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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Spinning no-scale $${\mathcal {F}}$$-SU(5) in the right direction

Abstract The Fermi National Accelerator Laboratory (FNAL) recently announced confirmation of the Brookhaven National Lab (BNL) measurements of the $$g-2$$ g - 2 of the muon that uncovered a discrepancy with the theoretically calculated Standard Model value. We suggest an explanation for the combined BNL+FNAL 4.2 $$\sigma $$ σ deviation within the supersymmetric grand unification theory (GUT) model No-Scale $${\mathcal {F}}$$ F - $$SU(5)$$ S U ( 5 ) supplemented with a string derived TeV-scale extra $$10+\overline{10}$$ 10 + 10 ¯ vector-like multiplet and charged vector-like singlet $$(XE,XE^c)$$ ( X E , X E c ) , dubbed flippons. We introduced these vector-like particles into No-Scale Flipped SU (5) many years ago, and as a result, the renormalization group equation (RGE) running was immediately shaped to produce a distinctive and rather beneficial two-stage gauge coupling unification process to avoid the Landau pole and lift unification to the string scale, in addition to contributing through 1-loop to the light Higgs boson mass. The flippons have long stood ready to tackle another challenge, and now do so yet again, where the charged vector-like “lepton”/singlet couples with the muon, the supersymmetric down-type Higgs $$H_d$$ H d , and a singlet S , using a chirality flip to easily accommodate the muonic $$g-2$$ g - 2 discrepancy in No-Scale $${\mathcal {F}}$$ F - $$SU(5)$$ S U ( 5 ) . Considering the phenomenological success of this string derived model over the prior 11 years that remains accommodative of all presently available LHC limits plus all other experimental constraints, including no fine-tuning, and the fact that for the first time a Starobinsky-like inflationary model consistent with all cosmological data was derived from superstring theory in No-Scale Flipped SU (5), we believe it is imperative to reconcile the BNL+FNAL developments within the model space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Physics from Cosmic Surveys (Final Report)

The main focus of the PI during this time was leading the effort to produce cosmological results on the data set from the first three years from the Dark Energy Survey (DES). The analysis combines weak gravitational lensing and maps of the galaxy distribution, supplemented by estimates of the redshifts of galaxies. This will ultimately lead to 33 papers, culminating in a single paper that brings all this together and provides a constraint on the clustering parameter σ 8 .This will be directly compared to the constraint obtained by high-redshift experiments, such as the Planck satellite, extrapolated forward assuming the CDM model. If the two values disagree, as they currently seem to at the 2-sigma level, this will be an indication that the model is incorrect or incomplete. These papers are expected to be submitted in January, 2021. Leading this effort, with help from many others, has been the primary research focus of the PI during this grant.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Cosmology Intertwined III: $f \sigma_8$ and $S_8$

The standard $\Lambda$ Cold Dark Matter cosmological model provides a wonderful fit to current cosmological data, but a few tensions and anomalies became statistically significant with the latest data analyses. While these anomalies could be due to the presence of systematic errors in the experiments, they could also indicate the need for new physics beyond the standard model. In this Letter of Interest we focus on the tension of the Planck data with weak lensing measurements and redshift surveys, about the value of the matter energy density $\Omega_m$, and the amplitude or rate of the growth of structure ($\sigma_8,f\sigma_8$). We list a few interesting models for solving this tension, and we discuss the importance of trying to fit with a single model a full array of data and not just one parameter at a time.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Measurement of the photon beam asymmetry in γ → p → K + Σ 0 at E γ = 8.5 GeV

