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At least 289 records · Page 16

Dark Energy Survey Year 6 Results: improved mitigation of spatially varying observational systematics with masking

As photometric surveys reach unprecedented statistical precision, systematic uncertainties increasingly dominate large-scale structure probes relying on galaxy number density. Defining the final survey footprint is critical, as it excludes regions affected by artefacts or suboptimal observing conditions. For galaxy clustering, spatially varying observational systematics, such as seeing, are a leading source of bias. Template maps of contaminants are used to derive spatially dependent corrections, but extreme values may fall outside the applicability range of mitigation methods, compromising correction reliability. The complexity and accuracy of systematics modelling depend on footprint conservativeness, with aggressive masking enabling simpler, robust mitigation. We present a unified approach to define the DES Year 6 joint footprint, integrating observational systematics templates and artefact indicators that degrade mitigation performance. This removes extreme values from an initial seed footprint, leading to the final joint footprint. By evaluating the DES Year 6 lens sample MagLim++ plus plus on this footprint, we enhance the Iterative Systematics Decontamination (ISD) method, detecting non-linear systematic contamination and improving correction accuracy. While the mask's impact on clustering is less significant than systematics decontamination, it remains non-negligible, comparable to statistical uncertainties in certain w(theta) scales and redshift bins. Supporting coherent analyses of galaxy clustering and cosmic shear, the final footprint spans 4031.04 deg2, setting the basis for DES Year 6 1x2pt, 2x2pt, and 3x2pt analyses. This work highlights how targeted masking strategies optimise the balance between statistical power and systematic control in Stage-III and -IV surveys.

Rodríguez-Monroy, M. [Madrid, IFT; IJCLab, Orsay]↗

The Dark Energy Bedrock All-sky Supernova Program: Cross Calibration, Simulations, and Cosmology Forecasts

Type Ia supernovae (SNe Ia) have been essential for probing the nature of dark energy; however, most SN analyses rely on the same low-redshift sample, which may lead to shared systematics. In a companion paper, we introduce the Dark Energy Bedrock All-Sky Supernova (DEBASS) program, which has already collected more than 500 low-redshift SNe Ia on the Dark Energy Camera, and present an initial release of 77 SNe Ia within the Dark Energy Survey (DES) footprint observed between 2021 and 2024. Here, we examine the systematics, including photometric calibration and selection effects. We find agreement at the 10 mmag level among the tertiary standard stars of DEBASS, DES, and Pan-STARRS1. Our simulations reproduce the observed distributions of DEBASS SN light-curve properties, and we measure a bias-corrected Hubble residual scatter of 0.08 mag, which, while small, is found in 10% of our simulations. We compare the DEBASS SN distances to the Foundation sample and find consistency with a median residual offset of 0.016 ± 0.019 mag. Selection effects have negligible impacts on distances, but a different photometric calibration solution shifts the median residual −0.015 ± 0.019 mag, highlighting calibration sensitivity. Using conservative simulations, we forecast that replacing historical low-redshift samples with the full DEBASS sample will improve the statistical uncertainties on dark energy parameters w 0 and w a by 30% and 24%, respectively, enhance the dark energy Figure of Merit by up to 60%, and enable a measurement of fσ 8 at the 25% level.

Acevedo, Maria [Duke Univ., Durham, NC (United Sta↗

Choline Fluoride-Ethylene glycol deep eutectic solvent mixture – Synthesis and physicochemical properties

A critical factor in achieving tunability in DESs is varying the type of hydrogen bond acceptors (HBAs) and donors (HBDs). Choline halides (ChX), such as ChCl and ChBr, have been studied to investigate the effect of the choline anion on DESs. However, ChF-based DESs have been underrepresented in scientific research. ChF has excellent potential, such as high electron affinity, ionization potential, and strong hydrogen bond interactions. Moreover, ChF-based DES can lead to a deeper understanding of DESs due to the NMR-active 19F nuclear spin nature. We report the first synthesis and characterization of choline fluoride-EG (1:2, ChF:EG) DES, which we named “EthalineF.” We studied this mixture using various spectroscopic techniques, including NMR, FT-IR, Raman, and UV–vis spectroscopies. Polarity, density, viscosity, and conductivity measurements were collected as well. Transient absorption spectroscopy (TAS) was used to study the solvation dynamics of EthalineF. 19F NMR indicated that some fluoride anions (~15%) are coordinated to the choline cation. In EthalineF, the new type of observed fluoride anions is proposed to be a tight-binding choline-fluoride ion pair. Further, EthalineF has a larger solvodynamic radius than Ethaline. This can explain the lower conductivity for EthalineF compared to Ethaline despite the higher fluidity and solvation dynamics for EthalineF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Facile Degumming Method of Kenaf Fibers Using Deep Eutectic Solution

