite. All experiments are conducted at ambient temperature and follow a similar protocol: (i) application of confining stresses (3MPa) on the fault fully saturated with DI water, (ii) shear-mobilization through the increase of axial loading at a constant displacement rate until a post-peak steady-state condition is reached, (iii) reduction of axial loading and related shear stress to a prescribed fraction of the peak steady-state frictional strength (typically 60% to 90%, representing intermediate to high magnitudes) and (iv), fault reactivation triggered by a stepwise increase of pore pressure on the fault in 0.1 MPa increments held constant for 1-5 minutes. Mechanical data from three ISCO pumps connected to a Temco pressure vessel measure axial, confining, and fault-related parameters, including fluid pressure (kPa), fluid flow rate (mL/min), and axial displacement (mm). See included code for initial data analysis and visualization for select experiments. Resource names represent experiment numbers found in the "Read Me" file, which describes each experimental setup and parameters.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Bayes goes fast: Uncertainty quantification for a covariant energy density functional emulated by the reduced basis method

A covariant energy density functional is calibrated using a principled Bayesian statistical framework informed by experimental binding energies and charge radii of several magic and semi-magic nuclei. The Bayesian sampling required for the calibration is enabled by the emulation of the high-fidelity model through the implementation of a reduced basis method (RBM)—a set of dimensionality reduction techniques that can speed up demanding calculations involving partial differential equations by several orders of magnitude. The RBM emulator we build—using only 100 evaluations of the high-fidelity model—is able to accurately reproduce the model calculations in tens of milliseconds on a personal computer, an increase in speed of nearly a factor of 3,300 when compared to the original solver. Besides the analysis of the posterior distribution of parameters, we present model calculations for masses and radii with properly estimated uncertainties. We also analyze the model correlation between the slope of the symmetry energy L and the neutron skin of 48 Ca and 208 Pb. The straightforward implementation and outstanding performance of the RBM makes it an ideal tool for assisting the nuclear theory community in providing reliable estimates with properly quantified uncertainties of physical observables. Such uncertainty quantification tools will become essential given the expected abundance of data from the recently inaugurated and future experimental and observational facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Development of prechamber enabled mixing-controlled combustion strategy for ultra-low methane emissions from lean burn natural gas engines

This numerical study explores the optimization of Prechamber Enabled Mixing-Controlled Combustion (PC-MCC) using natural gas in heavy-duty engines, aiming to enhance combustion efficiency to minimize methane slip and NOx emissions. The approach involves a prechamber ignition system, distinct from conventional spark ignition (SI) systems, to initiate combustion of direct injected natural gas. By leveraging the robust ignition characteristics of the prechamber, the PC-MCC method demonstrates significant potential in achieving efficient combustion akin to diesel engines but with lower greenhouse gas emissions. The research evaluates the effects of various geometric and operational parameters on the combustion process and emissions, including prechamber volume, nozzle diameter, direct injector (DI) geometry, and engine operating strategies. Computational Fluid Dynamics (CFD) simulations are utilized, focusing on a heavy-duty, single-cylinder engine modeled after the Caterpillar C9.3B engine. Key findings indicate that a prechamber volume of 3 cc, coupled with a nozzle diameter of 2.75 mm for two prechamber holes, strikes an optimal balance between combustion efficiency and emissions reduction. This configuration ensures robust combustion across a range of operating conditions while maintaining methane slip within targeted limits. Further investigation into DI geometry shows the significance of the injector umbrella angle and nozzle diameter in shaping the fuel-air mixing and combustion dynamics. An umbrella angle of 130° and a nozzle diameter of 300 microns are identified as optimal, promoting rapid and efficient combustion with minimized methane and NOx emissions. The study also investigates the impact of injection timing and pressure, highlighting their roles in controlling combustion timing and influencing emissions levels. Advanced injection timing is found to be crucial in achieving the desired low methane slip, whereas retarded injection timing assists to reduce NOx emissions while having a slight increase in methane emissions. Operating strategies incorporating various levels of Exhaust Gas Recirculation (EGR) are assessed for their effectiveness in further reducing emissions. The research demonstrates that a judicious combination of internal hot EGR and careful calibration of DI pressure and SOI timing can achieve significant reductions in NOx emissions while keeping methane slip under control. Specifically, an internal EGR level of 15%–25%, combined with DI pressures of 200–300 bar and injection timings at or after top dead center, is recommended. These findings contribute valuable insights into the development of advanced combustion techniques for natural gas engines, offering a viable pathway to reduce methane slip without compromising engine efficiency or performance. The PC-MCC system presents a promising solution for the future of heavy-duty natural gas engine technology to reduce methane emissions.

Nsaif, Osama↗