We report measurements of the photon beam asymmetry $\Sigma$ for the reaction $\vec{\gamma} p\to K^+\Sigma^0$(1193) using the GlueX spectrometer in Hall D at Jefferson Lab. Data were collected using a linearly polarized photon beam in the energy range of 8.2-8.8 GeV incident on a liquid hydrogen target. The beam asymmetry $\Sigma$ was measured as a function of the Mandelstam variable $t$, and a single value of $\Sigma$ was extracted for events produced in the $u$-channel. These are the first exclusive measurements of the photon beam asymmetry $\Sigma$ for the reaction in this energy range. For the $t$-channel, the measured beam asymmetry is close to unity over the $t$-range studied, $-t=(0.1-1.4)~$(GeV/$c$)$^{2}$, with an average value of $\Sigma = 1.00\pm 0.05$. This agrees with theoretical models that describe the reaction via the natural-parity exchange of the $K^{*}$(892) Regge trajectory. A value of $\Sigma = 0.41 \pm 0.09$ is obtained for the $u$-channel integrated up to $-u=2.0$~(GeV/$c$)$^{2}$.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Dark energy survey year 3 results: cosmology from galaxy clustering and galaxy–galaxy lensing in harmonic space

We present the joint tomographic analysis of galaxy-galaxy lensing and galaxy clustering in harmonic space (HS), using galaxy catalogues from the first three years of observations by the Dark Energy Survey (DES Y3). We utilize the redMaGiC and MagLim catalogues as lens galaxies and the metacalibration catalogue as source galaxies. The measurements of angular power spectra are performed using the pseudo-$C_\ell$ method, and our theoretical modelling follows the fiducial analyses performed by DES Y3 in configuration space, accounting for galaxy bias, intrinsic alignments, magnification bias, shear magnification bias and photometric redshift uncertainties. We explore different approaches for scale cuts based on non-linear galaxy bias and baryonic effects contamination. Our fiducial covariance matrix is computed analytically, accounting for mask geometry in the Gaussian term, and including non-Gaussian contributions and super-sample covariance terms. To validate our HS pipelines and covariance matrix, we used a suite of 1800 log-normal simulations. We also perform a series of stress tests to gauge the robustness of our HS analysis. In the $\Lambda$CDM model, the clustering amplitude $S_8 =\sigma _8(\Omega _m/0.3)^{0.5}$ is constrained to $S_8 = 0.704\pm 0.029$ and $S_8 = 0.753\pm 0.024$ (68 per cent C.L.) for the redMaGiC and MagLim catalogues, respectively. For the wCDM, the dark energy equation of state is constrained to $w = -1.28 \pm 0.29$ and $w = -1.26^{+0.34}_{-0.27}$, for redMaGiC and MagLim catalogues, respectively. These results are compatible with the corresponding DES Y3 results in configuration space and pave the way for HS analyses using the DES Y6 data.

(cosmology:) cosmological parameters↗
DOE OSTI2021

Demonstration of Advanced Experimental and Theoretical Characterization of Hydrogen Dynamics and Associated Behavior in Advanced Reactors

Advanced materials development, manufacturing, and modeling capabilities for innovative reactor designs support nuclear security and mission-focused science through enhanced technology for safer and more efficient and secure production of nuclear energy. The research in this project has established: 1) a state-of-the-art neutron-based hydrogen mapping and cross-section measurement capability as well as detailed crystallographic characterization of hydrogen atoms at LANSCE, and 2) a multi-physics framework for simulating behavior of moderator materials and other material performance in advanced nuclear reactors. Through the course of this project, we successfully developed and demonstrated measurement techniques for hydrogen distribution and atomistic-scale behavior of hydrogen atoms using pulsed neutron techniques. In parallel, advanced multi-physics simulation tools to predict the behavior of hydrogen atoms, e.g. in a moderator for a nuclear reactor, through materials performance, neutron transport, and thermal mechanical behavior were enhanced. Multi-discipline areas across the laboratory were involved in the project as the integration of improved experimental capabilities with enhanced modeling and simulation through MST, NEN, SIGMA, and XCP division subject matter experts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A three-dimensional model of terrain-induced updrafts for movement ecology studies

