VII Colloquium on Computational Simulation in Sciences

The Center for Nanoscience and Nanotechnology of UNAM invites you to

VII COLLOQUIUM ON COMPUTATIONAL
SIMULATION IN SCIENCES
VIRTUAL

Students session.
Hands-on workshops: Python for IA, Non Covalent Interactions, and Optical Properties of Materials.

unam nacion

 

  Organizing committee.

Local committee

External committee

 

Acknowledgments: Project DGAPA-PAPIIT IG101124

The Laboratorio Virtual de Modelación de Materiales del Centro de Nanociencias y Nanotecnología-UNAM, invites you to the VII Coloquio de Simulaciones Computacionales en Ciencias, VIRTUAL from August 26 to August 30, 2024. 
 
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Zoom link to be part of the conference series

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General Program

Student Session 1 - Monday, August 26

Análisis del acoplamiento electrón-fonón en monogermanidos mediante la teoría del funcional de la densidad con escalamiento de espín

– José Andrés Nuñez Ávila – Instituto de Física “Ing. Luis Rivera Terrazas” (IFUAP), Benemérita Universidad Autónoma de Puebla (BUAP)

 

Abstract

Se presenta un estudio de la dinámica de red y el acoplamiento electrón-fonón de la solución sólida Mn1–yFeyGe (0 <= y <= 1) en la estructura no-centrosimétrica B20. Previamente se ha reportado que MnGe exhibe fases magnéticas de alto espín (  2 µB/Mn), bajo espín (1 µB/Mn) y no magnético en función de la presión, mientras que FeGe únicamente presenta fases de alto espín (1 µB/Mn) con anomalías fonónicas y no magnético. En este estudio se exploran la relación que existe entre las diferentes fases magnéticas en la solución sólida y el acoplamiento electrón-fonón. Para ello, se han realizado cálculos de primeros principios, mediante la teoría del funcional de la densidad (DFT), usando el método de pseudopotenciales con bases mezcladas (MBPP). En particular, se analiza la evolución del momento magnético en función de la concentración de Fe (y) en la solución sólida, así como su relación con las diferentes fases magnéticas encontradas en la solución. Se pone especial énfasis en las frecuencias y en el linewidth fonónico, con el fin de determinar la influencia del magnetismo en la dinámica de red. Debido a la importancia de la adecuada descripción del momento magnético, se examina y se contrasta el enfoque de escalamiento del espín (ssxc) en la energía de intercambio y correlación dentro de DFT, con el fin de determinar sus efectos en las propiedades de interés previamente mencionadas.

Modelado de primeros principios de las superficies de Fermi de los compuestos tipo Kagome Pt3X2(X=In y Tl)

– Samuel Flóres García – Universidad Nacional Autónoma de México

 

Abstract

Los compuestos Pt3In2 y Pt3Tl2 tiene fase hexagonal con grupo espacial P63/mmc en los cuales las especies de Pt forman monocapas con ordenamiento tipo Kagome. Esta disposición genera propiedades muy características en su estructura electrónica. Tales como bandas aplanadas, provocada por la localización de los electrones debido a este arreglo atómico. Se modeló la estructura electrónica por medio la teoría de la densidad del funcional obteniendo las densidades de estados, la estructura de bandas y la superficie de Fermi, para ambos compuestos. Además se comparó los resultados de este último por medio de las oscilaciones de la magnetización provocadas por el efecto de De Haas-van Alphen reportado en la literatura en la dirección [0001]. Igualmente se varió el ángulo del campo magnético y con ello hacer un barrido de toda la superficie de Fermi obteniendo las frecuencias para otras direcciones además de la [0001]. Por medio la estructura de bandas proyectadas se caracterizan cuáles orbitales y a qué especie pertenecen las bandas que contribuyen a la superficie de Fermi.

Agradecemos a los proyectos DGAPA-UNAM IG101124 y DGAPA-UNAM IA100624. Los cálculos se realizaron en el centro de súpercomputo UNAM proyecto LANCAD-UNAM-DGTIC-368, LNSBUAP proyecto 202201042N e THUBAT KAAL IPICYT proyecto TKII-JGSA001.

Title

– L.A. Alvarado-Leal – Universidad Autónoma de Nuevo León

Abstract

Este estudio investiga la influencia de los momentos magnéticos de los metales de transicieon en la adsorción y activación del oxígeno molecular (O2) en sistemas de catalizadores de un solo átomo soportados en grafeno dopado con nitrógeno, utilizando cálculos de teoría del funcional de la densidad. Demostramos que los metales con mayores momentos magnéticos, como Cr y Mn, exhiben una afinidad y estabilización mejoradas en la adsorción de O2. En contraste, los metales con momentos magnéticos bajos o nulos, como Ni y Cu, muestran una capacidad disminuida para adsorber O2 de manera efectiva. Nuestro análisis de las energías de adsorción, las profundidades del potencial de Morse y la fuerza de reacción subraya el papel crítico de los momentos magnéticos de los metales de transición en dictar el rendimiento catalítico y caracterizar la naturaleza del enlace químico entre el centro metálico y el oxígeno. Esto proporciona información valiosa para optimizar los catalizadores de un solo átomo en las reacciones de reducción de oxígeno y otras aplicaciones de conversión de energía.

