Molecular Glass Formers Research Articles

Importance of Experiments That Can Test Theories Critically.

General dynamic and thermodynamic properties of complex materials, including amorphous polymers and molecular glass-formers, have been established from the wealth of experimental data accumulated over the years. Naturally, these general properties attract researchers to construct theories and models to address and explain them. Often more than one theory with contrasting or even conflicting theoretical bases can equally explain a general property rather well. The correct explanation becomes unclear, and progress is stopped. The resolution of the problem comes when an innovative experiment is performed with insightful results that can critically test the premise and assumptions of each theory. This important role played by experimentalists is exemplified by the contributions of Mark Ediger in several general properties considered in this paper: (1) dynamics of the components in binary polymer blends; (2) breakdown of the Stokes-Einstein and the Debye-Stokes-Einstein relations; (3) enhancement of surface mobility and in relation to formation of ultrastable glasses; and (4) the Johari-Goldstein β-relaxation in ultrastable glasses. Different theories proposed to explain these properties are discussed, including the Coupling Model of the author.

Normal-to-Supercooled Liquid Transition in Molecular Glass-Formers: A Hidden Structural Transformation Fuelled by Conformational Interconversion.

Molecular dynamics and transport coefficients change significantly around the so-called Arrhenius crossover in glass-forming systems. In this article, we revisit the dynamic processes occurring in a glass-forming macrocyclic crown thiaether MeBzS2O above its glass transition, revealing two crossover temperatures: TB at 309 and TA at 333 K. We identify the second one as the Arrhenius crossover that is closely related to the normal-to-supercooled liquid transition in this compound. We show that the transformation occurring at this point goes far beyond molecular dynamics (where the temperature dependence of structural relaxation times changes its character from activation-like to super-Arrhenius), being reflected also in the internal structure and diffraction pattern. In this respect, we found a twofold local organization of the nearest-neighbor molecules via weak van der Waals forces, without the formation of any medium-range order or mesophases. The nearest surrounding of each molecule evolves structurally in time due to the ongoing fast conformational changes. We identify several conformers of MeBzS2O, demonstrating that its lowest-energy conformation is preferred mainly at lower temperatures, i.e., in the supercooled liquid state. Its increased prevalence modifies locally the short-range intermolecular order and promotes vitrification. Consequently, we indicate that the Arrhenius transition is fuelled rather by conformational changes in this glass-forming macrocyclic crown thiaether, which is a different scenario from the so-far existing concepts. Our studies combine broadband dielectric spectroscopy (BDS), X-ray diffraction, Fourier transform infrared (FTIR) spectroscopy, molecular dynamics (MD) simulations, and density functional theory (DFT) calculations.

Transfer learning-driven artificial intelligence model for glass transition temperature estimation of molecular glass formers mixtures

Predicting binary mixtures' glass transition temperature (Tg) is crucial in various fields, particularly for industrial materials affected by this property during production processes and in service-life. On the other hand, from the fundamental point of view, this predictive capability is relevant for understanding the chemical interactions between the two components and how this affects the Tg of the mixture. In this sense, some models provide different approaches for describing the Tg of the mixture. Among them, the Gordon-Taylor approach has been widely used since it only relies on the relationship between the Tg of the pure components, their weight fraction, and only one fitting parameter. Although simple, this approach still requires measurements of Tg of the pure components and at least some intermediated composition for the fitting procedure. In a previous work, our research has focused on neural networks methods for predicting Tg values directly from the chemical structure of monomers and molecules, but the scarcity of experimental data for binary mixtures limits the application of a similar approach. To address this problem, we propose to use in this work a transfer learning method that relays on the previous acquired knowledge of the chemical structure - Tg relationship, for the prediction of the Tg of the binary mixtures. Therefore, pure component characteristics are derived from chemical fingerprints originated in a pre-trained network, and enables a training process focused on their behavior within the mixtures. This approach successfully estimated K with very low deviations, even allowing for the exploration of the embedded chemical structure's relation to previously unknown mixtures.

Glass spectrum, excess wing phenomenon, and master curves in molecular glass formers: A multi-method approach.

