Dennis Trujillo

Education: B.S. Physics, New Mexico State University, 2014

Bio: Prior to joining the research group in 2016, Dennis performed research at Los Alamos National Lab and New Mexico State University as part of his bachelors and post bachelor’s studies. He performed studies using ultrafast lasers for coherent diffractive imaging of materials and coherent diffraction reconstruction algorithms. During that time, he developed an interest in materials properties and functional materials which ultimately catalyzed his interest in pursuing a PhD. Science has been a life-long interest and as a result, he has participated in many additional internships and projects related to materials physics, high performance computing (HPC), statistics applied to high energy physics and system administration in an HPC environment. Also, he has conducted multiple summer internships at Los Alamos National Lab through the duration of his time at UConn where he performed research in the domain of standard machine learning and deep learning for application in materials property prediction and application of convolutional neural networks towards classification-based problems. Dennis has experience in a variety of fields and hopes to apply his knowledge to provide unique solutions to difficult problems in the domain of materials science.

Current Research: Development of novel catalysts for desulphurization and oxygen evolution reactions (OER) via first-principles based approaches, machine learning and deep learning approach to identify and classify topological states in ferroelectric materials and the application of “shallow learning” techniques to predict material properties based on density functional theory calculated descriptors. Studies of multiferroic bismuth ferrite as a novel thin film electrocatalyst for application in catalyzing OER and doped zeolite structures as possible catalysts in desulphurization reactions are currenting in preparation for publication.

Favorite Computer Command: $ rm -rf *

Outside the Lab: Computers (100100000100010100) and learning to fly airplanes

LinkedIn Profile: https://www.linkedin.com/in/dptrujillo/

Research Gate Profile: https://www.researchgate.net/profile/Dennis_Trujillo 

GitHub: https://github.com/dptru10

ORCID: https://orcid.org/0000-0001-9259-3744

Dennis Trujillo on Nov. 16, 2017. (Peter Morenus/UConn Photo)

Structural models for (a) BiLaFe2O6 and BiSrFe2O6. (b) 80-atoms unit cell with x = 25% and (c) x = 50% doping in three distinct configurations where distances between dopants are varied. [“Electronic and Magnetic Properties of Lanthanum and Strontium Doped Bismuth Ferrite: A First-Principles Study”, Scientific Reports, 2019]

Structural models for (a) BiLaFe2O6 and BiSrFe2O6. (b) 80-atoms unit cell with x = 25% and (c) x = 50% doping in three distinct configurations where distances between dopants are varied. [“Electronic and Magnetic Properties of Lanthanum and Strontium Doped Bismuth Ferrite: A First-Principles Study”, Scientific Reports, 2019]

Sulphur containing thiophene molecule adsorption on reduced Zeolite cluster. [Publication in preparation]

Sulphur containing thiophene molecule adsorption on reduced Zeolite cluster. [Publication in preparation]


Publications

Surface Structure and Energetics of Low Index Facets of Bismuth Ferrite
D. Trujillo, A. Ghosh, S. Nakhmanson, S. Sahoo, and S. P. Alpay, Phys. Chem. Chem. Phys., Advance Article (2020)
DOI: https://doi.org/10.1039/D0CP01575J

Electronic and Magnetic Properties of Lanthanum and Strontium Doped Bismuth Ferrite: A First-Principles Study
A. Ghosh, D. P. Trujillo, H. Choi, S. M. Nakhmanson, S. P. Alpay, and J.-X Zhu, Scientific Reports 9, 194 (2019).
DOI: https://doi.org/10.1038/s41598-018-37339-3