Comparative DFT Study of functionalized graphene for energy storage applications

– Elizabeth Fernandez-García – Universidad Nacional Autónoma de México

Abstract

Understanding the interaction of metal oxides and carbon in nanocomposite electrode materials for supercapacitors is a task to achieve by combining the high electrical conductivity and specific surface area from carbon structural arrays and the high pseudocapacitance from metal oxides. This interaction can be obtained by incorporating functional groups on the carbon nanomaterial surface. In this study, we realized the structural optimization of NH2, COOH, and OH functional groups over pristine graphene and graphene with single vacancy. Comparing models’ Density of States (DOS) with functional groups shows higher charge density concentration at the Fermi level over pristine graphene, resulting in improved charge transfer. This enhancement is associated with an increased charge-discharge capacity in electrode materials designed for supercapacitors. Integrated quantum capacitance calculation in -1V to 1V potential revealed higher charge accumulation in graphene with single vacancy simulated models, with the OH model presenting the highest quantum capacitance. Accumulated superficial charge in -1V to 1V potential reveals a higher capacity of graphene with a single vacancy OH model to store more charge in negative and positive potential, allowing it to operate as a cathode and anode electrode.

Disociación de Moléculas de Agua Usando Superficies de BiOX

– Gabriel Martinez Gutierrez – Universidad Nacional Autónoma de México

 

Abstract

Hydrogen generation is complex because it requires high energy; an example is electrolysis, which needs 2.456 eV/particle to dissociate it [1]. Different materials have been investigated to achieve water splitting. Bismuth oxyhalides (BiOX, X = Cl, Br, I) are constantly investigated due to their efficient catalytic properties, among them recently the material BiOI (2×1) has been studied, which by first-principles simulations proved to be stable [2]. It has vacancy-mediated channels that serve as catalytic points for water splitting. Using the BiOI (2×1) structure, it was possible to determine an energy barrier to dissociate water molecules, where a barrier of 0.106 eV. Two hydrogen atoms are displaced in the process, recreating a proton transfer effect—such an effect generates lower energy barriers than those required for electrolysis. 

Este trabajo es apoyado por DGAPA-UNAM projects IG101124 and IA100624. Calculations were performed in the Miztli supercomputer projects LANCAD-UNAM-DGTIC-368. JGS acknowledges LNS-BUAP project 202201042N and THUBAT KAAL IPICYT supercomputing center project TKII-JGSA001 for their computational resources. 

Fernández-Escamilla, H. N., et al. “Bismuth and oxygen vacancies induce (2× 1) reconstructions in bismuth oxyhalide (BiOX, X= Cl, Br, I)(0 0 1) surfaces.” Applied Surface Science 618 (2023): 156583.

Exploring the potential of h-Zn2GeO4 as an Li-host anode

– Gabriel Cosio – Centro de Investigación Científica y de Educación Superior de Ensenada

 

Abstract

The demand for eco-friendly and efficient energy sources in industrial, portable, and wearable applications has driven extensive research into electrochemical storage devices. Among these technologies, lithium-ion batteries emerge as highly promising due to their exceptional physicochemical and electrochemical properties. These batteries offer a lightweight design, high-energy density, and compact size, attributes directly influenced by the active materials within the electrodes and the redox reactions occurring during charge and discharge processes. To further enhance lithium-ion battery performance beyond conventional graphite-based anodes, there is ongoing exploration of advanced nanomaterials with specific chemical compositions and crystalline structures capable of facilitating reversible and rapid conversion and alloying reactions, thus enabling superior Li-ion storage capacity. In this context, our study focuses on employing h-Zn2GeO4 nanoparticles as a Li-ion host material. The synthesis of h-Zn2GeO4 in a willemite-like phase using the facile Pechini method was proposed, followed by a comprehensive investigation into its physicochemical and electrochemical properties for Li-ion battery applications. Experimental analyses were complemented by computational simulations using Density Functional Theory (DFT) and Ab Initio Molecular Dynamics (AIMD) to delve into atomic-scale interactions between Li ions and the h-Zn2GeO4 crystal structure.

This work was supported by: project CONACYT-SENER No. 274314; DGAPA-UNAM IA100624, IG101124 and IN101523; Supercomputing center DGCTIC-UNAM, Project No. LANCAD-UNAM-DGTIC-150, LANCAD-UNAM-DGTIC-368 and LANCAD-UNAM-DGTIC-422.

Charge-density asymmetry in MoSO and MoSeO nanotriangles increases their reactivity towards the hydrodesulfurization reaction

– Jair Othoniel Dominguez Godinez – Universidad Nacional Autónoma de México

 

Abstract

Transition metal dichalcogenides have garnered attention because of their unique physical properties. Janus monolayers with different chalcogen layers may increase their versatility and range of applications. Paez et al. 10.1038/s41598- 021-00287-6 demonstrated that charge-density asymmetry generates curvature in MoSeS nanotriangles and, consequently, an increase in their reactivity. Considering such effect, in this work, we engineered the MoS2 and MoSe2 nanotriangles to generate MoSO and MoSeO via selective oxidation of one side of the monolayer, ending up with thermodynamically stable Janus monolayers. After that, we designed MoSO and MoSeO nanotriangles and analyzed the curvature generated by the difference in electronegativity between S/Se and O. Also, we analyzed the reactivity increase due to the induced curvature and discussed their potential in the hydrodesulfurization reaction.

We thank DGAPA-UNAM projects IA100624, and IG101124 for partial financial support. Calculations were performed in the DGCTIC-UNAM Supercomputing Center projects LANCAD-UNAM-DGTIC 368 and 422, LNS and THUBAT KAAL IPICYT.