The relaxation spectra of glass formers solely displaying an α-peak and excess wing contribution collected by various methods are reanalyzed to pin down their different spectral evolution. We show that master curve construction encompassing both α-peak and emerging excess wing works for depolarized light scattering (DLS) and nuclear magnetic resonance (NMR) relaxometry. It reveals the self-part of the slow dynamics' spectrum. Master curves are to be understood as a result of a more extensive scaling covering all temperatures instead of strict frequency-temperature superposition. DLS and NMR display identical relaxation spectra; yet, comparing different systems, we do not find a generic structural relaxation at variance with recent claims. Dielectric spectroscopy (DS) spectra show particularities, which render master curve construction obsolete. The DS α-peak is enhanced or suppressed with respect to that of DLS or NMR, yet, not correlated to the polarity of the liquid. Attempting to single out the excess wing from the overall spectrum discloses a stronger exponential temperature dependence of its amplitude compared to that below Tg and a link between its exponent and that of the fast dynamics' spectrum. Yet, such a decomposition of α-peak and excess wing appears to be unphysical. Among many different glasses, the amplitude of the excess wing power-law spectrum is found to be identical at Tg, interpreted as a relaxation analog to the Lindemann criterion.

Nature of Subdiffusion Crossover in Molecular and Polymeric Glassformers.

A crossover from a non-Gaussian to Gaussian subdiffusion has been observed ubiquitously in various polymeric and molecular glassformers. We have developed a framework that generalizes the fractional Brownian motion model to incorporate non-Gaussian features by introducing a jump kernel. We illustrate that the non-Gaussian fractional Brownian motion model accurately characterizes the subdiffusion crossover. From the solutions of the non-Gaussian fractional Brownian motion model, we gain insights into the nature of van Hove self-correlation in non-Gaussian subdiffusive regime, which is found to exhibit exponential tails, providing first such experimental evidence in molecular glassformers. The validity of the model is supported by comparison with incoherent quasielastic neutron scattering data obtained from several molecular and polymeric glassformers.

The slow Arrhenius process in small organic molecules.

Equilibration, the complex set of molecular rearrangements leading to more stable states, is usually dominated by density fluctuations, occurring through the structural (α-)relaxation, whose timescale quickly increases upon cooling. Growing evidence shows, however, that equilibration can be reached also through an alternative pathway provided by the Slow Arrhenius process (SAP), a molecular mode slower than the structural processes in the liquid state and faster in glass. The SAP, widely observed in polymers, has not yet been reported in small molecules, probably because of the larger experimental difficulties in handling these systems. Here, we report the presence of the SAP in three different molecular glassformers, by investigating these systems in the thin film geometry via dielectric spectroscopy. These results reinforce the idea that the SAP is a universal feature of liquid and glassy dynamics.

Molecular Dynamics and Near-Tg Phenomena of Cyclic Thioethers.

This article presents the synthesis and molecular dynamics investigation of three novel cyclic thioethers: 2,3-(4'-methylbenzo)-1,4,7,10-tetrathiacyclododeca-2-ene (compound 1), 2,3,14,15-bis(4',4″(5″)-methylbenzo)-1,4,7,10,13,16,19,22,25-octathiacyclotetracosa-2,14-diene (compound 2), and 2,3,8,9-bis(4',4″(5″)-methylbenzo)-1,4,7,10-tetrathiacyclododeca-2,8-diene (compound 3). The compounds exhibit relatively high glass transition temperatures (Tg), which range between 254 and 283 K. This characteristic positions them within the so-far limited category of crown-like glass-formers. We demonstrate that cyclic thioethers may span both the realms of ordinary and sizeable molecular glass-formers, each featuring distinct physical properties. Furthermore, we show that the Tg follows a sublinear power law as a function of the molar mass within this class of compounds. We also reveal multiple dielectric relaxation processes of the novel cyclic thioethers. Above the Tg, their dielectric loss spectra are dominated by a structural relaxation, which originates from the cooperative reorientation of entire molecules and exhibits an excess wing on its high-frequency slope. This feature has been attributed to the Johari-Goldstein (JG) process. Each investigated compound exhibits also at least one intramolecular secondary non-JG relaxation stemming from conformational changes. Their activation energies range from approximately 19 kJ/mol to roughly 40 kJ/mol. Finally, we analyze the high-pressure molecular dynamics of compound 1, revealing a pressure-induced increase in its Tg with a dTg/dp coefficient equal to 197 ± 8 K/GPa.

Characterising the glass transition temperature-structure relationship through a recurrent neural network

Quantitative structure-property relationship (QSPR) is a powerful analytical method to find correlations between the structure of a molecule and its physicochemical properties. The glass transition temperature (Tg) is one of the most reported properties, and its characterisation is critical for tuning the physical properties of materials. In this work, we explore the use of machine learning in the field of QSPR by developing a recurrent neural network (RNN) that relates the chemical structure and the glass transition temperature of molecular glass formers. In addition, we performed a chemical embedding from the last hidden layer of the RNN architecture into an m-dimensional Tg-oriented space. Then, we test the model to predict the glass transition temperature of essential amino acids and peptides. The results are very promising and they can open the door for exploring and designing new materials.

