Samuel D. Young

Samuel D. Young

Postdoctoral Researcher (Sep 2023)

University of Michigan (Ann Arbor)

Welcome!

I am a postdoctoral researcher in the Goldsmith Computational Modeling Laboratory at the University of Michigan. I completed my doctoral degree at University of Michigan in August 2023. My graduate research centered on using computational catalysis and machine learning for environmental sciences, specifically water remediation. I am also a 2022–2023 J. Robert Beyster Computational Innovation Graduate Fellow and a member of the Michigan Catalysis Science and Technology Institute.

In my free time, I enjoy swimming, music composition, and organ performance.

Check out my CV!

Interests
  • Machine learning for materials discovery
  • Computational catalysis
  • Environmental chemistry
Education

  • Ph.D. in Chemical Engineering, 2023

    University of Michigan

  • M.S. in Chemical Engineering, 2020

    University of Michigan

  • B.S. in Chemical Engineering, 2016

    Cornell University

Research Interests

Current Projects

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Electrocatalytic Nitrate Reduction
Electrocatalysis is a promising approach to remediating nitrate-contaminated water.
Samuel D. Young
Electrocatalytic Nitrate Reduction
Machine Learning for Alloy Catalyst Discovery
Active machine learning can accelerate the search for highly active, stable, and selective catalysts.
Samuel D. Young
Machine Learning for Alloy Catalyst Discovery

Awards and Fellowships

J. Robert Beyster Computational Innovation Graduate Fellowship
University of Michigan - College of Engineering Aug 2022 – May 2023
Fellowship given to support cutting-edge research in computational materials discovery, materials data infrastructure, and high-performance computing.
MICDE Graduate Fellowship
University of Michigan - Michigan Institute for Computational Discovery and Engineering Sep 2018 – May 2019
Research fellowship given for graduate research work in the application or development of scientific computing.

Experience

 
 
 
 
 
Postdoctoral Researcher
University of Michigan
Sep 2023 – Present Ann Arbor, MI
Currently conducting computational catalysis and machine learning research for nitrate reduction. My research involves density functional theory simulations and high-throughput electrocatalyst screening.
 
 
 
 
 
Graduate Student Research Assistant
University of Michigan
Aug 2018 – Aug 2023 Ann Arbor, MI
Currently conducting computational catalysis and machine learning research for nitrate reduction. My research involves density functional theory simulations and high-throughput electrocatalyst screening.
 
 
 
 
 
Visiting Graduate Student Scientist
Los Alamos National Laboratory
Jan 2021 – Oct 2021 Los Alamos, NM
Conducted a computational research project investigating the thermodynamic stability and structure of ABO2N and ABON2 perovskite oxynitrides.
 
 
 
 
 
Graduate Student Instructor - ChE 505
University of Michigan
Aug 2021 – Dec 2021 Ann Arbor, MI
Co-lead an engineering mathematics course for first-year graduate students. Responsibilities included providing office hours, composing homework assignments, and guiding students through a capstone semester project.
 
 
 
 
 
Graduate Student Instructor - ENGR 1000-320
University of Michigan
Jan 2021 – Apr 2021 Ann Arbor, MI
Currently co-leading a freshman introductory machine learning course for 46 students. My duties include holding weekly office hours, assisting students with homework and lab assignments, and grading homework and exams.
 
 
 
 
 
Graduate Student Instructor - ChE 505
University of Michigan
Aug 2020 – Dec 2020 Ann Arbor, MI
Co-lead an engineering mathematics course for first-year graduate students. Responsibilities included providing office hours, composing homework assignments, and guiding students through a capstone semester project.
 
 
 
 
 
Chemical Engineering Consultant
U.S. Army Combat Capabilities Development Command Chemical Biological Center
Aug 2016 – Aug 2018 Edgewood, MD
Provided lifecycle analysis and support of chemical detection commodity items used in the Army, as well as logistics support for 59 active-duty Army units.

Skills

Atomistic Modeling

DFT (VASP), ASE, Pymatgen

Python

Numerical computing, web services, automation

Machine Learning

scikit-learn, PyTorch

NoSQL DBMS

MongoDB, PyMongo

SQL RBDMS

MS Access JET/ACE SQL, PostgreSQL, sqlite

Web Development

React, Next.js, Django, Tailwind, SWR

Linux (SuSE, Arch, Ubuntu)