Ab initio study of the TaN/MgO interface

– Victor Quintanar-Zamora – Universidad Nacional Autónoma de México

 

Abstract

The present work addresses possible interface models between TaN and FCC MgO (001) using density functional theory (DFT) calculations. The epitaxial relation of TaN layers and MgO bulk is [001]TaN/[001]MgO. It has been reported that MgO substrates promote the growth of high-quality superconducting FCC TaN thin films with better results than Si substrates [1]. Therefore, firstprinciples calculations were performed to explore the TaN/MgO system in detail. Slabs were evaluated using the interface formation energy (IFE) formalism [2, 3] to assess its thermodynamic stability. Four stable and one unstable interface models were identified. In the most stable model, a TaO transition layer is formed at the boundary between TaN and MgO, resulting from oxygen scavenging by the Ta. Additionally, the electronic properties at the interface, such as density of states (DOS) and electron localization function (ELF), were calculated. The total DOS reveals a metallic nature, and the projected DOS shows that Ta-dyz and Ta-dxz degenerated orbitals are the main contributors to the states at the Fermi energy. Finally, the ELF indicates ionic-type bonding at the interface. Keywords: tantalum nitride, magnesium oxide, thermodynamic stability, DFT. 

This work was supported by DGAPA-UNAM IG101124, IG101623, IA100624, and IN101523 projects, as well as the CB_CONACYT A1-S-33492 grant. Calculations were performed in the DGCTIC-UNAM Supercomputing Center, Project No. LANCAD-UNAM-DGTIC-150, LANCADUNAM- DGTIC-368 and LANCAD-UNAM-DGTIC-422, and the THUBAT KAAL IPICYT supercomputing center. 

[1] Chaudhuri S. Chaudhuri, I. J. Maasilta, L. Chandernagor, M. Ging, and M. Lahtinen, “Fabrication of superconducting tantalum nitride thin films using infrared pulsed laser deposition,” Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films, vol. 31, no. 6, p. 061502, Nov. 2013, doi: 10.1116/1.4812698. 

[2] J. Guerrero-Sánchez and N. Takeuchi, “Formation of ferromagnetic/ferrimagnetic epitaxial interfaces: Stability and magnetic properties,” Comput Mater Sci, vol. 144, pp. 294–303, Mar. 2018, doi: 10.1016/j.commatsci.2017.12.049. 

[3] K. Alam, R. Ponce-Pérez, K. Sun, A. Foley, N. Takeuchi, and A. R. Smith, “Study of the structure, structural transition, interface model, and magnetic moments of CrN grown on MgO(001) by molecular beam epitaxy,” Journal of Vacuum Science & Technology A, vol. 41, no. 5, Sep. 2023, doi: 10.1116/6.0002546.

Efectos del modelo agua en las propiedades comformacionales del receptor transmembranal GPR40

– Jorge Alberto Aguilar Pineda – Benemérita Universidad Autónoma de Puebla

 

Abstract

El receptor GPR40, también conocido como FFAR1, forma parte de la familia de receptores transmembranales GPCR. Actualmente este receptor es considerado una diana terapéutica en el tratamiento de la diabetes mellitus tipo 2 (DMT2), ya que su activación está relacionada a la mejora del control glucémico al estimular la secreción de insulina. Haciendo uso de herramientas computacionales, como son las simulaciones de dinámica molecular y análisis de trayectorias, en esta plática se hablará acerca de la importancia del modelo de agua utilizado como solvente en los sistemas GPR40-membrana. En este trabajo analizamos el efecto de cuatro modelos de agua explícita sobre la estructura e interacciones del receptor GPR40. Los modelos elegidos fueron dos de tipo rígido (SPC/E y TIP4P) y sus modelos mejorados flexibles (FBA/ε y TIP4P/εflex). Diversas técnicas in silico fueron empleadas para este propósito.

Student Session 2 - Tuesday, August 27

Nanohojas de BN impurificadas con átomos de B empleadas para la purificación de gas natural

– Diana Pozos Silva – Benemérita Universidad Autónoma de Puebla

 

Abstract

El Nitruro de Boro (BN) es un material con alto potencial para desarrollar nanoestructuras alotrópicas (nanohojas, nanotubos y fullerenos). Este tipo de estructuras son significativamente estudiadas producto de sus aplicaciones que van desde la creación de dispositivos electrónicos hasta medio de transporte de fármacos, incluso, se utilizan para la purificación del gas natural. En este trabajo se presentan cálculos de primeros principios, usando la teoría de los funcionales de la densidad (DFT) a nivel del gradiente generalizado (GGAHSEh1PBE) para analizar el efecto de adsorción de N2 sobre nanohojas de BN prístina y nanohojas de BN impurificadas con átomos de boro para determinar las propiedades electrónicas, químicas y estructurales. Los resultados obtenidos muestran que el comportamiento electrónico de los complejos B27N27H18-N2, B29N24H18-N2, B27N27H18-2N2,B29N24H18-2N2, B27N27H18-3N2 y B29N24H18-3N2 son de carácter semiconductor (gap 5.80 – 2.25 eV) de acuerdo con las diferentes orientaciones geométricas estudiadas. La energía de adsorción dependiendo de la concentración de N2 se mantiene conforme se van colocando un mayor número de moléculas de N2 sobre la nanohoja prístina (Ead = -0.05 – -0.09 eV), esto es indicativo de que las moléculas de N2 son físisorbidas por las dichas hojas de BN lo que implica que posiblemente las hojas de BN no son aptas para la remoción de N2 del gas natural. Sin embargo, cuando la nanohoja es impurificada por átomos de boro las N2 son químicamente adsorbidas (Ead = -1.25 a -1.49 eV), lo que indica que estos sistemas son aptos para la remoción del N2 del gas natural.