One experiment makes a direct comparison of structural recovery with equilibrium relaxation.

For a molecular glass-former, propylene glycol, we directly compare the equilibrium fluctuations, measured as "structural" relaxation in the regime of linear response, with structural recovery, i.e., field induced physical aging in the limit of a small perturbation. The two distinct correlation functions are derived from a single experiment. Because the relaxation time changes only 2% during structural recovery, no aging model is needed to analyze the results. Although being conceptually different processes, dielectric relaxation and recovery dynamics are observed to be identical for propylene glycol, whereas single-particle dynamics as seen by photon correlation spectroscopy are significantly faster. This confirms the notion that structural recovery and aging are governed by all modes observed by dielectric spectroscopy, i.e., including cross correlations, not only by single-particle dynamics. A comparison with analogous results for other materials suggests that the relation between relaxation and recovery time scales may be material specific rather than universal.

Understanding the difference in the stretched structural relaxations probed by dielectric and enthalpic studies of glass forming substances.

We investigated the stretched dynamics of the structural relaxation in molecular glass formers by using dielectric and thermal (or enthalpic) relaxations. The dielectric stretching exponents βdie are determined by the Havriliak-Negami function, while the enthalpic βTNMH is quantified by using the Tool-Narayanaswamy-Moynihan-Hodge formalism. We found βTNMH is anticorrelated with the degree of freedom, a molecule addressed by the concept of beads. Referring to the reported relation of βdie to the dipole moment μ, we proposed a combined parameter of μ2*beads, which can rationalize the difference in stretching exponents obtained by dielectric and enthalpic relaxations. For the majority of glass-forming molecules, the difference is trivial, but for those molecules with both unusually high dipole moments and flexibility, a large difference is obvious. The interplay of the degree of freedom and dielectric dipole-dipole interaction in molecular dynamics is addressed.

Fast differential scanning calorimetry: new solutions in data treatment and applications to molecular glass-formers

Fast scanning calorimetry is an experimental technique very appreciated for its capability of suppressing reorganization processes, thanks to its wide interval of scanning rates, several orders higher than that of conventional calorimeters; nevertheless, drawbacks still exist. In this paper we propose a novel way to estimate the dynamical thermal lag by using the temperatures of maximum slope of the heat flow through the glass transition when we are not in the optimal conditions to apply the existing methods based on a reference material added on both cells of the chip or on the fictive temperature. Moreover, a novel interpretation of the heat flow losses due to the sample depending on the scanning rate sign is provided, in order to rescale the measured specific heat capacity to that from conventional calorimetry. Finally, the use of the glass to liquid transition measured on heating is shown as a new manner to reveal static thermal gradients.

Estimating glass transition temperature and related dynamics of molecular glass formers combining artificial neural networks and disordered systems theory

Glass transition temperature and related dynamics play an essential role in amorphous materials research since many of their properties and functionalities depend on molecular mobility. However, the temperature dependence of the structural relaxation time for a given glass former is only experimentally accessible after synthesizing it, implying a time-consuming and costly process. In this work, we propose combining artificial neural networks and disordered systems theory to estimate the glass transition temperature and the temperature dependence of the main relaxation time based on the knowledge of the molecule's chemical structure. This approach provides a way to assess the dynamics of molecular glass formers, with reasonable accuracy, even before synthesizing them. We expect this methodology to boost industrial development, save time and resources, and accelerate the scientific understanding of structure-properties relationships. • New joint theoretical and numerical approach to estimate the molecular dynamics • Machine learning for understanding structure-property relationships • Artificial neural networks for the design and development of new materials • Combining artificial neural networks and disordered systems theory • Estimating glass transition temperature and related dynamics of molecular glass formers

Neural Networks Reveal the Impact of the Vibrational Dynamics in the Prediction of the Long-Time Mobility of Molecular Glassformers.

Two neural networks (NN) are designed to predict the particle mobility of a molecular glassformer in a wide time window ranging from vibrational dynamics to structural relaxation. Both NNs are trained by information concerning the local structure of the environment surrounding a given particle. The only difference in the learning procedure is the inclusion (NN A) or not (NN B) of the information provided by the fast, vibrational dynamics and quantified by the local Debye–Waller factor. It is found that, for a given temperature, the prediction provided by the NN A is more accurate, a finding which is tentatively ascribed to better account of the bond reorientation. Both NNs are found to exhibit impressive and rather comparable performance to predict the four-point susceptibility at , a measure of the dynamic heterogeneity of the system.