An eco-friendly and effective degumming method needed to be developed for producing kenaf bast fibers. As such, this study devised a novel deep eutectic solvent (DES) method coupled with microwave and alkaline-ultrasonic treatment. The novel method could effectively remove the gummy matters, providing a smooth and clean fiber surface. The properties of the fibers were assessed including chemical compositions, surface structure, crystallinity index (66.68%) and thermal properties. The residual gum content (9.419%), fiber fineness (4.125tex), breaking tenacity (13.650 cn/tex) of the refined dry fibers produced by the novel treatment were comparable with the fibers produced by the traditional two-step alkali boiling method. Besides, the novel method could reduce the usage of chemical, water and time by 48.9%, by 66.7% and 66.8%, respectively. These results revealed that the novel combined DES pretreatment is a practical and feasible pretreatment method for kenaf bast degumming, demonstrating its facile, green energy-saving and fast properties in the degumming process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dark Energy Survey Year 3 results: Imprints of cosmic voids and superclusters in the Planck CMB lensing map

ABSTRACT The CMB lensing signal from cosmic voids and superclusters probes the growth of structure in the low-redshift cosmic web. In this analysis, we cross-correlated the Planck CMB lensing map with voids detected in the Dark Energy Survey Year 3 (Y3) data set (∼5000 deg2), expanding on previous measurements that used Y1 catalogues (∼1300 deg2). Given the increased statistical power compared to Y1 data, we report a 6.6σ detection of negative CMB convergence (κ) imprints using approximately 3600 voids detected from a redMaGiC luminous red galaxy sample. However, the measured signal is lower than expected from the MICE N-body simulation that is based on the ΛCDM model (parameters Ωm = 0.25, σ8 = 0.8), and the discrepancy is associated mostly with the void centre region. Considering the full void lensing profile, we fit an amplitude $A_{\kappa }=\kappa _{{\rm DES}}/\kappa _{{\rm MICE}}$ to a simulation-based template with fixed shape and found a moderate 2σ deviation in the signal with Aκ ≈ 0.79 ± 0.12. We also examined the WebSky simulation that is based on a Planck 2018 ΛCDM cosmology, but the results were even less consistent given the slightly higher matter density fluctuations than in MICE. We then identified superclusters in the DES and the MICE catalogues, and detected their imprints at the 8.4σ level; again with a lower-than-expected Aκ = 0.84 ± 0.10 amplitude. The combination of voids and superclusters yields a 10.3σ detection with an Aκ = 0.82 ± 0.08 constraint on the CMB lensing amplitude, thus the overall signal is 2.3σ weaker than expected from MICE.

79 ASTRONOMY AND ASTROPHYSICS↗

Autonomous Operations for Advanced Reactors Utilizing Supervisory Control

Automation is a critical tenet of reactor plant operations as reliance on nuclear energy increases. Nuclear power plants require a large workforce which does not scale with output; that is, the cost per megawatt increases as reactor output becomes smaller. The economic viability of advanced reactors, particularly small modular reactors (SMRs) and microreactors, requires a significantly reduced onsite workforce. The logical solution is establishing a systematic process of elimination of reliance on human operators, and to the extent possible, replacing these actions with automated functions. In this paper, we propose a method for such transformation to establish a robust technical basis to enable transition to autonomy. Our method is based on finite state automata (FSA)—also known as finite state machines (FSMs). Relying on this method allows us to exploit the rich set of mathematical proofs available in the field of regular languages. FSA are one of the mathematical tools to model discrete event systems (DES). These properties are applied to produce an automated startup controller for the Massachusetts Institute of Technology Research Reactor (MITR). The startup procedure is captured in terms of discrete changes from one state to another while an independent supervisory control system directs the sequence of states and alerts a human in the event of an abnormal operation. First, the design and behavior of the MITR rod control system were modeled in Simulink. Then, the startup procedure was applied to the rod control system and the DES performed a startup by procedurally withdrawing rods to the subcritical position. The simulation also stops rod motion in response to an uncontrollable event and restarts rod motion once the event has been cleared.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Automatisierte Generierung von Mikrokinetiken für heterogen katalysierte Reaktionen unter Berücksichtigung korrelierter Unsicherheiten**