Estudio de Primeros Principios Aplicados a MOenes

– Santiago Triana Bejarano – Universidad Nacional Autónoma de México

 

Abstract

In recent years, the interest in the study of two-dimensional (2D) materials has grown exponentially because of their unique structural, electronic, and magnetic properties. In the search for new 2D materials, the family of MXenes has attracted the attention of researchers. MXenes are a family of materials made up of metal carbides and nitrides. These 2D materials have numerous physical properties that make them ideal for manufacturing energy storage materials, biomedical applications, and electronic devices. Analogous to this family, researchers have discovered MOenes, which are made up of a transition metal and oxygen. These materials are expected to exhibit novel energy storage properties like MXenes. In recent years, the existence of molybdenum structures within the MXenes group has been demonstrated theoretically. In this work, a first-principles study of two MoO2 structures (1T and 2H) was carried out. We studied the structural and electronic properties of the MoO2 2D system. According to the phononic band structure and electronic band structure, both MoO2 systems are stable and exhibit metallic behavior. Furthermore, the 2H monolayer is the most stable.

Exploring the Li, Na and K intercalation process in the functionalized Mo2V2C3T2 (T = O, F, OH) MXene: insight from first-principles calculations.

– Raul Santoy-Flores – Universidad Nacional Autónoma de México

 

Abstract

MXenes are excellent candidates to be employed as anode in Li-ion batteries due to their electrochemical properties, high electrical conductivity, and low energy barriers for ion diffusion. Recent studies have demonstrated that bi-metallic MXenes, like Ti2Ta2C3, exhibit superior electrochemical performance compared to their monometallic counterparts, offering potential for extended lifespan in energy storage systems. In this work, we investigated the role of the surface functionalization in the Li intercalation process, for this porpoise, we considered the presence of O, F, Cl and OH functional groups onto the surface. Besides, we investigated the activation energy to diffuse the Li, Na and K ions onto the surface and the theoretical gravimetric capacity. Our findings indicate that the oxidized phase of Mo2V2C3 performs exceptionally well as an anode in batteries, providing higher gravimetric capacity with Li-ion integration. These insights highlight the promise of bi-metallic MXenes in advancing cycling stability and energy efficiency in next-generation energy storage devices.

Obtention of nitrogen-doped graphene from different types of graphene oxide

– M. Amezcua-Navarro – Universidad Nacional Autónoma de México

 

Abstract

In this study, we archived nitrogen-doped graphene by applying a post-treatment synthesis method taking graphene oxide and melamine as precursors. Graphene oxide (GO) is synthesized by the modified Hummers method, which promotes the presence of epoxy, hydroxyl groups, and some other oxygen species. The samples were characterized by UV-vis, FTIR, Bohem titration and XPS to study their composition. Its structure was studied by XRD, optical microscopy, AFM and TEM. The results show the presence of the expected functional groups in a two-dimensional multilayer structure. Nitrogen-doped graphene was obtained by heating graphene oxide and melamine mixtures to 700 °C. Through experimental adjustments to the concentration of oxygen functional groups within graphene oxide, achieved by modifying key parameters such as the edge:area ratio of the starting materials and the temperature of the synthesis reaction, we were able to confirm that some oxygen functional groups improve the formation of a unique species of nitrogen. Using density functional theory calculations, we investigated the vibrational modes of graphene oxide, reduced graphene oxide, and nitrogen-doped graphene and corroborated them with experimental data. The mechanism to form graphitic nitrogen in nitrogen-doped graphene was also studied by adsorption of melamine onto graphene oxide, desorption of NH3, and its interaction with the oxygen functional group to form the graphitic nitrogen site. 

We thank, DGAPA-UNAM projects IN111223, IA100624, IN101523, and the CONACHYT PROJECTS Al-S-17539. Calculations were performed in the DGCTIC-UNAM project no. LANCAD-UNAM-DGTIC-422 and project no. LANCAD-UNAM-DGTIC-382. We also thank Dr. Lazaro Huerta from IIM-UNAM and Eduardo Murillo from CNyN-UNAM for assistance with some characterizations and AG&P and LVMM groupmates for fruitful discussions.

Understanding the role of carboxylic acid surfactants growth inhibition effect in the area selective atomic layer deposition: The case of ZnO growth on Cu and Cu2O

– L.E. López-González – Universidad Nacional Autónoma de México

 

Abstract

A recently explored fabrication approach is area selective deposition (ASD), whose main advantage is that it allows growth only at specific regions in a self-aligned manner1. Typically, the control of surface functional groups is the approach employed to modify the deposition chemistry2 by using self-assembled monolayers (SAMs). Modifying surface functional groups before the atomic layer deposition (ALD) process gives rise to the area-selective atomic layer deposition technique (AS-ALD) 3. Even though AS-ALD has great potential, it faces challenges that must be overcome, such as selectivity loss with increasing ALD cycles. In this context, the study of the adsorption of surfactants in surfaces and the effect that co-adsorbed ALD precursor molecules have on the surface–inhibitor molecule system is of interest to further understand the factors impacting selectivity loss in SAM AS-ALD. Here, we report a detailed adsorption process of acetic acid (AA) as a model of carboxylic acid self-assembled monolayers head group- on Cu and Cu2O (111) surfaces and the effect of diethyl zinc (DEZ) on its adsorption geometry on Cu2O (111) by using quantum chemical calculations. The most stable adsorption configurations were obtained considering electrostatic potential compatibility from the molecule and surface. Overall, the adsorption behavior revealed bidentate binding as the most stable configuration. Weak van der Waals interactions are key in AA adsorption on Cu (111), while in Cu2O (111), coordination and hydrogen bonds dominated the interaction. AA adsorption geometry on Cu2O revealed that DEZ has no significative impact on the monodentate and bidentate adsorption modes. These results highlight the significance of the different adsorption modes for achieving area-selective deposition using atomic layer deposition and soft removal SAM molecules.