Abstract Background Spatially explicit simulation models of animal movements through the atmosphere necessarily require a representation of the spatial and temporal variation of atmospheric conditions. In particular, for movements of soaring birds that rely extensively on vertical updrafts to avoid flapping flight, accurate and reliable estimation of the vertical component of wind is critical. The interaction between wind and complex terrain shapes both the horizontal and vertical wind fields, highlighting the need to model the coupling between local terrain features and atmospheric conditions at scales relevant to animal movement. Methods In this work, we propose a new empirical model for estimating the orographic updraft field. The model is developed using computational fluid dynamics simulations of canonical atmospheric conditions over moderately complex terrain. To isolate buoyancy and thermal effects, and focus on terrain-induced effects, we use only simulations of a neutrally stratified atmosphere to develop the model. The model, which we name Engineering Vertical Velocity Estimator (EVVE), is simple to implement and is a function of the underlying terrain elevation map, the desired height above ground level (AGL), and wind conditions at a reference height (80 m). We validate the model with data from the Alaiz mountain (Spain) field campaign. Results Compared to observations, the proposed improved model estimates the updrafts at 120 m AGL with a mean error of 0.11 m/s ( $$\sigma =0.28$$ σ = 0.28 m/s), compared to 0.85 m/s ( $$\sigma =0.58$$ σ = 0.58 m/s) for its baseline. For typical land-based wind turbine hub heights of 80 m AGL, the proposed model has a mean error of 0.04 m/s ( $$\sigma =0.25$$ σ = 0.25 m/s), compared to baseline 0.54 m/s ( $$\sigma =0.45$$ σ = 0.45 m/s) estimations. We illustrate an application of the model in movement ecology by comparing simulated tracks and presence maps of golden eagles ( Aquila chrysaetos ) moving across two distinct landscapes. The tracks and presence maps are obtained using a simple heuristic-based movement model, with the updraft field given by the proposed model and a wind vector-based estimation approach that is currently in wide use in movement ecology studies of raptors and other soaring birds. Conclusions We highlight that movement model results can be sensitive to the underlying orographic updraft model, especially in studies of fine-scale movements in regions of complex topography. We suggest adopting the proposed model rather than the wind vector estimation method for studies of soaring bird movements.

17 WIND ENERGY↗
DOE OSTI2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological Implications from two Decades of Spectroscopic Surveys at the Apache Point observatory

We present the cosmological implications from final measurements of clustering using galaxies, quasars, and Ly$\alpha$ forests from the completed Sloan Digital Sky Survey (SDSS) lineage of experiments in large-scale structure. These experiments, composed of data from SDSS, SDSS-II, BOSS, and eBOSS, offer independent measurements of baryon acoustic oscillation (BAO) measurements of angular-diameter distances and Hubble distances relative to the sound horizon, $r_d$, from eight different samples and six measurements of the growth rate parameter, $f\sigma_8$, from redshift-space distortions (RSD). This composite sample is the most constraining of its kind and allows us to perform a comprehensive assessment of the cosmological model after two decades of dedicated spectroscopic observation. We show that the BAO data alone are able to rule out dark-energy-free models at more than eight standard deviations in an extension to the flat, $\Lambda$CDM model that allows for curvature. When combined with Planck Cosmic Microwave Background (CMB) measurements of temperature and polarization the BAO data provide nearly an order of magnitude improvement on curvature constraints. The RSD measurements indicate a growth rate that is consistent with predictions from Planck primary data and with General Relativity. When combining the results of SDSS BAO and RSD with external data, all multiple-parameter extensions remain consistent with a $\Lambda$CDM model. Regardless of cosmological model, the precision on $\Omega_\Lambda$, $H_0$, and $\sigma_8$, remains at roughly 1\%, showing changes of less than 0.6\% in the central values between models. The inverse distance ladder measurement under a o$w_0w_a$CDM yields $H_0= 68.20 \pm 0.81 \, \rm km\, s^{-1} Mpc^{-1}$, remaining in tension with several direct determination methods. (abridged)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

