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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

On the canonical formulation of gauge field theories and Poincaré transformations

We address the Hamiltonian formulation of classical gauge field theories while putting forward results some of which are not entirely new, though they do not appear to be well known. We refer in particular to the fact that neither the canonical energy momentum vector ( P μ ) nor the gauge invariant energy momentum vector ( P inv μ ) do generate space-time translations of the gauge field by means of the Poisson brackets: In a general gauge, one has to consider the so-called kinematical energy momentum vector and, in a specific gauge (like the radiation gauge in electrodynamics), one has to consider the Dirac brackets rather than the Poisson brackets. Similar arguments apply to rotations and to Lorentz boosts and are of direct relevance to the “nucleon spin crisis” since the spin of the proton involves a contribution which is due to the angular momentum vector of gluons and thereby requires a proper treatment of the latter. We conclude with some comments on the relationships between the different approaches to quantization (canonical quantization based on the classical Hamiltonian formulation, Gupta-Bleuler, path integrals, BRST, covariant canonical approaches).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

On the connection between perturbation theory and new semiclassical expansion in quantum mechanics

Here, it is shown that for the one-dimensional anharmonic oscillator with potential V(x) = ax 2 + bgx 3 + ... = $\frac{1}{g^2}$ $\hat{V}$ (gx), as well as for the radial oscillator V(r) = $\frac{1}{g^2}$ $\hat{V}$ (gr) and for the perturbed Coulomb problem V(r) = $\frac{a}{r}$ + βgr + ... = g $\tilde{V}$ (gr), the Perturbation Theory in powers of the coupling constant g (weak coupling regime) and the semiclassical expansion in powers of $\hbar$ 1/2 for the energies coincide. This is related to the fact that the dynamics developed in two spaces: x (r)-space and gx (gr)-space, lead to the same energy spectra. The equations which govern dynamics in these two spaces, the Riccati-Bloch equation and the Generalized Bloch equation, respectively, are presented. It is shown that the perturbation theory for the logarithmic derivative of the wavefunction in - space leads to (true) semiclassical expansion in powers of $\hbar$ 1/2 ; for the one-dimensional case this corresponds to the flucton calculus for the density matrix in the path integral formalism in Euclidean (imaginary) time proposed by one of the authors. Matching the perturbation theory in powers of g and the semiclassical expansion in powers of $\hbar$ 1/2 for the wavefunction leads to a highly accurate local approximation in the entire coordinate space, its expectation value for the Hamiltonian provides a prescription for the summation of the perturbative (trans)-series.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Public perceptions of wave energy development on the west coast of North America: Risks, benefits, and coastal attachment

While solar and wind energy continue to grow as significant sources of renewable energy, a global energy transition away from fossil fuels will require an expanding portfolio of generating resources. Marine renewable energy has the potential to contribute greatly in the coming decades, as the more predictable nature of wave energy can support the resiliency of the power grid and complement solar and inland wind generation. Yet, the broad deployment of marine energy technologies like wave energy will depend on public support, making it critical to identify the relevant factors associated with public attitudes and risk/benefit perceptions. This paper draws on social representations theory to specifically examine perceptions of wave energy on the west coast of North America, a site chosen because of the high suitability for wave energy generation and the fact that one of only three wave energy test sites in the world is under development off the coast of Oregon. Using an online survey in June 2020, we recruited a sample of 2000 respondents from California, Oregon, Washington, and British Columbia. We found a majority of respondents held positive attitudes to wave energy, but respondents also had low familiarity – with a quarter of respondents lacking sufficient information to form an opinion. We used logistic regression to identify factors correlated with wave energy attitudes, finding that respondents who were more supportive of wind and solar energy, more optimistic about new technology, and reported more familiarity with wave energy were significantly more likely to have a positive impression of wave energy. Respondents with higher levels of place attachment to coastal areas were more split, as they perceived higher benefits of wave energy – but also higher risks. Our results indicate broad appeal of wave energy on the west coast, but we caution policymakers and developers to not take initial siting processes for granted. As experience has shown for offshore wind, broad appeal does not guarantee a smooth siting process in a local context. Furthermore, the role of place attachment to coastal areas must be taken seriously or risk alienating local communities.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Thermodynamically consistent Cahn–Hilliard–Navier–Stokes equations using the metriplectic dynamics formalism