Abstract Die Studie stellt eine ab initio basierte Methode für die automatische Konstruktion von detaillierten Mikrokinetiken vor, welche korrelierte Unsicherheiten in allen energetischen Parametern und Schätzroutinen berücksichtigt. Hierfür wurden innerhalb des Unsicherheitsraums des BEEF‐vdW Funktionals 2000 Mikrokinetiken für die Oxidationsreaktionen repräsentativer Abgasemissionen von stöchiometrischen Verbrennungsmotoren auf Pt(111) generiert und durch Multiskalenmodellierung mit Experimenten verglichen. Das Ensemble der Simulationsergebnisse unterstreicht die Bedeutung der Berücksichtigung von Unsicherheiten. Innerhalb dieses Ensembles ist es möglich, eine Mikrokinetik zu identifizieren, welche mit den experimentellen Daten übereinstimmt. Diese Mikrokinetik lässt sich auf ein einziges Austausch‐Korrelations‐Funktional zurückführen und legt nahe, dass Pt(111) das aktive Zentrum für die Oxidation leichter Kohlenwasserstoffe sein könnte. Die Studie bietet einen universellen Rahmen für die automatisierte Konstruktion von Reaktionsmechanismen unter Berücksichtigung korrelierter Unsicherheiten und ermöglicht eine DFT‐basierte Optimierung der Mikrokinetik auch für andere heterogen katalysierte Systeme.

Kreitz, Bjarne↗

Thermodynamic Framework for Water in Deep Eutectic Solvents and Ionic Liquids

Water is widely recognized as critical to the tunability and electrochemical stability of nonaqueous solvents such as deep eutectic solvents (DESs) and ionic liquids (ILs). Traditionally, the water content of these solvents has been controlled by either drying or adding small amounts of water to control their bulk properties to meet specific application requirements. The total water content by itself, does not provide sufficient information about the chemical reactivity and molecular interactions within DES– and IL–water mixtures. In this concept article, water activity is highlighted as a thermodynamically more rigorous descriptor to quantify the influence of the co‐solvent water on DES– and IL–water mixtures. Water activity relates measurable physical properties, such as vapor pressure, density, viscosity, electrochemical stability, and conductivity of DESs and ILs to the underlying molecular interactions between their components. Furthermore, water activity of DESs and ILs correlates with changes in local solvent structures and thermodynamic excess properties, including excess molar volume, enthalpy, and Gibbs energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measuring Solvation Interactions of Deep Eutectic Solvents Formed by Metal Chlorides and an Imidazolium Salt by Inverse Gas Chromatography

Deep eutectic solvents (DESs) represent a class of solvents that offer a number of advantages including minimal toxicity, affordability, low vapor pressure, and simple, environmentally friendly preparation methods. They have found utility in areas, such as gas absorption, metal plating, and extractions. However, the relationship between their solvation properties and chemical composition remains poorly understood. In this study, a broad range of Type I DESs composed of metal chlorides and an imidazolium salt were prepared, employed as gas chromatographic stationary phases, and characterized using the Abraham solvation parameter model by inverse gas chromatography. The Abraham solvation parameter model allows for the study of DES solvation properties and the effects of varying structural components on system constants using a linear-free energy relationship. The DESs were investigated by systematically varying their composition, including the type of metal chloride and the molar ratio between the metal chloride and the imidazolium salt. The results show that hydrogen bond acidity, hydrogen bond basicity, and dipolarity/polarizability interactions are strongly influenced by the type of metal chloride within the DES and the ratio of metal chloride to imidazolium salt in the eutectic mixture. Furthermore, a column pretreatment procedure is presented that enables the effective coating of highly polar DESs onto open tubular capillary gas chromatography columns.