$\Sigma ^{+}$ production in pp collisions at $\sqrt{\textit{s}}=13$ TeV

The measurement of $\Sigma ^{+}$ production in pp collisions at $\sqrt{s}=13$ TeV is presented. The measurement is performed at midrapidity in both minimum-bias and high-multiplicity pp collisions at $\sqrt{s}=13$ TeV. The $\Sigma ^{+}$ is reconstructed via its weak-decay topology in the decay channel $\Sigma ^{+} \rightarrow \mathrm{{p}} + \pi ^{0}$ with $\pi ^{0} \rightarrow \gamma + \gamma$. In a novel approach, the neutral pion is reconstructed by combining photons that convert in the detector material with photons measured in the calorimeters. The transverse-momentum $(p_{\textrm{T}})$ distributions of the $\Sigma ^{+}$ and its rapidity densities dN/dy in both event classes are reported. The $p_{\textrm{T}}$ spectrum in minimum-bias collisions is compared to QCD-inspired event generators. The ratio of $\Sigma ^{+}$ to previously measured Λ baryons is in good agreement with calculations from the Statistical Hadronization Model. The high efficiency and purity of the novel reconstruction method for $\Sigma ^{+}$ presented here will enable future studies of the interaction of $\Sigma ^{+}$ with protons in the context of femtoscopic measurements, which could be crucial for understanding the equation of state of neutron stars.

Abualrob, I. J. [University of Houston] (ORCID:000↗
DOE OSTI2025

Early time solution as an alternative to the late time evolving dark energy with DESI DR2 BAO

Recently the Dark Energy Spectroscopic Instrument (DESI) provided constraints on the expansion history from their Data Release 2 (DR2). The DESI baryon acoustic oscillation (BAO) measurements are well described by a flat $\Lambda$CDM model, but the preferred parameters are in mild ($2.3\sigma$) tension with those determined from the cosmic microwave background (CMB). The DESI collaboration has already explored a variety of solutions to this tension relying on variations in the late-time evolution of dark energy. Here we test an alternative -- the introduction of an ``early dark energy'' (EDE) component. We find that EDE models can alleviate the tension, though they lead to differences in other cosmological parameters that have observational implications. Particularly the EDE models that fit the acoustic datasets prefer lower $\Omega_m$, higher $H_0$, $n_s$ and $\sigma_8$ in contrast to the late-time solutions. We discuss the current status and near-future prospects for distinguishing amongst these solutions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

$\overline{\Sigma }^{\pm }$ production in $\text {pp}$ and $\text {p}{-}\text{Pb}$ collisions at $\sqrt{s_{\textrm{NN}}} = 5.02$ TeV with ALICE

The transverse momentum spectra and integrated yields of anti-$Σ$ hyperons ($\overline{\Sigma}^{\pm}$) have been measured in and collisions at $\sqrt{s_{\textrm{NN}}} = 5.02$ TeV with the ALICE experiment. Measurements are performed via the newly accessed decay channel $\overline{\Sigma}^{\pm}$ → $\bar{\textrm{n}}π^±$. A new method of antineutron reconstruction with the PHOS electromagnetic spectrometer is developed and applied to this analysis. The p T spectra of $\overline{\Sigma}^{\pm}$ are measured in the range 0.5 < p T < 3 GeV/c and compared to predictions of the PYTHIA 8, DPMJET, PHOJET, EPOS LHC and EPOS4 models. The EPOS LHC and EPOS4 models provide the best descriptions of the measured spectra both in pp and p-Pb collisions, while models which do not account for multiparton interactions provide a considerably worse description at high p T . The total yields of $\overline{\Sigma }^{\pm }$ in both pp and p-Pb collisions are compared to predictions of the Thermal-FIST model and dynamical models PYTHIA 8, DPMJET, PHOJET, EPOS LHC and EPOS4. All models reproduce the total yields in both colliding systems within uncertainties. The nuclear modification factors R pPb for both $\overline{\Sigma}^{+}$ and $\overline{\Sigma}^{-}$ are evaluated and compared to those of protons, $Λ$ and $Ξ$ hyperons, and predictions of EPOS LHC and EPOS4 models. No deviations of R pPb for $\overline{\Sigma}^{\pm}$ from the model predictions or measurements for other hadrons are found within uncertainties.