Shell scripting, VMs, Docker

Workflow Managers

Slurm, PBS/Torque, FireWorks, Luigi

Visual Basic for Applications

MS Access DAO, forms, MS Excel

Publications

Written Dissertation
Abstract Humans contribute more fixed nitrogen than can be reduced naturally. Understanding nitrogen chemistry is essential to balancing the global nitrogen cycle. An imbalanced nitrogen cycle raises levels of nitrate (NO3–) in water.
Samuel D. Young
Written Dissertation
Thermodynamic Stability and Anion Ordering of Perovskite Oxynitrides
The version of record is located here. Supporting information is available for free here.
Samuel D. Young, Jiadong Chen, Wenhao Sun, Bryan R. Goldsmith, Ghanshyam Pilania
Thermodynamic Stability and Anion Ordering of Perovskite Oxynitrides
Metal Oxynitrides for the Electrocatalytic Reduction of Nitrogen to Ammonia
Selected as an ACS Editors’ Choice article! Publicly available to read for free through the end of Jan 2023 at https://pubs.acs.org/doi/full/10.1021/acs.jpcc.2c02816.
Samuel D. Young, Bianca Ceballos, Amitava Banerjee, Rangachary Mukundan, Ghanshyam Pilania, Bryan R. Goldsmith
Metal Oxynitrides for the Electrocatalytic Reduction of Nitrogen to Ammonia
Electrocatalytic nitrate reduction on rhodium sulfide compared to Pt and Rh in the presence of chloride
Danielle Richards, Samuel D. Young, Bryan R. Goldsmith, Nirala Singh
Electrocatalytic nitrate reduction on rhodium sulfide compared to Pt and Rh in the presence of chloride
Perovskite Oxynitrides as Tunable Materials for Electrocatalytic Nitrogen Reduction to Ammonia
Perovskite oxynitrides are a tunable class of materials with unique chemistry for electrocatalytic nitrogen reduction.
Samuel D. Young, Amitava Banerjee, Ghanshyam Pilania, Bryan R. Goldsmith
Perovskite Oxynitrides as Tunable Materials for Electrocatalytic Nitrogen Reduction to Ammonia
Increasing Electrocatalytic Nitrate Reduction Activity by Controlling Adsorption through PtRu Alloying
PtRu alloy catalysts have higher nitrate reduction activity than Pt or Ru alone.
Zixuan Wang, Samuel D. Young, Bryan Goldsmith, Nirala Singh
Increasing Electrocatalytic Nitrate Reduction Activity by Controlling Adsorption through PtRu Alloying
Conductivity and Microstructure of Combinatorially Sputter-Deposited Ta–Ti–Al Nitride Thin Films
Ta-Ti-Al nitride thin films with only ~20 at.% Ti may enable PEM fuel cell catalyst supports that are both conductive and durable.
James R. O’Dea, Megan E. Holtz, Anna E. Legard, Samuel D. Young, Raymond G. Burns, Abigail R. Van Wassen, David A. Muller, Héctor D. Abruña, Francis J. DiSalvo, R. Bruce van Dover, John A. Marohn
Conductivity and Microstructure of Combinatorially Sputter-Deposited Ta–Ti–Al Nitride Thin Films

Recent and Upcoming Talks

Heterogeneous Electrocatalysts for Aqueous Nitrate Reduction and Nitrogen Chemistry
U.S. Army Research Lab Distinguished Postdoctoral Fellowship Candidate Seminar
Oct 12, 2023 1:00 PM — 2:00 PM Virtual
Samuel D. Young
Heterogeneous Electrocatalysts for Aqueous Nitrate Reduction and Nitrogen Chemistry
Oral Dissertation Defense
Oral defense of the dissertation of Samuel D. Young
Aug 7, 2023 9:00 AM — 10:30 AM B10 South Atrium
Samuel D. Young
Oral Dissertation Defense
AIChE 2022: Thermodynamic Stability and Anion Ordering in ABO2N and ABON2 Perovskite Oxynitrides
Nov 18, 2022 9:12 AM — 9:30 AM Phoenix, AZ, USA
Samuel D. Young, Bianca Ceballos, Amitava Banerjee, Ghanshyam Pilania, Bryan Goldsmith
AIChE 2022: Thermodynamic Stability and Anion Ordering in ABO2N and ABON2 Perovskite Oxynitrides
ACS Fall 2022: Thermodynamic Stability and Anion Ordering in ABO2N and ABON2 Perovskite Oxynitrides
Aug 23, 2022 10:40 AM — 11:00 AM McCormick Place Convention Center, Rm. W178a
Samuel D. Young, Amitava Banerjee, Bryan R. Goldsmith, Ghanshyam Pilania
ACS Fall 2022: Thermodynamic Stability and Anion Ordering in ABO2N and ABON2 Perovskite Oxynitrides
AIChE 2021: Platinum-Ruthenium Alloys As Electrocatalysts for Efficient Aqueous Nitrate Reduction
To be held in-person at the Hynes Convention Center, Sheraton Boston and Marriott Boston Copley Place over the dates of Nov. 7-11 and virtually from Nov. 15-19, the AIChE Annual Meeting is the forum for ChEs interested in innovation and professional growth. Experts will cover wide range of topics relevant to cutting-edge research, new technologies, and emerging areas in the field.
Nov 16, 2021 4:30 PM — 4:50 PM Boston (in-person, 7–11 Nov 2021) and Virtual (15–19 Nov 2021)
Samuel D. Young, Zixuan Wang, Nirala Singh, Bryan Goldsmith
AIChE 2021: Platinum-Ruthenium Alloys As Electrocatalysts for Efficient Aqueous Nitrate Reduction
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