Cahn–Hilliard–Navier–Stokes (CHNS) systems describe flows with two-phases, e.g., a liquid with bubbles. Obtaining constitutive relations for general dissipative processes for such systems, which are thermodynamically consistent, can be a challenge. We show how the metriplectic 4-bracket formalism (Morrison and Updike, 2024) achieves this in a straightforward, in fact algorithmic, manner. First, from the noncanonical Hamiltonian formulation for the ideal part of a CHNS system we obtain an appropriate Casimir to serve as the entropy in the metriplectic formalism that describes the dissipation (e.g. viscosity, heat conductivity and diffusion effects). General thermodynamics with the concentration variable and its thermodynamics conjugate, the chemical potential, are included. Having expressions for the Hamiltonian (energy), entropy, and Poisson bracket, we describe a procedure for obtaining a metriplectic 4-bracket that describes thermodynamically consistent dissipative effects. The 4-bracket formalism leads naturally to a general CHNS system that allows for anisotropic surface energy effects. Furthermore, this general CHNS system reduces to cases in the literature, to which we can compare.

Cahn–Hilliard↗
DOE OSTI2024

Spin-orbit entanglement in the Color Glass Condensate

We compute the spin-orbit correlations of quarks and gluons at small-x and show that the helicity and the orbital angular momentum of individual partons are strongly anti-aligned even in unpolarized or spinless hadrons and nuclei. Combined with the fact that gluons in the Color Glass Condensate are linearly polarized, our finding indicates that the helicity and the orbital angular momentum of single gluons are maximally entangled in a quantum mechanical sense.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Measuring short-range correlations and quasi-elastic cross sections in A(e,e’) at x > 1 and modest Q 2

We present results from the Jefferson Lab E08-014 experiment, investigating short-range correlations (SRC) through measurements of inclusive quasi-elastic scattering from 2 H, 3 He, 4 He, 12 C, 40 Ca, and 48 Ca. The kinematics were selected to isolate scattering from SRCs, yielding a plateau in the A/ 2 H cross-section ratios due to the universal two-body structure of the 2N-SRCs in light and heavy nuclei. We observe approximate plateaus in the A/ 2 H ratios and provide the first extractions of the A/ 2 H ratio for 40 Ca and 48 Ca. We also examine the A/ 3 He ratio, aiming to identify three-nucleon SRCs (3N-SRCs). Following the approach for isolating 2N-SRCs, searching for 3N-SRC dominance involved measuring the A/ 3 He cross section ratio at modest-to-large Q 2 values and looking for a plateau ratios for x ≳ 2.5. This was not observed in the data, and in fact increasing Q 2 values moved the data further away from the predicted plateau. We show here that, when analyzed in terms of the struck nucleon’s light-cone momentum, the data exhibited the expected trend, progressively approaching the predicted 3N-SRC plateau. These observations suggest that future measurements at higher energies may facilitate a definitive isolation and identification of 3N-SRCs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Quantum state preparation with resolution refinement

We introduce a method called resolution refinement that allows one to bootstrap eigenstate preparation on a quantum computer. We first prepare an eigenstate of a low-resolution Hamiltonian using any method of choice. The eigenstate is then lifted to higher resolution and adiabatically evolved to produce the corresponding eigenstate of a higher-fidelity Hamiltonian. We give examples of resolution refinement applied to both single-particle basis states as well as a spatial lattice grid. For basis refinement, we compute few-body ground states of the Busch model for interacting particles in a harmonic trap in one dimension. For lattice refinement, we compute Hartree-Fock nuclear states for a central Woods-Saxon potential in three dimensions, and we compute bound states and continuum states in a multi-species Hubbard model of fermions in one dimension. In all cases, the method is efficient and requires an adiabatic evolution time that scales with the inverse of the energy gap times the square root of the system size. We show that this very favorable scaling arises from the fact that resolution refinement does not make large changes to the structure or energies of the low-energy eigenstates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Diquark correlations in hadron physics: Origin, impact and evidence