References
1 M. Pasquali, S. De Gendt and S. Armini, Understanding the impact of Cu surface pre-treatment on Octadecanethiol-derived self-assembled monolayer as a mask for area-selective deposition, Appl Surf Sci, 2021, 540, 148307.
2 D. Bobb-Semple, L. Zeng, I. Cordova, D. S. Bergsman, D. Nordlund and S. F. Bent, Substrate-dependent study of chain orientation and order in alkylphosphonic acid self-assembled monolayers for ALD blocking, Langmuir, 2020, 36, 12849–12857.
3 F. S. Minaye Hashemi, B. R. Birchansky and S. F. Bent, Selective Deposition of Dielectrics: Limits and Advantages of Alkanethiol Blocking Agents on Metal–Dielectric Patterns, ACS Appl Mater Interfaces, 2016, 8, 33264–33272.

Understanding DFT+U: Analyzing the Density of States and Band Structure in MnSi2N4

– B. Pedroza Rojas – Universidad Autónoma del Estado de Hidalgo

 

Abstract

Layered two-dimensional magnetic materials have been used in recent years to design magneto-resistance electronic devices. These materials are often theoretically predicted before being obtained experimentally. An adequate and careful theoretical framework for this purpose is Density Functional Theory (DFT), which includes various pseudopotentials and substantial research backing it. However, a significant challenge arises when transition metals are involved. The unfilled d and f orbitals of these metals require semi-empirical considerations or hybrid pseudopotentials, which often do not accurately describe the electronic and magnetic properties in practice. Furthermore, the demand for durable and faster components can be met by 2D materials like the MA2Z4 family, a promising alternative. However, M can represent any transition metal, and many studies have been published without these semi-empirical treatments. In this context, we analyze the correction of 3d orbitals in MnSi2N4 using the Hubbard method according to Dudarev’s formulation. 

We thank to CONACYT (grant No. 432), to DGSCA-UNAM Supercomputer Center (project 3-2023) and to LANCAD Supercomputer Center (project 23-2023) for valuable computer resources used in this research.

Análisis computacional de propiedades de fármacos en el tratamiento de la diabetes

– Jesús Pérez Aguilar – Benemérita Universidad Autónoma de México

 

Abstract

La diabetes mellitus es la segunda enfermedad con mayor prevalencia en la población mexicana, afectando aproximadamente al 10.3% de la población, lo que equivale a 14.1 millones de personas. En la actualidad, se han desarrollado tratamientos con péptidos que inhiben la hormona Glucagón-1 (GLP-1) y aumentan la producción de insulina. Utilizando métodos computacionales como la Dinámica Molecular (DM), es posible investigar aspectos microscópicos que complementan los estudios experimentales y contribuyen al desarrollo de fármacos más específicos. En este trabajo se presenta un estudio detallado de estructuras de interés en el tratamiento de la diabetes. Para el análisis, se emplearon estructuras cristalográficas obtenidas del Protein Data Bank, de las cuales se aislaron los péptidos de interés: semaglutida, liraglutida, tirzepatida y exenatida. Durante las simulaciones de DM, el agua se incluyó explícitamente utilizando el modelo TIP4P, conocido por su alta capacidad predictiva de las propiedades del agua como solvente. Las estructuras solvatadas se neutralizaron con iones monovalentes y se añadió sal a una concentración de 0.154M para emular condiciones fisiológicas, manteniendo una temperatura de 309.65 K y una presión de 1 bar. Se generaron dos tipos de sistemas para el estudio. El primer sistema consiste en el fármaco disuelto en agua bajo condiciones fisiológicas. El segundo sistema incluye el fármaco en presencia de glucosa e insulina, también en condiciones fisiológicas. Estas simulaciones permiten una comprensión más profunda de la interacción entre los péptidos y su entorno, proporcionando información valiosa para el diseño de tratamientos más eficaces para la diabetes.

Computational study of the TiO2-surface LP gas detection mechanisms

– Jonathan E. Rodriguez Hueso – Universidad Nacional Autónoma de México

 

Abstract

Understanding and manipulating materials at the atomic scale has become a fundamental aspect of engineering the materials involved in high-performance devices. In the present work, we report the sensing behavior and structural properties of the titanium dioxide surface (TiO2) of the optimized structures and describe the structural and electronic properties of the interaction between the molecules that integrate the LP gas (butane, propane, and methanethiol) and the anatase TiO2 surface. The aim was to evaluate the feasibility of this material in a high-performance LP gas sensor device. Results demonstrate that the methanethiol of LP gas was the most reactive molecule to the TiO2 surface. In addition, the electrical properties calculated show the need to induce oxygen surface vacancies or a rearrangement of the (101) surface TiO2 anatase to make the interaction with methanethiol detectable. Our results are a step further in the design of LP gas sensing devices with modified TiO2 substrates.

