pyEF: A Python Framework for QM and QM/MM Atom-Wise Electric Field Analysis
Year: 2026
Type: article
Abstract: High Resolution Image Download MS PowerPoint Slide We introduce pyEF, a software package for computing molecular electric fields, electrostatic interaction energies, and electrostatic potentials from quantum mechanical (QM) atom-centered multipole expansions with atom-wise decomposable contributions. We demonstrate the computational efficiency and accuracy of this QM-derived electric field evaluation tool through several tests. To assess the influence of the underlying QM method and charge partitioning scheme on these electrostatic quantities, we analyze over 250 configurations of an acetone solute molecule in five solvents of variable polarity. We find that electric field calculations are highly sensitive to the choice of charge partitioning method. Even among real-space charge schemes, acetone Stark tuning rates differ by up to a factor of 2. Benchmarking computed solvent dipole moments against experimental bulk values, we conclude that the CM5, ADCH, and Hirshfeld-I charge schemes most reliably capture solvent electrostatics and therefore provide a more faithful foundation for computing electric fields. When constructed from these real-space charges, electric fields are nearly insensitive to basis set size and monotonically increase in magnitude with higher Fock exchange. We also demonstrate efficient convergence of QM electrostatics when more distant molecules are represented solely by MM point charges, reducing computational overhead. Leveraging these findings, we demonstrate the use of pyEF to deduce environmental effects on a transition metal complex from a Ga 4 L 6 12– nanocage and quantify the dominant role of organic linkers in orchestrating electrostatic preorganization.
Institution: Massachusetts Institute of Technology
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,500
Funders: National Science Foundation, U.S. Department of Energy, National Institutes of Health, Office of Science, National Institute of General Medical Sciences, Office of Advanced Cyberinfrastructure, Division of Chemistry, Basic Energy Sciences, National Science Foundation Graduate Research Fellowship Program
Awards: G1453181110, G1555197637, G1787346651, Track 4: Advanced CI Coordination Ecosystem: Monitoring and Measurement Services, Revealing Nature's Blueprints for Single-Site Catalysis of C-H Activation with First-principles Modeling and Machine Learning, G338811424, G34258105, G3531872738, G3562386289, Track 1: ACCESS Resource Allocations Marketplace and Platform Services (RAMPS), G4010157413, G4275568664, ACO: An Open CI Ecosystem to Advance Scientific Discovery (OpenCI), Track 3: COre National Ecosystem for CyberinfrasTructure (CONECT), G5156331529, G5367127336, G5464919783, MOLECULAR UNDERSTANDING OF BIFUNCTIONAL SOLID LEWIS ACID ZEOLITES FOR THE C-C COUPLING OF ALPHA KETO ACIDS, Graduate Research Fellowship Program (GRFP), G6954850749, G7268552007, G741047408, G7526614437, G7916508619, G8178752565, Track 2: Customized Multi-tier Assistance, Training, and Computational Help (MATCH) for End User ACCESS to CI, G8499740153, G8623325734, G8994211811
OpenAlex ID: W7140092488