arXiv subjects

Rodrigo Perez

Publications and source records attributed to Rodrigo Perez.

4 recordsLinked to original sources

arXiv2025

Enhanced Reactivity in Janus Transition Metal Dichalcogenide Quantum Dots: Charge-Density Asymmetry and Hydrodesulfurization Potential

Quantum dots (QDs) are nanoscale materials that exhibit unique electronic and optical properties due to quantum confinement effects, making them highly relevant for applications in catalysis, optoelectronics, and energy conversion. While transition metal dichalcogenide (TMD) QDs have been extensively studied in their pristine forms, Janus-type TMD QDs -- featuring compositional asymmetry across their atomic layers -- offer an additional degree of tunability through charge-density gradients and curvature effects, yet remain comparatively unexplored. In this work, we investigate the electronic and structural properties of Janus TMD QDs composed of molybdenum (Mo) or tungsten (W) in combination with chalcogen elements (S, Se, Te) and oxygen, exploring three distinct structural classes: pristine, non-oxidized Janus, and oxidized Janus phases. Using first-principles calculations, including static DFT and ab initio molecular dynamics (AIMD) simulations, we analyze curvature evolution, electrostatic potential isosurfaces, charge-density asymmetry, and surface formation energies to assess size- and composition-dependent stability. Our findings reveal that oxidation induces significant curvature and charge localization, particularly in W-based systems, enhancing their potential as catalysts for hydrodesulfurization reactions. Additionally, we identify size- and geometry-dependent stability trends, with larger and beta-type QDs exhibiting superior thermodynamic and thermal robustness. These results provide a comprehensive theoretical foundation for the design and synthesis of structurally tunable Janus QDs with tailored properties for catalytic and electronic applications.

cond-mat.mtrl-sci↗

arXiv2020

PettingZoo: Gym for Multi-Agent Reinforcement Learning

This paper introduces the PettingZoo library and the accompanying Agent Environment Cycle ("AEC") games model. PettingZoo is a library of diverse sets of multi-agent environments with a universal, elegant Python API. PettingZoo was developed with the goal of accelerating research in Multi-Agent Reinforcement Learning ("MARL"), by making work more interchangeable, accessible and reproducible akin to what OpenAI's Gym library did for single-agent reinforcement learning. PettingZoo's API, while inheriting many features of Gym, is unique amongst MARL APIs in that it's based around the novel AEC games model. We argue, in part through case studies on major problems in popular MARL environments, that the popular game models are poor conceptual models of games commonly used in MARL and accordingly can promote confusing bugs that are hard to detect, and that the AEC games model addresses these problems.

cs.LG↗

arXiv2010

Control of cancellations that restrain the growth of a binomial recursion

We study a recursion that generates real sequences depending on a parameter $x$. Given a negative $x$ the growth of the sequence is very difficult to estimate due to canceling terms. We reduce the study of the recursion to a problem about a family of integral operators, and prove that for every parameter value except -1, the growth of the sequence is factorial. In the combinatorial part of the proof we show that when $x=-1$ the resulting recurrence yields the sequence of alternating Catalan numbers, and thus has exponential growth. We expect our methods to be useful in a variety of similar situations.

math.CO↗

arXiv2004

On the growth of iterated monodromy groups

Nekrashevych conjectured that the iterated monodromy groups of quadratic polynomials with preperiodic critical orbit have intermediate growth. We illustrate some of the difficulties that arise in attacking this conjecture and prove subexponential growth for the iterated monodromy group of $z^2+i$. This is the first non-trivial example supporting the conjecture.

math.GR↗