DGAPA-UNAM IG101124, IA100624, IN101523, IG101623, and Conhacyt grants A1-S-9070 and A1-S-26789 of the Call of Proposals for Basic Scientific Research 2017–2018 for partial financial support. Calculations were performed in the DGCTIC-UNAM Supercomputing Center, projects LANCAD-UNAM-DGTIC-368, LANCAD-UNAM-DGTIC-051, LANCAD-UNAM-DGTIC-390, and LANCAD-UNAM-DGTIC-422 We thank Aldo Rodriguez-Guerrero; Rodrigo Ponce; J. I. Paez Ornelas and nanomaterials modeling department for technical support.

El uso de materiales topológicos en la reacción de evolución de Hidrógeno

– Jonathan E. Rodriguez Hueso – Universidad Nacional Autónoma de México

Abstract

La reacción de evolución de hidrógeno (HER, por sus siglas en inglés) es un proceso químico en el cual se produce gas hidrógeno (H2) a partir de protones (H+) y electrones (e-), típicamente en presencia de un catalizador [1]. Esta reacción tiene varias aplicaciones, y una de las más notables es la batería de hidrógeno, que permite un medio de almacenamiento de energía limpia que solo deja agua como producto residual. El problema es que el catalizador más eficiente para esta reacción es el platino, el cual es aún menos abundante que el oro. Se están haciendo esfuerzos para encontrar una alternativa más económica para un catalizador para HER, y se ha encontrado un lugar prometedor en los materiales cuánticos topológicos (TQM), aquí presentaremos los resultados de la investigación bibliográfica sobre dicho tema. Estos materiales tienen propiedades eléctricas muy únicas que pueden explicarse estudiando su estructura electrónica utilizando conceptos matemáticos que pertenecen a la rama de la Topología. Exhiben estados superficiales que son robustos frente a perturbaciones e impurezas, así como una alta movilidad de carga, propiedades que les dan el potencial de tener una alta actividad catalítica para HER, similar o incluso mayor que la del Pt, proporcionando un catalizador efectivo sin la necesidad de metales preciosos.

Referencias
1. Yang, Q. (2021) The rise of topologically non-trivial materials for hydrogen
evolution electrocatalysis. Max-Planck-Institu für Chemische Physik fester
Stoffe.
2. Xie, R., Weng, H., Chai, G. (2022). Progress, Advantages and Challenges
of Topological Material Catalysts. Perspective. Small Science

Session 1 - Wednesday, August 28

– Fernando Rojas Íñiguez – Director Centro de Nanociencias y Nanotecnología, UNAM.

AI-driven Fully Quantum (Bio)Molecular Simulations: From Dream to Reality

– Alex Tkatchenko – University of Luxembourg

 

Abstract

The convergence between accurate quantum-mechanical (QM) models (and codes) with efficient machine learning (ML) methods seem to promise a paradigm shift in molecular simulations. Many challenging applications are now being tackled by increasingly powerful QM/ML methodologies. These include modeling covalent materials, molecules, molecular crystals, surfaces, and even whole proteins in explicit water (https://www.science.org/doi/abs/10.1126/sciadv.adn4397). In this talk, I attempt to provide a reality check on these recent advances and on the developments required to enable fully quantum dynamics of complex functional (bio)molecular systems. Multiple challenges are highlighted that should keep theorists in business for the foreseeable future:

(1) Ensuring the accuracy of high-level QM methods (https://doi.org/10.1038/s41467-021-24119-3; https://doi.org/10.1038/s41586-023-06587-3), 

(2) Describing intricate QM long-range interactions (https://doi.org/10.1126/sciadv.aax0024; https://doi.org/10.1126/science.aae0509; https://doi.org/10.1103/PhysRevLett.128.106101), 

(3) Treating quantum electrodynamic effects that become relevant for complex molecules (https://doi.org/10.1021/acs.jpclett.1c04222; https://doi.org/10.1103/PhysRevResearch.4.013011).

(4) Developing increasingly accurate, efficient, scalable, and transferable ML architectures for molecules and materials (https://doi.org/10.1038/s41467-022-31093-x; https://arxiv.org/abs/2209.14865; https://arxiv.org/abs/2209.03985).

(5) Accounting for the quantum nature of the nuclei and the influence of external environments (https://doi.org/10.1038/s41467-020-20212-1; https://doi.org/10.1038/s41467-022-28461-y).

I argue that only a conjunction of all these developments will enable the long-held dream of fully quantum (bio)molecular simulations.

Strategies to boost electrical conductivity in porous materials: a computational perspective

– Joaquin Calbo – Universitat de València

Abstract

Despite being traditionally considered as insulators, (metal)-organic frameworks are porous crystalline structures that have proved to be efficient for the transport of electrical charge upon suitable chemical design for next-generation applications.[1] Among the most promising strategies to infuse charge conductivity in porous crystals, we emphasize the π-π stacking of electroactive ligands, the incorporation of guest molecules within the pores, or the exploitation of mixed valency in chemically available metal redox pairs. These porous conductors are meant to unlock new avenues in the design of novel materials for efficient energy conversion and storage.[2]

Herein, we showcase the theoretical modelling of advanced porous materials that take advantage of each of these chemical strategies to boost charge conductivity. First, the charge transport of a series of purely organic porous frameworks based on H-bonding (HOFs) is described in terms of a through-space hopping of charge carriers between stacked electroactive TTF-based ligands in a zwitterionic form (Figure 1a).[3] Second, one of the first examples of perylene-based MOFs with semiconductivity is presented based on the partial oxidation of the ligand upon inclusion of I2 dopant, and promoted by a herringbone CH···π perylene-perylene stacking (Figure 1b).[4] Last, the record 3D conducting MOF based on Fe(II)/Fe(III) redox pair and tetrazole ligand Fe2(BDT)3 (Figure 1c)[5] is characterized theoretically, and compared with its polymorphs, to unveil the origin of its striking high charge transport.