NMR Relaxometry Accessing the Relaxation Spectrum in Molecular Glass Formers.

It is a longstanding question whether universality or specificity characterize the molecular dynamics underlying the glass transition of liquids. In particular, there is an ongoing debate to what degree the shape of dynamical susceptibilities is common to various molecular glass formers. Traditionally, results from dielectric spectroscopy and light scattering have dominated the discussion. Here, we show that nuclear magnetic resonance (NMR), primarily field-cycling relaxometry, has evolved into a valuable method, which provides access to both translational and rotational motions, depending on the probe nucleus. A comparison of 1H NMR results indicates that translation is more retarded with respect to rotation for liquids with fully established hydrogen-bond networks; however, the effect is not related to the slow Debye process of, for example, monohydroxy alcohols. As for the reorientation dynamics, the NMR susceptibilities of the structural (α) relaxation usually resemble those of light scattering, while the dielectric spectra of especially polar liquids have a different broadening, likely due to contributions from cross correlations between different molecules. Moreover, NMR relaxometry confirms that the excess wing on the high-frequency flank of the α-process is a generic relaxation feature of liquids approaching the glass transition. However, the relevance of this feature generally differs between various methods, possibly because of their different sensitivities to small-amplitude motions. As a major advantage, NMR is isotope specific; hence, it enables selective studies on a particular molecular entity or a particular component of a liquid mixture. Exploiting these possibilities, we show that the characteristic Cole–Davidson shape of the α-relaxation is retained in various ionic liquids and salt solutions, but the width parameter may differ for the components. In contrast, the low-frequency flank of the α-relaxation can be notably broadened for liquids in nanoscopic confinements. This effect also occurs in liquid mixtures with a prominent dynamical disparity in their components.

Surfactants Accelerate Crystallization of Amorphous Nifedipine by Similar Enhancement of Nucleation and Growth Independent of Hydrophilic-Lipophilic Balance.

Amorphous formulations, increasingly employed to deliver poorly soluble drugs, generally contain surfactants to improve wetting and dissolution. These surfactants are often liquids and can potentially increase the mobility of the drug and reduce its stability, but little is known about this effect. Here we investigate the effect of four common nonionic surfactants (Tween 80, Span 80, Triton X-100, and Poloxamer 407) on the crystallization of amorphous nifedipine (NIF). We find that the surfactants significantly enhance the rates of crystal nucleation and growth even at low concentrations, by up to 2 orders of magnitude at 10 wt %. The surfactants tested show similar enhancement effects independent of their structural details and hydrophilic-lipophilic balance (HLB), suggesting that surfactant adsorption at solid/liquid interfaces does not play a major role in crystal nucleation and growth. Importantly, the surfactants accelerate crystal nucleation and growth by a similar factor. This result mirrors the previous finding that a polymer dopant in a molecular glass-former causes similar slowdown of nucleation and growth. These results indicate that nucleation and growth in a deeply supercooled liquid are both mobility-limited, and a dopant mainly functions as a mobility modifier (enhancer or suppressor depending on the dopant). The common surfactants tested are all mobility enhancers and destabilize the amorphous drug, and this negative effect must be managed using stabilizers such as polymers. The effect of surfactants on nucleation can be predicted from the effect on crystal growth and the crystallization kinetics of the pure system, using the same principle previously established for drug-polymer systems. We show how the independently measured nucleation and growth rates enable predictions of the overall crystallization rates.

Controlling the volume fraction of glass-forming colloidal suspensions using thermosensitive host "mesogels".

The key parameter controlling the glass transition of colloidal suspensions is φ, the fraction of the sample volume occupied by the particles. Unfortunately, changing φ by varying an external parameter, e.g., temperature T as in molecular glass formers, is not possible, unless one uses thermosensitive colloidal particles, such as the popular poly(N-isopropylacrylamide) (PNiPAM) microgels. These, however, have several drawbacks, including high deformability, osmotic deswelling, and interpenetration, which complicate their use as a model system to study the colloidal glass transition. Here, we propose a new system consisting of a colloidal suspension of non-deformable spherical silica nanoparticles, in which PNiPAM hydrogel spheres of ∼100-200μm size are suspended. These non-colloidal "mesogels" allow for controlling the sample volume effectively available to the silica nanoparticles and hence their φ, thanks to the T-induced change in mesogels' volume. Using optical microscopy, we first show that the mesogels retain their ability to change size with T when suspended in Ludox suspensions, similarly as in water. We then show that their size is independent of the sample thermal history such that a well-defined, reversible relationship between T and φ may be established. Finally, we use space-resolved dynamic light scattering to demonstrate that, upon varying T, our system exhibits a broad range of dynamical behaviors across the glass transition and beyond, comparable with those exhibited by a series of distinct silica nanoparticle suspensions of various φ.

