Alexander Dowling

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Assistant Professor

University of Notre Dame

United States

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Dr. Alexander Dowling is an Assistant Professor at the University of Notre Dame, USA. His research focuses on optimization techniques in sustainability and energy systems, including Bayesian optimization, multiscale modeling, and computational design. Recent articles highlight his work on sustainable aviation fuels, critical mineral separations, and advanced thermoelectric materials.

Recent Grants

Grant: Close

CAREER: Uncertainty Quantification and Optimization with Hybrid Models for Molecular-to-Systems Engineering

Open Date: 2020-02-01

Close Date: 2025-01-31

Grant: Close

Collaborative Research: Development and Application of a Molecular and Process Design Framework for the Separation of Hydrofluorocarbon Mixtures

Open Date: 2019-09-01

Close Date: 2022-08-31

Articles (20)

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2022

Collaborators (3)

Tengfei Luo

Dorini Family Professor

University of Notre Dame

UNITED STATES

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Ning Wang

Assistant Professor

The University of Texas at Tyler

UNITED STATES

View details

Edward Maginn

Keough-Hesburgh Professor

University of Notre Dame

UNITED STATES

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Alexander Dowling

Research Interests

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About

Recent Grants

Articles (20)

Bayesian Optimization of Low-Temperature Nonthermal Plasma Jet Sintering of Nanoinks

Measure this, not that: Optimizing the cost and model-based information content of measurements

Critical Mineral Separations: Opportunities for Membrane Materials and Processes to Advance Sustainable Economies and Secure Supplies

Multiscale Equation-Oriented Optimization Decreases the Carbon Intensity of Shale Gas to Liquid Fuel Processes

Reverse engineering morphogenesis through Bayesian optimization of physics-based models

Sustainable aviation fuel technologies, costs, emissions, policies, and markets: A critical review

Computational toolkits for model-based design and optimization

Hybrid Data‐driven Discovery of High‐performance Silver Selenide‐based Thermoelectric Composites

Assessment and Ranking of Difluoromethane (R32) and Pentafluoroethane (R125) Interatomic Potentials Using Several Thermophysical and Transport Properties Across Multiple State Points

Machine Learning-Enabled Development of Accurate Force Fields for Refrigerants

Data science for thermodynamic modeling: Case study for ionic liquid and hydrofluorocarbon refrigerant mixtures

Thermodynamics of Li<sup>+</sup>–Crown Ether Interactions in Aqueous Solvent

When physics-informed data analytics outperforms black-box machine learning: A case study in thickness control for additive manufacturing

Beyond price taker: Conceptual design and optimization of integrated energy systems using machine learning market surrogates

What Data Are Most Valuable to Screen Ionic Liquid Entrainers for Hydrofluorocarbon Refrigerant Reuse and Recycling?

Optimal Diafiltration Membrane Cascades Enable Green Recycling of Spent Lithium-Ion Batteries

Nonlinear Reactor Design Optimization With Embedded Microkinetic Model Information

Pyomo.DOE: An open‐source package for model‐based design of experiments in Python

Bayesian optimization for chemical products and functional materials

Multiscale simulation of integrated energy system and electricity market interactions

Collaborators (3)

Tengfei Luo

Ning Wang

Edward Maginn

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