deep eutectic solvent↗

Facilitating enzymatic hydrolysis with a novel guaiacol-based deep eutectic solvent pretreatment

In this work, we established a novel deep eutectic solvent (DES) using lignin-derived guaiacol as hydrogen bond donor (HBD). The sole ChCl/guaiacol system was found to be inefficient for the fractionation of wheat straw (WS), while the incorporation of trace AlCl 3 significantly facilitated the degradation of hemicellulose and lignin, resulting in a complete enzymatic digestibility of the pretreated WS. Further, this study revealed that the DES-degraded lignin was readily precipitated during the washing process, and thus hindered the enzymatic hydrolysis of poplar and bamboo (with hydrolysis yield of 42.03% and 71.67%, respectively). Alkali washing offers a possible approach to remove the precipitated lignin, after which a near 100% hydrolysis yield was also obtained for poplar and bamboo.

59 BASIC BIOLOGICAL SCIENCES↗

Synergistic effect of dual Brønsted acidic deep eutectic solvents for oxidative desulfurization of diesel fuel

Deep eutectic solvents (DESs) are generally used as attractive solvents or extractants rather than catalysts in the field of synthesis and separation. Herein, dual Brønsted acidic DESs were prepared by mixing sulfonated quaternary ammonium and oxalic acid as extractants and catalysts for deep oxidative desulfurization. Compared to the DESs with single acidic group, the dual acidic DESs exhibited much higher catalytic activity likely due to the synergistic effect. The 1 H NMR study indicated that the weak interaction between DES and sulfur compounds led to a low extraction capacity. However, the sulfur removal could reach 97.7% under optimized reaction conditions. Density functional theory (DFT) calculations demonstrated that sulfonic group and carboxylic group are of equal importance to desulfurization performance. Further, the desulfurization efficiency was also strongly affected by the viscosity of DESs. Here, we put forward a new strategy that the reaction time could be sharply shortened to 40 min and 100 min by adding low viscous acetonitrile and polyethylene glycol into DES to form mixing reaction system, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep eutectic solvents as green and sustainable diluents in headspace gas chromatography for the determination of trace level genotoxic impurities in pharmaceuticals

Genotoxic impurities (GTIs) are potential carcinogens that need to be controlled down to ppm or lower concentration levels in pharmaceuticals under strict regulations. The static headspace gas chromatography (HS-GC) coupled with electron capture detection (ECD) is an effective approach to monitor halogenated and nitroaromatic genotoxins. Deep eutectic solvents (DESs) possess tunable physico-chemical properties and low vapor pressure for HS-GC methods. In this study, zwitterionic and non-ionic DESs have been used for the first time to develop and validate a sensitive analytical method for the analysis of 24 genotoxins at sub-ppm concentrations. Compared to non-ionic diluents, zwitterionic DESs produced exceptional analytical performance and the betaine: 7 (1,4- butane diol) DES outperformed the betaine: 5 (1,4-butane diol) DES. Limits of detection (LOD) down to the 5-ppb concentration level were achieved in DESs. Wide linear ranges spanning over 5 orders of magnitude (0.005–100 µg g –1 ) were obtained for most analytes with exceptional sensitivities and high precision. The method accuracy and precision were validated using 3 commercially available drug substances and excellent recoveries were obtained. Finally, this study broadens the applicability of HS-GC in the determination of less volatile GTIs by establishing DESs as viable diluent substitutes for organic solvents in routine pharmaceutical analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the consistency of cosmological contours for supernova cosmology

As the scale of cosmological surveys increases, so does the complexity in the analyses. This complexity can often make it difficult to derive the underlying principles, necessitating statistically rigorous testing to ensure the results of an analysis are consistent and reasonable. This is particularly important in multi-probe cosmological analyses like those used in the Dark Energy Survey (DES) and the upcoming Legacy Survey of Space and Time, where accurate uncertainties are vital. In this paper, we present a statistically rigorous method to test the consistency of contours produced in these analyses and apply this method to the Pippin cosmological pipeline used for type Ia supernova cosmology with the DES. We make use of the Neyman construction, a frequentist methodology that leverages extensive simulations to calculate confidence intervals, to perform this consistency check. A true Neyman construction is too computationally expensive for supernova cosmology, so we develop a method for approximating a Neyman construction with far fewer simulations. We find that for a simulated dataset, the 68% contour reported by the Pippin pipeline and the 68% confidence region produced by our approximate Neyman construction differ by less than a percent near the input cosmology; however, they show more significant differences far from the input cosmology, with a maximal difference of 0.05 in $Ω$ M and 0.07 in w. In conclusion, this divergence is most impactful for analyses of cosmological tensions, but its impact is mitigated when combining supernovae with other cross-cutting cosmological probes, such as the cosmic microwave background.