Abualrob, I. J. [University of Houston] (ORCID:000↗
DOE OSTI2024

Asymmetric drift in MaNGA: mass and radially dependent stratification rates in galaxy discs

ABSTRACT We measure the age–velocity relationship from the lag between ionized gas and stellar tangential speeds in ∼500 nearby disc galaxies from MaNGA in Sloan Digital Sky Survey IV (SDSS-IV). Selected galaxies are kinematically axisymmetric. Velocity lags are asymmetric drift, seen in the Milky Way’s (MW) solar neighbourhood and other Local Group galaxies; their amplitude correlates with stellar population age. The trend is qualitatively consistent in rate ($\dot{\sigma }$) with a simple power-law model where σ ∝ tb that explains the dynamical phase-space stratification in the solar neighbourhood. The model is generalized based on disc dynamical times to other radii and other galaxies. We find in-plane radial stratification parameters σ0,r (dispersion of the youngest populations) in the range of 10–40 km s−1 and 0.2 < br < 0.5 for MaNGA galaxies. Overall, brincreases with galaxy mass, decreases with radius for galaxies above 10.4 dex (M⊙) in stellar mass, but is ∼constant with radius at lower mass. The measurement scatter indicates the stratification model is too simple to capture the complexity seen in the data, unsurprising given the many possible astrophysical processes that may lead to stellar population dynamical stratification. None the less, the data show dynamical stratification is broadly present in the galaxy population, with systematic trends in mass and density. The amplitude of the asymmetric drift signal is larger for the MaNGA sample than the MW, and better represented in the mean by what is observed in the discs of M31 and M33. Either typical discs have higher surface-density or, more likely, are dynamically hotter (hence thicker) than the MW.

Bershady, Matthew A. (ORCID:0000000231314374)↗
DOE OSTI2020

Precise measurement of $2νββ$ decay of $^{100}$Mo with the CUPID-Mo detection technology

We report the measurement of the two-neutrino double-beta ($2\nu\beta\beta$) decay of $^{100}$Mo to the ground state of $^{100}$Ru using lithium molybdate (\crystal) scintillating bolometers. The detectors were developed for the CUPID-Mo program and operated at the EDELWEISS-III low background facility in the Modane underground laboratory. From a total exposure of $42.235$ kg$\times$d, the half-life of $^{100}$Mo is determined to be $T_{1/2}^{2\nu}=[7.12^{+0.18}_{-0.14}\,\mathrm{(stat.)}\pm0.10\,\mathrm{(syst.)}]\times10^{18}$ years. This is the most accurate determination of the $2\nu\beta\beta$ half-life of $^{100}$Mo to date. We also confirm, with the statistical significance of $>3\sigma$, that the single-state dominance model of the $2\nu\beta\beta$ decay of $^{100}$Mo is favored over the high-state dominance model.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Beam Dynamics Challenges in the Muon g-2 Experiment

The muon&s;s anomalous magnetic moment $a_{\mu}$ has hinted at physics beyond the standard model for nearly 20 years. The Muon $g-2$ experiment at Fermilab aims to measure $a_{\mu}$ to 140 parts per billion (ppb) precision. The 460 ppb result from its first data run (Run-1), released in 2021, agreed with the previous 2006 Brookhaven Muon $g-2$ result. The experimental average stands in tension with the standard model theory $a_{\mu}$ prediction by $4.2 \sigma$. The result of Run-2/3 data analysis is set be released in summer 2023, and will improve on the Run-1 precision by a factor of two. With the data collected in all six runs, the experiment is on track to produce a 140 ppb measurement of $a_{\mu}$. If the experiment and theory central values are both unchanged, the tension would exceed $5 \sigma$. The measurement is accomplished by injecting muons into a magnetic storage ring and precisely measuring two observable frequencies: $\omega_a$, the muons&s; anomalous precession frequency, and $\tilde{\omega}&s;_p$, the precession frequency of protons which determines the magnetic field strength experienced by the muons. This thesis presents a selection of muon beam dynamics effects which are critical for reaching the experiment precision goal. A system of detectors assists with the challenging beam injection into the storage ring, and a measurement of the injected beam provides input for simulating the stored beam dynamics. A new method is introduced to reduce a critical systemic caused by time dependence in the stored beam momentum, enabled by a detector which directly profiles the stored beam. Finally the analysis of $\tilde{\omega}&s;_p$, the muon-weighted magnetic field, for the Run-2/3 result is presented. Systematics of $\tilde{\omega}&s;_p$ due to beam effects are evaluated in detail, and shown to be sub-dominant.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Open-source generation of sigma profiles: impact of quantum chemistry and solvation treatment on machine learning performance