The last decade has seen a marked shift in how the internal structure of hadrons is understood. Modern experimental facilities, new theoretical techniques for the continuum bound-state problem and progress with lattice-regularised QCD have provided strong indications that soft quark+quark (diquark) correlations play a crucial role in hadron physics. For example, theory indicates that the appearance of such correlations is a necessary consequence of dynamical chiral symmetry breaking, viz. a corollary of emergent hadronic mass that is responsible for almost all visible mass in the universe; experiment has uncovered signals for such correlations in the flavour-separation of the proton's electromagnetic form factors; and phenomenology suggests that diquark correlations might be critical to the formation of exotic tetra- and penta-quark hadrons. Therefore, a broad spectrum of such information is evaluated herein, with a view to consolidating the facts and therefrom moving toward a coherent, unified picture of hadron structure and the role that diquark correlations might play.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

High precision tests of QCD without scale or scheme ambiguities: The 40th anniversary of the Brodsky–Lepage–Mackenzie method

A key issue in making precise predictions in QCD is the uncertainty in setting the renormalization scale μ r and thus determining the correct values of the QCD running coupling α s (μ r ) at each order in the perturbative expansion of a QCD observable. It has often been conventional to simply set the renormalization scale to the typical scale of the process Q and vary it in the range μ r $\in$ [Q/2, 2Q] in order to estimate the theoretical error. This is the practice of Conventional Scale Setting (CSS). The resulting CSS prediction will however depend on the theorist’s choice of renormalization scheme and the resulting pQCD series will diverge factorially. It will also disagree with renormalization scale setting used in QED and electroweak theory thus precluding grand unification. A solution to the renormalization scale-setting problem is offered by the Principle of Maximum Conformality (PMC), which provides a systematic way to eliminate the renormalization scale-and-scheme dependence in perturbative calculations. The PMC method has rigorous theoretical foundations, it satisfies Renormalization Group Invariance (RGI) and preserves all self-consistency conditions derived from the renormalization group. The PMC cancels the renormalon growth, reduces to the Gell-Mann–Low scheme in the N c → 0 Abelian limit and leads to scale- and scheme-invariant results. The PMC has now been successfully applied to many high-energy processes. In this article we summarize recent developments and results in solving the renormalization scale and scheme ambiguities in perturbative QCD. In particular, we present a recently developed method the PMC ∞ and its applications, comparing the results with CSS. The method preserves the property of renormalizable SU(N)/U(1) gauge theories defined as Intrinsic Conformality (iCF). This property underlies the scale invariance of physical observables and leads to a remarkably efficient method to solve the conventional renormalization scale ambiguity at every order in pQCD. This new method reflects the underlying conformal properties displayed by pQCD at NNLO, eliminates the scheme dependence of pQCD predictions and is consistent with the general properties of the PMC. A new method to identify conformal and β-terms, which can be applied either to numerical or to theoretical calculations is also shown. We present results for the thrust and C-parameter distributions in e + e - annihilation showing errors and comparison with the CSS. We also show results for a recent innovative comparison between the CSS and the PMC ∞ applied to the thrust distribution investigating both the QCD conformal window and the QED N c → 0 limit. In order to determine the thrust distribution along the entire renormalization group flow from the highest energies to zero energy, we consider the number of flavors near the upper boundary of the conformal window. In this flavor-number regime the theory develops a perturbative infrared interacting fixed point. These results show that PMC ∞ leads to higher precision and introduces new interesting features in the PMC. In fact, this method preserves with continuity the position of the peak, showing perfect agreement with the experimental data already at NNLO. We also show a detailed comparison of the PMC ∞ with the other PMC approaches: the multi-scale-setting approach (PMCm) and the single-scale-setting approach (PMCs) by comparing their predictions for three important fully integrated quantities R e+e- , R$_Τ$ and Γ (H→$b\bar{b}$) up to the four-loop accuracy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

A statistical model for the product energy distribution in reactions leading to prompt dissociation