Probing Small-Angle Molecular Motions with EPR Spectroscopy: Dynamical Transition and Molecular Packing in Disordered Solids

Disordered molecular solids present a rather broad class of substances of different origin—amorphous polymers, materials for photonics and optoelectronics, amorphous pharmaceutics, simple molecular glass formers, and others. Frozen biological media in many respects also may be referred to this class. Theoretical description of dynamics and structure of disordered solids still does not exist, and only some phenomenological models can be developed to explain results of particular experiments. Among different experimental approaches, electron paramagnetic resonance (EPR) applied to spin probes and labels also can deliver useful information. EPR allows probing small-angle orientational molecular motions (molecular librations), which intrinsically are inherent to all molecular solids. EPR is employed in its conventional continuous wave (CW) and pulsed—electron spin echo (ESE)—versions. CW EPR spectra are sensitive to dynamical librations of molecules while ESE probes stochastic molecular librations. In this review, different manifestations of small-angle motions in EPR of spin probes and labels are discussed. It is shown that CW-EPR-detected dynamical librations provide information on dynamical transition in these media, similar to that explored with neutron scattering, and ESE-detected stochastic librations allow elucidating some features of nanoscale molecular packing. The possible EPR applications are analyzed for gel-phase lipid bilayers, for biological membranes interacting with proteins, peptides and cryoprotectants, for supercooled ionic liquids (ILs) and supercooled deep eutectic solvents (DESs), for globular proteins and intrinsically disordered proteins (IDPs), and for some other molecular solids.

Correlation between fragility and free volume void size at glass transition temperature

Despite the tremendous endeavors devoted to exploiting the nature of glass transition, the factors that control the steepness index of viscosity near glass transition, that is, fragility, remain unclear. In this study, we demonstrate that, for polymeric and small molecular weight organic glass formers, fragility increases upward with increasing size of the free volume void at the glass transition temperature. This changing trend indicates that fragility is governed by the properties of the segments or molecular clusters in the free volume void rather than by the properties of the entire polymer chains. The physics behind the relationship between fragility and free volume void at the glass transition temperature is consistent with the physics behind the relationship between fragility and the molecular weight as well as the mechanics of the relationship between fragility and size of the cooperative units. This relationship also provides new insights into the understanding of the nature of the glass transition of polymeric and small molecular weight organic glass formers.

Fast Differential Scanning Calorimetry: New Solutions in Data Treatment and Applications to Molecular Glass-Formers

Fast Differential Scanning Calorimetry: New Solutions in Data Treatment and Applications to Molecular Glass-Formers

Isochronal superpositioning of the caged dynamics, the α, and the Johari-Goldstein β relaxations in metallic glasses.

The superposition of the frequency dispersions of the structural α relaxation determined at different combinations of temperature T and pressure P while maintaining its relaxation time τα(T, P) constant (i.e., isochronal superpositioning) has been well established in molecular and polymeric glass-formers. Not known is whether the frequency dispersion or time dependence of the faster processes including the caged molecule dynamics and the Johari-Goldstein (JG) β relaxation possesses the same property. Experimental investigation of this issue is hindered by the lack of an instrument that can cover all three processes. Herein, we report the results from the study of the problem utilizing molecular dynamics simulations of two different glass-forming metallic alloys. The mean square displacement 〈Δr2t〉, the non-Gaussian parameter α2t, and the self-intermediate scattering function Fsq,t at various combinations of T and P were obtained over broad time range covering the three processes. Isochronal superpositioning of 〈Δr2t〉, α2t, and Fsq,t was observed over the entire time range, verifying that the property holds not only for the α relaxation but also for the caged dynamics and the JG β relaxation. Moreover, we successfully performed density ρ scaling of the time τα2,maxT,P at the peak of α2t and the diffusion coefficient D(T, P) to show both are functions of ργ/T with the same γ. It follows that the JG β relaxation time τβ(T, P) is also a function of ργ/T since τα2,maxT,P corresponds to τβ(T, P).