The combination of machine learning (ML) models with chemistry-related tasks requires the description of molecular structures in a machine-readable way. The nature of these so-called molecular descriptors has a direct and major impact on the performance of ML models and remains an open problem in the field. Structural descriptors like SMILES strings or molecular graphs lack size-independence and can be memory intensive. Machine-learned descriptors can be of low dimensionality and constant size but lack physical significance and human interpretability. Sigma profiles, which are unnormalized histograms of the surface charge distributions of solvated molecules, combine physical significance with low dimensionality and size-independence, making them a suitable candidate for a universal molecular descriptor. However, their widespread adoption in ML applications requires open access to sigma profile generation, which is currently not available. This work details the development of OpenSPGen – an open-source tool for generating sigma profiles. Also presented are studies on the effect of different settings on the efficacy of the generated sigma profiles at predicting thermophysical material properties when used as inputs to a Gaussian process as a simple surrogate ML model. We find that a higher level of theory does not translate to more accurate results. We also provide further recommendations for sigma profile calculation and use in ML models.

Salih, Fathya Y. M. [University of Notre Dame, IN ↗
DOE OSTI2024

Dynamics of inspiraling dark energy

Abstract We investigate the dynamics of a multifield dark energy model, which arises from certain rapid-turning and inspiraling trajectories in field space. We find the speed of sound $$c_s$$ c s of the dark energy perturbations around the background and show that $$c_s$$ c s is monotonically decreasing with time. Furthermore, it has a positive-definite lower bound that implies a certain clustering scale. We also extend the previously known background solution for dark energy to an exact solution that includes matter. This allows us to address the implications of our model for two cosmological tensions. More precisely, we argue that the $$\sigma _8$$ σ 8 tension can be alleviated generically, while reducing the Hubble tension requires certain constraints on the parameter space of the model. Notably, a necessary condition for alleviating the Hubble tension is that the transition from matter domination to the dark energy epoch begins earlier than in $$\Lambda $$ Λ CDM.

Anguelova, Lilia↗
DOE OSTI2025

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗
DOE OSTI2024

High-Throughput Screening and Accurate Prediction of Ionic Liquid Viscosities Using Interpretable Machine Learning

Ionic liquids (ILs) are a novel group of green solvents with great promise for various industrial applications, including carbon capture and lignocellulosic biomass deconstruction. However, the use of ILs at the industrial scale remains challenging due to their high viscosities at ambient temperatures. To develop ILs with lower viscosities, a systematic study of their quantitative structure–property relationship (QSPR) is desirable. Here, we developed four machine learning (ML) models to predict viscosity at various temperature and pressure ranges, trained over a wide range of ILs consisting of various cationic and anionic families. ML methods including two-factor polynomial regression (two-factor PR), support vector regression (SVR), feed-forward neural networks (FFNN), and categorical boosting (CATBoost) were developed based on features that have proven useful in previous ML studies: COSMO-RS (conductor-like screening model for real solvents)-derived surface screening charge densities (sigma profiles). FFNN and CATBoost were the most accurate in predicting IL viscosities with lower average absolute relative deviation and higher R2 values on the test set. Tanimoto similarity scores were calculated to characterize the chemical space and structural similarity of the investigated ions. Furthermore, SHapley Additive exPlanation (SHAP) analysis was employed to interpret the ML results. Temperature, the polar area of ILs, and the nonpolar regions of ions are key features that influence the viscosity predictions. Importantly, the IL viscosity prediction here is the most accurate reported to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