Figure 1. Crystal structure of a) TTF-based MUV-20a, b) perylene-based Per-MOF, and c) tetrazole-based Fe2(BDT)3 frameworks.

References

(1) Calbo, J.; Golomb, M. J.; Walsh, A. J. Mater. Chem. A 2019, 7, 16571-16597.

(2) Xie, L. S.; Skorupskii, G.; Dincă, M. Chem. Rev. 2020, 120, 8536–8580.

(3) Vicent-Morales, M.; Esteve-Rochina, M.; Calbo, J.; Ortí, E.; Vitórica-Yrezábal, I. J.; Mínguez Espallargas, G. J. Am. Chem. Soc. 2022, 144, 9074–9082.

(4) Valente, G.; Esteve-Rochina, M.; Paracana, A.; Rodríguez-Diéguez, A.; Choquesillo-Lazarte, D.; Ortí, E.; Calbo, J.; Ilkaeva, M.; Mafra, L.; Hernández-Rodríguez, M. A.; Rocha, J.; Alves, H.; Souto, M. Mol. Syst. Des. Eng. 2022, 7, 1065-1072.

(5) Xie, L. S.; Sun, L.; Wan, R.; Park, S. S.; DeGayner, J. A.; Hendon, C. H.; Dinca, M. J. Am. Chem. Soc. 2018, 140, 7411-7414.

Elevating the Accuracy of Density Functional Theory for Condensed Phase Simulations through Machine Learning and Many-Body Techniquesvited

– Saswata Dasgupta – University of California, San Diego

Abstract

Accurately depicting the electronic structure and dynamics of condensed phases is crucial for understanding their phase behavior and reactivity. Among the quantum chemistry techniques, Density Functional Theory (DFT) is extensively employed to model the properties of condensed-phase systems, despite its high computational demands that hinder the use of more accurate modern density functionals. To address this, we introduce innovative data-driven many-body potential energy functions trained with arbitrary DFT functionals (MB-DFT), which preserve the accuracy of the parent functionals consistently from gas to condensed phases. Despite these advancements, no existing density functional has achieved the necessary accuracy to predict the properties of hydrated systems across their full phase diagram. To bridge this gap, we present the Density-Corrected SCAN (DC-SCAN) method that elevates the accuracy of the SCAN functional to the level of coupled-cluster theory, the gold standard for chemical accuracy. This method allows for accurate descriptions of aqueous systems from gas to condensed phases within our data-driven many-body DFT framework. However, like most polarizable force fields, these MB-DFT potentials cannot participate in chemical reactions. To model chemical reactions in the condensed phase, we have combined the accuracy of DC-SCAN with the capabilities of neural network potentials. This integration has resulted in the development of reactive machine-learned potentials capable of studying phenomena such as water autoionization and proton transport within confinement, facilitated by advanced enhanced-sampling techniques. Our findings provide not only an accurate estimation of the autoionization constant but also emphasize the significant role of the Grotthuss mechanism in acid/base equilibria.

Molecular Simulations of Extraterrestrial Organic Minerals

– Richard Remsing – Rutgers University

Abstract

Titan, Saturn’s largest moon, has a thick atmosphere rich in organic molecules and a cold surface temperature of 94 K. As a result, many of the organic molecules produced by photochemistry in the atmosphere condense onto the surface as organic liquids and solids. The resulting crystalline organic solids coat Titan’s surface and are referred to as cryominerals, in analogy to minerals on Earth. Cryominerals can play important roles in Titan’s surface geology, geochemistry, and even potential prebiotic chemistry. To fully understand chemical processes in these unique environments, a molecular-level picture is needed, which we are working towards using a combination of ab initio simulations and machine learning models. I will discuss our recent work modeling structure and dynamics in several Titan cryominerals, including the potential for these solids to exist in plastic crystal phases, in which molecules are translationally ordered but rotationally disordered. The disorder present in plastic crystals generally impacts important thermodynamic and mechanical properties relevant to surface processes, such as reducing elastic moduli. I will also discuss the implications of our work for understanding the properties of Titan’s surface and for understanding driving forces for prebiotic chemistry in Titan-like non-aqueous environments.

Recycled Macrocycles – in silico design of cyclic peptides targeting protein-protein interactions

– Brianda Lopez Santini – CeMM Research Center for Molecular Medicine & Max Planck School, Vienna  

Abstract

This talk focuses on the computational design of cyclic peptides for modulating protein interactions using the cPEPmatch method. This novel approach identifies cyclic peptide templates by structural matching at protein interfaces, targeting hot spots to enhance binding specificity. The method has been validated against known interactions and demonstrated through computational predictions confirmed experimentally. The research highlights the therapeutic potential of cyclic peptides in drug discovery and the development of new biomedical strategies.

