Glass transition temperature prediction of disordered molecular solids

Abstract

Glass transition temperature, Tg, is the key quantity for assessing morphological stability and molecular ordering of films of organic semiconductors. A reliable prediction of Tg from the chemical structure is, however, challenging, as it is sensitive to both molecular interactions and analysis of the heating or cooling process. By combining a fitting protocol with an automated workflow for forcefield parameterization, we predict Tg with a mean absolute error of ~20 °C for a set of organic compounds with Tg in the 50–230 °C range. Our study establishes a reliable and automated prescreening procedure for the design of amorphous organic semiconductors, essential for the optimization and development of organic light-emitting diodes.

New Light-Green Thermally Activated Delayed Fluorescence Polymer Based on Dimethylacridine-Triphenyltriazine Light-Emitting Unit and Tetraphenylsilane Moiety as Non-Conjugated Backbone

“…The DSC traces of p -TPS-DMAC-TRZ ( Figure 6 b) showed a glass transition temperature (T g ) value of 265 °C, which is higher than that of DMAC-TRZ (91 °C [ 33 ]), and no melting transitions, indicating its amorphous nature. This high T g value is an essential feature for materials to be used in OLEDs since it correlates with stable film morphology and thus, a potentially longer operational lifetime of the devices [ 24 , 47 , 48 ].…”

Predicting the Melting Point of Energetic Molecules Using a Learnable Graph Neural Fingerprint Model

“…Nevertheless, melting point prediction for structurally diverse compounds is a more challenging task − because several factors, such as intermolecular interactions and entropic effects to name a few, significantly influence the melting behavior and are difficult to quantify solely from the molecular structure. − Advancements in methodology for predicting melting points over the past several decades have resulted in models that are more accurate and applicable to a wider range of compound types. Currently, methods for melting point prediction can be roughly divided into three categories, namely, group addition, , molecular dynamics, − and QSPR. , Group addition is the most straightforward method, but its accuracy and application are severely limited by the scope of pre-defined functional fragments or groups in the molecules. Although melting points predicted from molecular dynamics are generally more accurate and therefore desirable, the calculations are time-consuming and require knowledge of the crystal structures of predicted compounds, which significantly limits the applicability of this method.…”

Data-Driven Identification and Analysis of the Glass Transition in Polymer Melts

“…Upon cooling of a rubbery liquid polymer, dynamic properties such as viscosity or relaxation time increase drastically near the glass transition temperature ( T g ) in a super-Arrhenius fashion − without any remarkable change in structural properties . Despite enormous experimental and theoretical efforts, − the nature of glass transition as well as the question of a precisely defined T g still remain unclear. ,− In computer simulations, T g is often calculated from characteristic macroscopic properties, e.g., changes in the specific volume, density, or energy. − The increase in viscosity, equivalent to the terminal relaxation times, is commonly fitted to a Vogel–Fulcher–Tamann behavior that predicts a divergence at T VFT , typically about 50° below the calorimetric T g . However, the precise value of the observed T g depends on the cooling rate and fitting procedures, which can lead to some ambiguities in comparison with experimental values, , unlike a sharp and distinct change in physical properties.…”

“…However, the precise value of the observed T g depends on the cooling rate and fitting procedures, which can lead to some ambiguities in comparison with experimental values, , unlike a sharp and distinct change in physical properties. Thus, reliable predictions of T g are indeed challenging. ,,, …”

“…Thus, reliable predictions of T g are indeed challenging. 12,13,21,22 Attempts to link T g with the molecular structure of polymeric materials draw more attention. Recent studies predict T g by quantifying the changes in specific dihedral angles and transitions between states defined by those angles 13,14 or by using averaged intrachain properties.…”