Dr. Thomas A. Manz

Associate Professor | Chemical & Materials Engineering

Manz.Tom_web.jpg

JH 150
(575) 646-2503

Education

  • Ph.D. Chemical Engineering 2009 Purdue University
  • M.S. Chemical Engineering 1998 Purdue University
  • B.S. Chemical Engineering 1994 The University of Toledo (Toledo, Ohio)

Professional appointments

  • 2018-present associate professor of Chemical & Materials Engineering at New Mexico State University
  • 2012-2018 assistant professor of Chemical & Materials Engineering at New Mexico State University
  • 2008-2012 research scientist (post-doc) at Georgia Tech

Research overview

My research group develops ground-breaking theoretical and computational frameworks that resolve long-standing problems. Each framework is a collection of methods and theoretical models that work together synergistically. Each framework functions as a sort of ‘scientific infrastructure’ that provides utility to other scientists and engineers by unifying diverse concepts and properties. A key goal is to educate the next generation of scientists and engineers to learn how to use these new theoretical tools.

This serves the United States’ (U.S.) national interest by: (i) exploring and advancing the scientific frontier, (ii) making the U.S. more competitive through technological and scientific advances, and (iii) making the U.S. more competitive by teaching the next generation of scientists and engineers how to use these new theoretical tools.

Together with my research group, I am developing the following theoretical and computational frameworks:

Space mixing theory

I’m creating a new theoretical framework called space mixing theory. The goal is to model the fundamental structure of physical spacetime, to unify physical interactions, and to describe the origins of subatomic particle properties. Earlier in my career, I did a lot of exploratory unpublished research on this topic. A key goal and challenge is to refine and publish this theory in the near future.

Standard atoms in materials framework (SAMF)

Many quantitative descriptors (such as bond orders and electron configurations) of atoms in materials have a long history in the chemical sciences but remained poorly defined for decades. Some approaches were well-defined but suffered key limitations. This created a confusing hodgepodge of techniques that lacked unification and widespread applicability. Richard Bader pioneered the development of the quantum theory of atoms in molecules (QTAIM) as a unified approach to assigning atom-in-material properties. QTAIM atoms are formed by partitioning a material’s electron density distribution into non-overlapping compartments. On the other hand, I’m creating the standard atoms in materials framework (SAMF) as a unified approach to assigning atom-in-material properties based on overlapping atoms. The SAMF partitions a material’s electron density distribution into overlapping atoms using stockholder-type partitioning. Hirshfeld developed the first stockholder partitioning approach, but it was too primitive. The SAME goes far beyond stockholder-type partitioning by assigning electron configurations, spdfg subshell populations, atomic orbitals in materials, bond order components, projected density of states plots, etc.

Superdeterminants and electron-electron correlations

I’m using superdeterminants to: (a) approximately compute matrix permanents via Monte Carlo sampling and (b) model electron-electron correlations in chemical systems. Superdeterminants provide powerful advantages by allowing many configurations to be simultaneously sampled.

Software tools and methods development

My research group develops software tools that implement our new computational methods. This provides impact by enabling other research groups around the world to use our new methods. Ultimately, this leverages impact, because collectively those groups use our software codes to study orders of magnitude more materials (or more systems) than it would be possible for my research group to study directly. For this reason, my research group primarily focuses on theoretical and computational methods development.

Research strategy and long-term goals

Considering the sweeping scope of the above theoretical and computational frameworks, project management and goal follow-through are extremely important. My research strategy centers around publishing great scientific papers and training Ph.D. students. In my experience, publishing a batch of closely related papers together is an effective technique. In the long term, review articles are an effective approach to summarize a large body of work. Also, a goal is to eventually incorporate these new approaches into university textbooks.

My research group seeks to obtain funding from the National Science Foundation and other funding agencies.

Prospective graduate students and post-docs

Prospective graduate students or post-docs should have a natural aptitude for mathematics, computer programming, chemistry, quantum mechanics, and physics. Preferably, they should have a high level of proficiency and experience in at least 3 of those 5 subjects. Students who have participated in and won scholastic contests (or aced math tests) may be good candidates. The ability to learn new topics quickly and retain knowledge for years is an important skill that I’m looking for. Students should have a natural curiosity that prompts them to experiment and seek out new knowledge. Excellent communication skills are important.

Publications

Please see my Google Scholar profile for a list of my scientific publications.

Professional profiles

Awards and recognitions

  • 2016-2022 National Science Foundation (NSF) Career Award, Division of Materials Science
  • 2018 Paulding High School Hall of Fame (Paulding, Ohio)
  • 2016 Early Career Research Council Award for Creative Scholarly Activity, New Mexico State University
  • Currently ranked in top 2% of scientists worldwide (see https://topresearcherslist.com/Home/Profile/1030884)