journal article·2023-09-06Open access

Prediction of the Effective Work Function of Aspirin and Paracetamol Crystals by Density Functional Theory─A First-Principles Study

James R. Middleton, Andrew J. Scott, Richard Storey, Mariagrazia Marucci, Mojtaba Ghadiri

Crystal Growth & Design· Volume 23· Issue 9

Abstract

Crystals of active pharmaceutical ingredients (API) are prone to triboelectric charging due to their dielectric nature. This characteristic, coupled with their typically low density and often large aspect ratio, poses significant challenges in the manufacturing process. The pharmaceutical industry frequently encounters issues during the secondary processing of APIs, such as particle adhesion to walls, clump formation, unreliable flow, and the need for careful handling to mitigate the risk of fire and explosions. These challenges are further intensified by the limited availability of powder quantities for testing, particularly in the early stages of drug development. Therefore, it is highly desirable to develop predictive tools that can assess the triboelectric propensity of APIs. In this study, Density Functional Theory calculations are employed to predict the effective work function of different facets of aspirin and paracetamol crystals, both in a vacuum and in the presence of water molecules on their surfaces. The calculations reveal significant variations in the work function across different facets and materials. Moreover, the adsorption of water molecules induces a shift in the work function. These findings underscore the considerable impact of distinct surface terminations and the presence of molecular water on the calculated effective work function of pharmaceuticals. Consequently, this approach offers a valuable predictive tool for determining the triboelectric propensity of APIs.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Polymer crystallization and properties · Injection Molding Process and Properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom

New Modalities Product Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Macclesfield SK10 2NA, United Kingdom

Oral Product Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Gothenburg 413 27, Sweden

Funding

AstraZeneca · Engineering and Physical Sciences Research Council

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