79 ASTRONOMY AND ASTROPHYSICS↗

Scanning Electrochemical Microscopy for Kinetic Investigations in Viscous Deep Eutectic Solvents: Identifying Practical Approach Curves and Deviations from Electron Transfer Models

Determining heterogeneous electrochemical electron transfer (ET) kinetics in electrolytes with a wide range of physical properties is of great interest for achieving high-performance redox flow batteries. Among such electrolytes, concentrated hydrogen-bonded electrolytes (CoHBEs), including deep eutectic solvents (DESs), have recently garnered significant attention. Unfortunately, traditional Tafel analysis using macroelectrodes often encounters issues with mass transfer limitations in CoHBEs with high viscosities, thereby restricting kinetic analysis to a narrow potential window. Here, in this work, we introduce a methodology for evaluating ET kinetics in viscous DES using the scanning electrochemical microscopy (SECM). We first determined practical solutions to SECM tip positioning in ethaline DES, which yield pseudopositive feedback responses. Lattice Boltzmann method (LBM) simulations helped us rationalize the impact of the fluid and concentration fields, as well as tip geometry, tip approach velocity v, and the solvent viscosity ηs, on the shape of the approach curves. In addition to successfully recreating approach curves over a variety of conditions, we found that approaching a conductor ensured a practical point where the normalized tip response (Ni T = 2) converged at L = 0.7 within ∼10% error regardless of tip velocity. With positioning capabilities at hand, we investigated the kinetics of Fe 3+ /Fe 2+ redox couple in aqueous and the ethaline media. The experimental kinetic results were interpreted using the Butler–Volmer (BV) and Marcus–Hush–Chidsey (MHC) models. For ethaline, a nonideal kinetic behavior was observed, potentially attributed to solvent dynamics within DESs or to the interplay of chloride anions in the charge transfer process.

electrodes↗

Deep Eutectic Solvents for Pretreatment of Lignocellulose Biomass: Physical Properties, Solubility Mechanisms, and Their Interactions

As the most accessible and abundant renewable resource on earth, lignocellulosic biomass mainly consists of cellulose, hemicelluloses, and lignin with a small amount of protein, pectin, minerals, and extractives (e.g., tannins, lipids, and resins). Lignocellulosic biomass has gained extensive attention in industry and research owing to its renewability, availability, and low cost. However, achieving efficient fractionation of lignocellulose components and all-component utilization in a green and cost-effective manner remains a challenge dueto biomass recalcitrance. Deep eutectic solvents (DESs) have received considerable attention because they are biocompatible, inexpensive, biodegradable, have low toxicity, and are easy to prepare and recycle; these characteristics strongly depend on individual components involved in DESs preparation. This review systematically summarizes recent progress in the fractionation of carbohydrates (cellulose and hemicelluloses) and lignin from biomass using DESs, with particular emphasis on the effects of DES types and pretreatment parameters on fractionation efficiency. The subsequent conversion and upgrading of the DES-fractionated products (i.e., carbohydrates and lignin) are comprehensively analyzed. Finally, the challenges and future prospects of lignocellulose biomass fractionation using DESs are proposed in view of the existing limitations. This review provides an in-depth understanding of lignocellulose biomass fractionation during DESs processing, offering insights to improve current pretreatment methods and/or to explore new pretreatment methods aimed at mitigating the global energy crisis.