Direct dynamics calculations have been performed for three reactions: C 3 H 8 + H → i-C 3 H 7 + H 2 , C 3 H 8 + H → n-C 3 H 7 + H 2 , and C 2 H 3 + O 2 → HCO + CH 2 O. The fraction of the population for the radical products that promptly dissociates is computed. Here the results for C 3 H 8 + H are qualitatively similar to previous results for C 3 H 8 + OH, but the new results exhibit a slightly higher branching fraction for prompt dissociation products, owing to the fact that a greater fraction of the internal energy in the transition state ends up in the radical. For C 2 H 3 + O 2 → HCO + CH 2 O, the fraction of HCO that promptly dissociates is in excess of 99%. Consequently, the main product for C 2 H 3 + O 2 at lower temperatures should be written as H + CO + CH 2 O and not HCO + CH 2 O. These results are then compared with four previous systems: CH 2 O + H → HCO + H 2 , CH 2 O + OH → HCO + H 2 O, C 3 H 8 + OH → i-C 3 H 7 + H 2 O, and C 3 H 8 + OH → n-C 3 H 7 + H 2 O. Based upon these seven system, several statistical models are presented. The goal of these statistical models is to predict the fraction of the transition state energy that ends up in the rovibrationally excited radical. On average, these statistical models provide an excellent prediction of product energy distribution. Consequently, these models can be used instead of costly trajectory simulations for predicting prompt radical dissociation for larger species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Experimental and modeling study of water time histories during H 2 S-N 2 O combustion in a shock tube

Here, with the interest in directly burning sour gas in gas turbines, and the fact that even small amounts of H 2 S or its combustion products can alter combustion characteristics, many research studies have been performed to better understand the combustion chemistry of H 2 S. In the present study, the water formation was followed by laser absorption with N 2 O as an oxidant, instead of O 2 . Nitrous Oxide being essentially consumed via N 2 O (+M) ⇌ N 2 + O (+M), the water formation via the H 2 S + O route can then be probed to further validate the models. Three H 2 S/N 2 O mixtures diluted in 98% Ar were studied to cover the following range of equivalence ratios: 0.5, 1.0, and 2.0, over a wide range of temperatures (1580–1940 K) around atmospheric pressure. A chemical kinetic model was then developed first by validating the base N 2 O kinetics mechanism, then by investigating the experimental results presented herein. The N 2 O kinetics mechanism was updated with recent work on the low- and high-pressure limits for N 2 O decomposition (N 2 O (+M) ⇌ N 2 + O (+M)) as well as a review of rate coefficients for N 2 O + H ⇌ N 2 + OH from the literature. Good agreement is shown for H 2 /N 2 O mixtures. Updates were then made to the H 2 S kinetics mechanism, specifically, an update from the literature on SO 2 + H (+M) ⇌ SO + OH (+M) and an adjustment to SO + SH ⇌ S 2 + OH. Additionally, reactions between SH and N 2 O were determined using W1BD data and transition state theory which required the addition of an NNS sub-mechanism. With these updates, the mechanism provides good agreement with the H 2 S/N 2 O experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

The Kalahari sediments and hominins in southern Africa

In this study, the temporal coupling of the structural evolution of the Kalahari Basin and the accumulation of the Kalahari Group sediments has been an accepted paradigm leading to the assumption that the Kalahari group sediments have been accumulating gradually since the mid-Cretaceous. Here we review the first actual ages for the Kalahari Group based on cosmogenic ages from six geological localities. These results demonstrate that Kalahari Basin infill was a more dynamic process than previously thought and that the Kalahari Group sediments are mostly Plio-Pleistocene in age (~4 Ma to 1–2 Ma). The hiatus between the initial structural subsidence of the basin, during the Cretaceous, and the general young age of the investigated sediments, implies a dynamic landscape in which significant phases of erosion occurred during the Mesozoic and Cenozoic. The magnitude of erosion is manifested by the fact that in many locations Kalahari Neogene to Quaternary sediments overlie Precambrian basement. The age of the present infill of the Kalahari thus falls within the temporal range of the genus Homo. In light of this new understanding, we provide a review of the archaeological evidence from the Kalahari Basin and along its southern fringe. Initial hominin presence is found at Wonderwerk Cave during the Olduvai Event and there is subsequent high-density occupation along the southern fringe of the Kalahari Basin during the Acheulean and the Fauresmith. Middle Stone Age occupation is limited to localities of limited size and small artifact counts and it appears that the focus of human occupation, particularly in the later stages of the Middle Stone Age, shifts southward, including along the coastal regions.

