Oliviero Andreussi, Ph.D.

What courses would you recommend for students to have taken prior to working in your laboratory?

Basic chemistry or materials knowledge is enough to start most of the projects. However, most projects involve being familiar with computers, especially with scripting and programming. Knowledge of unix/terminal commands can also be helpful. Students are encouraged to present their work at conferences and serve as co-authors on peer-reviewed publications.

How many hours per week do you expect a student to spend in the laboratory per research credit and does the time have to be a set schedule?

10 hours per week. The student’s schedule can be flexible, but it should overlap with standard working hours, to allow fruitful interactions with the advisor and senior lab members.

Ideally, for what length of time would a student research in your laboratory to achieve a meaningful research experience?

3 – 4 semesters

2008: Ph.D. – Physical Chemistry | Scuola Normale Superiore of Pisa, Italy

2003: M.S. – Chemistry | Scuola Normale Superiore of Pisa, Italy

The research of my lab is on computational science applied to problems in chemistry, materials, and biophysics. The main focus is on the development and application of computational models for the characterization of environment effects, with a focus on modeling wet materials interfaces. 

The main development project are: 

• Development and implementation of continuum embedding models as stand-alone libraries, to be coupled with first-principles and classical simulation packages. Most developed software is open-source and public, in Fortran and Python. 

• Development of automated Python workflows for high-throughput  of materials in complex environments. Improving existing embedding models and simulation workflows using machine learning algorithms. 

Application projects are related to:

• Computational design of electrocatalysts, with a current focus on two-dimensional materials and bulk metallic glasses for water splitting and recombination reactions.
• Modeling of chemical inhibitors for the formation and growth of natural gas hydrates.
• Study of solvent effects in drug design and biomolecular structure. 

N. Karmodak, L. Bursi, and O. Andreussi, “Oxygen Evolution and Reduction on Two-Dimensional Transition Metal Dichalcogenides”, J. Phys. Chem. Lett., 13, 58 (2022).

O. Andreussi, F. Nattino, and N.G. Hörmann, “Continuum Embedding Models for Electrolyte Solutions in First-Principles Simulations of Electrochemistry”, book chapter in M. Melander, T. Laurila, and K. Laasonen (editors) Atomic-Scale Modelling of Electrochemical Systems, Whiley, ISBN: 978-1-119-60561-4 (2021).

N. Karmodak and O. Andreussi, “Catalytic Activity and Stability of Two-Dimensional Materials for the Hydrogen Evolution Reaction”, ACS Energy Lett. 5, 885-891 (2020).

F. Nattino, C. Dupont, N. Marzari, and O. Andreussi, “Functional Extrapolations to Tame Unbound Anions in Density-Functional Theory Calculations”, J. Chem. Theory Comput. 15, 6313-6322 (2019).

N. Hörmann, Z. Guo, F. Ambrosio, O. Andreussi, A. Pasquarello, and N. Marzari, “Absolute band alignment at semiconductor-water interfaces using explicit and implicit descriptions for liquid water”, NPJ Comput. Mater. 5, 100 (2019).

O. Andreussi, N. Hörmann, F. Nattino, G. Fisicaro, S. Goedecker, and N. Marzari, “Solvent-aware Interfaces in Continuum Solvation”, J. Chem. Theory Comput. 15 (3) 1996 (2019).

N. Hörmann, O. Andreussi, and N. Marzari, “Grand canonical simulations of electrochemical interfaces in implicit solvation models”, J. Chem. Phys. 150, 041730 (2019).

F. Nattino, M. Truscott, N. Marzari, and O. Andreussi, “Continuum models of the electrochemical diffuse layer in electronic-structure calculations”, J. Chem. Phys. 150, 041722 (2019).

2021 – 2023

• MRI: Acquisition of a High Performance Hybrid Computer Cluster for Computational Modeling – NSF OAC

2020 – 2025

• Multiscale and Machine-Learning Approaches for Solid-Liquid Interfaces – NSF CAREER program, NSF CHE and DMR directorates

2020 – 2022

• Gas Hydrates Inhibition and Promotion: a First-Principles High-Throughput Approach –  ACS Petroleum Research Fund

2019 – 2022

• Collaborative Research: Elements: Flexible and Open-Source Models for Materials and Devices – NSF CSSI program

Recipient of the NSF CAREER award, NSF CHE and DMR directorates (2020).

• PHYS 3910 on “Intermediate Computational Physics”, Department of Physics at University of North Texas (UNT).
• PHYS 6110 on “Statistical Mechanics”, Department of Physics, UNT.
• PHYS 3510 on “Computer, Physics, and Software Applications”, Department of Physics, UNT.
• PHYS 1710 on “Classical Mechanics and Thermodynamics”, Department of Physics, UNT.
• Undergraduate course on “Errors and Data Analysis”, Department of Chemistry, University of Pisa, Italy.