Mqoni, Ntebogeng [North-West University (Mafikeng ↗

Impacts of Hydrogen Bond Donor Structures in Phenolic Aldehyde Deep Eutectic Solvents on Pretreatment Efficiency

As a green solvent for biomass processing, deep eutectic solvents (DESs) have shown effectiveness in biomass processing. Here, in this study, phenolic aldehydes with different numbers of methoxy groups, including 4-hydroxybenzaldehyde (HBA, no methoxy), vanillin (VA, monomethoxy), and syringaldehyde (SA, dimethoxy) were employed to synthesize DESs with choline chloride (ChCl). The presence of methoxy groups in the hydrogen bond donor structure affected DES properties, as well as biomass pretreatment performance. The high thermal stability of phenolic aldehyde DESs was shown with over 225 °C onset temperature. The hydrogen bond donor with one aldehyde and one hydroxyl group at the para position without a methoxy group (ChCl-HBA) showed the highest xylan removal and delignification, reaching 59.3 and 88.0%, respectively, leading to the highest enzymatic hydrolysis yield. Sonication after pretreatment further enhanced the hydrolysis yields, achieving 83.3% glucan conversion and 50.1% xylan conversion. In the lignin-rich fraction, the recovered lignin showed a low weight–average molecular weight under 2100 g/mol with a relatively uniform molecular weight dispersity below 1.5. This study provides insights into how the chemical structure of hydrogen bond donors in DESs affects biomass processing and paves the way for designing effective lignin-derived DES in future biorefinery processes.

09 BIOMASS FUELS↗

Accurate Machine Learning for Predicting the Viscosities of Deep Eutectic Solvents

Deep eutectic solvents (DESs) are emerging as environmentally friendly designer solvents for mass transport and heat transfer processes in industrial applications; however, the lack of accurate tools to predict and thus control their viscosities under both a range of environmental factors and formulations hinders their general application. While DESs may serve as designer solvents, with nearly unlimited combinations, this unfortunately makes it experimentally infeasible to comprehensively measure the viscosities of all DESs of potential industrial interest. To assist in the design of DESs, we have developed several new machine learning (ML) models that accurately and rapidly predict the viscosities of a diverse group of DESs at different temperatures and molar ratios using, to date, one of the most comprehensive data sets containing the properties of over 670 DESs over a wide range of temperatures (278.15–385.25 K). Three ML models, including support vector regression (SVR), feed forward neural networks (FFNNs), and categorical boosting (CatBoost), were developed to predict DES viscosity as a function of temperature and molar ratio and contrasted with multilinear and two-factor polynomial regression baselines. Further, quantum chemistry-based, COSMO-RS-derived sigma profile (σ-profile) features were used as inputs for the ML models. The CatBoost model is excellent at externally predicting DES viscosity, as indicated by high R 2 (0.99) and low root-mean-square-error (RMSE) and average absolute relative deviations (AARD) (5.22%) values for the testing data sets, and 98% of the data points lie within the 15% of AARD deviations. Furthermore, SHapley additive explanation (SHAP) analysis was employed to interpret the ML results and rationalize the viscosity predictions. The result is an ML approach that accurately predicts viscosity and will aid in accelerating the design of appropriate DESs for industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamics of Glyceline and Interactions of Constituents: A Multitechnique NMR Study

In this work, the dynamics of the organic components of the deep eutectic solvent (DES) glyceline are analyzed using an array of complementary nuclear magnetic resonance (NMR) methods. Fast-Field Cycling 1 H relaxometry, Pulsed Field Gradient diffusion, Nuclear Overhauser Effect Spectroscopy (NOESY), 13 C NMR relaxation and pressure dependent NMR experiments are deployed to sample a range of frequencies and modes of motion of the glycerol and choline components of the DES. Generally, translational and rotational diffusion of glycerol are more rapid than those of choline while short range rotational motions observed from 13 C relaxation indicate slow local motion of glycerol at low choline chloride (ChCl) content. The rates of glycerol and choline local motions become more similar at higher ChCl. This result taken together with pressure dependent NMR studies show that the addition of ChCl makes it easier to disrupt glycerol packing. Finally, a relatively slow hydroxyl H-exchange process between glycerol and choline protons is deduced from the data. Consistent with this, NOESY results indicate relatively little direct H-bonding between glycerol and choline. These results suggest that the glycerol H-bonding network is disrupted as choline is added, but primarily in regions where there is intimate mixing of the two components. Thus, the local dynamics of most of the glycerol, resembles that of pure glycerol until substantial choline chloride is present.

13C NMR relaxation↗