58 GEOSCIENCES↗
DOE OSTI2022

The modeling of risk perception in the use of structural health monitoring information for optimal maintenance decisions

This paper proposes an approach to select a maintenance strategy from a predefined set of choices considering the decision maker’s behavioral risk profile. It is assumed that the damage state is characterized by a continuous state parameter probabilistically inferred from observable sensor data. This work applies an engineering application of consequence-based decision-making incorporating the acceptable risk intensity of the decision-maker, i.e., the decision-maker’s (individual or an organization) valuation of the outcome of a decision, using a risk profile model. The utility of a decision-maker is subjective, and this paper considers the fact that different decision-makers mentally assign a different importance factor (the utility) to the seriousness or urgency to take necessary actions with the increasing intensity of structural damage. The approach herein incorporates a layer of human psychology on selecting appropriate maintenance strategies that not only depend on the posterior distribution of unmeasurable damage state but also consider the behavioral risk profile of the decision-maker. Further, the collective decision-making of an organization consisting of many individuals is also investigated. The approach is exemplified in a case study involving life cycle monitoring of a miter gate, part of a lock system enabling navigation of inland waterways.

42 ENGINEERING↗
DOE OSTI2023

Reliability modeling in a predictive maintenance context: A margin-based approach

Current system reliability methods (typically based on fault trees or reliability block diagrams) can effectively propagate reliability data from the asset to the system level in order to identify system critical points. However, employed asset reliability data are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). Sensor data, diagnostic assessments, and prognostic assessments are in fact not considered in plant reliability models used to inform system engineers on the most critical assets. In addition, the propagation of quantitative health data from the asset to the system level is a challenge given the diverse nature and structure of health data elements (e.g., vibration spectra, temperature readings, expected failure time). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating available health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Here, this paper is directly addressing these two goals by proposing a different approach for reliability modeling that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. The propagation of health data from the asset to the system level is performed through fault tree models not in probability terms, but in terms of margin where margin is the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated with asset performance, a margin-based approach focuses on the cause of an undesired asset performance (i.e., its health). Hence, thinking of reliability in terms of margins implies decision-making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical assets.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

2-D soil zymography: Accounting for the spatial variation of pH

Soil zymography is commonly used to quantify spatial distribution of hydrolytic enzyme activities on soil and plant root surfaces. It is recommended to adjust pH in zymography substrates and calibration solutions with respect to soil/root pH. However, pH values may vary greatly within a few mm of plant rhizosphere, potentially altering the distribution of pH in zymography membranes. Despite the fact that the effect of pH on the calibration of zymography membranes is generally known, its potential impact on zymography results is unaccounted for in processing zymography images and calculations of enzyme activity. In this study we assessed the effect of pH variations on the persistency of the methylumbelliferone (MUF) calibration. The studied pH values ranged from 4.5 to 7.5. The MUF calibration curves greatly deviated from that at a reference pH of 6.5, with a marked nonlinear increase of deviation with greater membrane brightness. We suggest that the problem can be partially alleviated by reducing the membrane incubation time. However, such deviations suggest the need for a more comprehensive resolution via mapping pH and using pH-specific calibrations to process zymography images. Here, we developed a MATLAB code to implement a pixel-based correction of enzyme activity for pH in processing time-lapse zymography images.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Disentangling error structures of precipitation datasets using decision trees

Characterizing error structures in precipitation products not only facilitates their proper applications for scientific and practical purposes but also helps improve their retrieval algorithms and processing methods. Despite the fact that multiple precipitation products have been assessed in the literature, factors that affect their error structures remain inadequately addressed. By interpreting 60 binary decision trees, this study disentangles the error characteristics of precipitation products in terms of their spatiotemporal patterns and geographical factors. Three independent precipitation products - two satellite-based and one reanalysis datasets: the Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) late run (IMERG-L), Soil Moisture to Rain-Advanced SCATterometer (SM2RAIN-ASCAT), and the Modern-Era Retrospective analysis for Research and Applications, Version 2 uncorrected precipitation output (MERRA2-UC), are evaluated across the contiguous United States from 2010 to 2019. Here, the ground-based Stage IV precipitation dataset is used as the ground truth. Results indicate that the MERRA2-UC outperforms the IMERG-L and SM2RAIN-ASCAT with higher accuracy and more stable interannual patterns for the analysis period. Decision trees cross-assess three spatiotemporal factors and find that the underestimation of MERRA2-UC occurs in the east of the Rocky Mountains, and SM2RAIN-ASCAT underestimates precipitation over high latitudes, especially in winter. Additionally, the decision tree method ascribes system errors to nine different geographical characteristics, of which the distance to the coast, soil type, and DEM are the three dominant features. On the other hand, the land cover type, topography position index, and aspect are three relatively weak factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A taxonomy of systems that combine utility-scale renewable energy and energy storage technologies

Interest in renewable energy-based hybrid systems—which combine multiple renewable energy and/or energy storage technologies—is apparent and growing. Such systems could play an important role in the grid of the future, but our ability to quantify their potential impacts is hindered by (a) the inconsistent treatment of hybrid systems and (b) an incomplete understanding of which aspects of hybridization will have the greatest influence. In this article, we review the literature and propose an organization scheme for utility-scale hybrid systems in which electricity is generated from commercially available, renewable energy technologies, and electricity is the only output. Based on this literature review, we propose three categories for delineating systems that link multiple renewable energy and/or energy storage technologies: co-located resources (locational linkage only), virtual power plants (operational linkage only), and full hybrids (location and operational linkages). Proposing a categorization based on whether the systems involve locational and/or operational linkages reflects the fact that technology combinations do not represent a meaningful delineation. In addition, the categories are ideal for informing model development efforts, by identifying the unique characteristics that must be captured in adequate representations of systems that fall under each category. Our categories can also help inform policy considerations, as they delineate system characteristics that would introduce distinct permitting, siting, interconnection, and policy challenges. Therefore, we believe that our proposed taxonomy will help organize thinking and research efforts in a way that will enable consistent evaluation of the costs, values, and potential of renewable energy-based hybrids.

25 ENERGY STORAGE↗
DOE OSTI2024

Sentiment analysis of the United States public support of nuclear power on social media using large language models

This study utilized large language models (LLMs) to analyze public sentiment in the United States (US) regarding nuclear power on social media, focusing on X/Twitter, considering climate change challenges and advancements in nuclear power technology. Approximately, 1.26 million nuclear tweets from 2008–2023 were examined to fine-tune LLMs for sentiment classification. We found the crucial role of accurate data labeling for model performance, with potential implications for a 15% improvement, achieved through high-confidence labels. LLMs demonstrated better performance compared to traditional machine learning classifiers, with reduced susceptibility to overfitting and up to 96% classification accuracy. LLMs are used to segment the US public tweets into policy and energy-related categories, revealing that 68% are politically themed. Policy tweets tended to convey negative sentiment, often reflecting opposing political perspectives and focusing on nuclear deals and international relations. Energy-related tweets covered diverse topics with predominantly neutral to positive sentiment, indicating broad support for nuclear power in 48 out of 50 US states. The US public positive sentiments toward nuclear power stemmed from its high power density, reliability regardless of weather conditions, environmental benefits, application versatility, and recent innovations and advancements in both fission and fusion technologies. Negative sentiments primarily focused on waste management, high capital costs, and safety concerns. The neutral campaign highlighted global nuclear facts and advancements, with varying tones leaning towards positivity or negativity. An interesting neutral theme was the advocacy for the combined use of renewable and nuclear energy to attain net-zero goals.

Energy & Fuels↗