Optimization of exchange and correlation functionals using Machine learning

Marivi Fernandez-Serra – Stony Brook University

Abstract

Density Functional Theory (DFT) is the standard formalism to study the electronic structure of matter at the atomic scale. The balance between accuracy and computational cost that DFT-based simulations provide allows researchers to understand the structural and dynamical properties of increasingly large and complex systems at the quantum mechanical level. The fundamental theorems of density functional theory ensure that there exists an exact functional which provides the exact energy of a system from its exact density. This functional is minimized at a fixed electron number and a fixed external potential by the exact electron density, hence providing both the density and and energy. However, doing this exactly comes at a colossal computational cost. It is, however, possible to approximate the exact functional, providing a balance between accuracy and computational cost. In this seminar we will learn how to use machine learning methods to construct approximations of the exact functional. I will first identify the strengths and weaknesses of current approaches to this problem. I will also show how to implement general methods to facilitate their incorporation in available electronic structure codes.

Sesión 2 - Thursday, August 29

More-predictive density functionals, symmetry breaking, and strong correlation

– John P. Perdew – Tulane University

Abstract

Approximate density functionals constructed to satisfy known mathematical
properties of the exact density functional for the exchange-correlation energy of a many-electron system can be predictive over a wide range of materials and molecules. The strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation [1] satisfies 17 exact constraints, and nicely describes some systems that were formerly thought to be beyond the reach of density functional theory, such as the cuprates [2]. Ground states that break the symmetry of a Coulomb-interacting Hamiltonian can be understood as dynamic density or spin-density fluctuations that drop to low or zero frequency [3,4] and so persist over long times. In many cases, symmetry breaking transforms the strong correlation in a symmetry-unbroken wavefunction into moderate correlation like that found in the uniform electron gas of high or valence-electron density (an “appropriate norm” for constraint-based approximations).

Supported by NSF DMR-1939528 and DE-SC0018331

[1] J. Sun, A. Ruzsinszky, and J.P. Perdew, Phys. Rev. Lett. 115, 036402 (2015)
[2] J.W. Furness, Y. Zhang, C. Lane, I.G. Buda, B. Barbiellini, R.S. Markiewicz, A.
Bansil, and J. Sun, Commun. Phys. 1, 11 (2018)
[3] P.W. Anderson, Science 177, 393 (1972)
[4] J.P. Perdew, A. Ruzsinszky, J. Sun, N.K. Nepal, and A.D. Kaplan, Proc. Nat.
Acad. Sci. USA 118, e2017850118 (2021).

Probabilistic AI meets computational chemistry

– Rodrigo A. Vargas-Hernandez – McMaster University

Abstract

Machine learning tools offer significant advantages in computational chemistry by providing innovative solutions to longstanding challenges. This talk will explore several pivotal technologies, including automatic differentiation, activation functions, and generative models, and their applications in this field.
Activation functions, a fundamental component of neural networks, also hold promise for quantum chemistry applications. In the first part of my talk, I will introduce automatic differentiation, a technique that enhances the accuracy and efficiency of gradient calculations in semi-empirical models. Following this, I will demonstrate how the softmax function can be utilized to parameterize the occupation numbers of natural orbitals in reduced density matrix approaches.
Finally, I will discuss the application of generative models, specifically normalizing flows, in addressing the orbital-free density functional problem.

Transferability in Data-Driven Density Functionals

Stefan VuckovicUniversity of Fribourg

 

Abstract

The promised revolution of machine-learned based density functional approximations (DFAs) is hampered by far broader applicability of old-school DFAs [1]. In this talk, I will discuss the issue of transferability in machine-learned DFAs, beginning with its definition [2] and then exploring potential solutions.

Aplicaciones de aprendizaje automático a la ciencia de materiales 

Luis PellegrinUniversidad Autónoma de Baja California

Abstract

Se llevará a cabo una revisión de trabajos recientes que han aplicado aprendizaje automático a la ciencia de materiales. El objetivo de la charla se centrará en conocer las ventajas, características y oportunidades que representa la sinergia entre estas dos áreas de estudio.

Machine learning electronic structures

Michele PavanelloRutgers University-Newark

Abstract

The most enthusiastic modeler claims to accurately predict chemical reaction thermodynamics, kinetics, and nonequilibrium dynamics. Unfortunately, current models, while more robust and predictive than in past years, are often either too approximate to provide a faithful representation of reality or too computationally expensive to yield answers within a reasonable time. The talk argues that it is imperative to develop new-generation electronic structure methods to aid experiments, as these face different yet similarly difficult circumstances. The talk introduces electronic structure models based on machine learning. It is argued that machine learning methods are best employed learning quantities rich in information, such as the electron density, density matrix or even the wavefunction. These models are inherently more useful than those targeting single quantities, such as energy, dipole, etc. Models for the one-electron density matrix of small to medium sized molecules and their response to external perturbation are presented. We also present methods to learn two-electron density matrices as a route for accounting for electronic correlation explicitly at force-field cost. The presented methods are available to the broader community as open-source Python implementations in the QMLearn software, http://qmlearn.rutgers.edu.

Multiscale Biomolecular Simulations: From Mechanistic Insights to Cancer

– G. Andrés Cisneros – University of Texas at Dallas

Abstract

Computational biomolecular simulations based on molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) methods have become sufficiently accurate to be able to predict specific features of protein systems. We have developed various programs and tools to perform QM/MM simulations with advanced potentials, and to assess various features of biomolecular systems. We have also developed a comprehensive approach to find and characterize the impact of cancer mutants on target proteins, Our approach employs a new method for discovery and statistical validation of single nucleotide polymorphisms (SNPs) on specific genes called HyDn–SNP–S, followed by atomistic simulations via. We will present examples of the use of these approaches to investigate the structural, dynamic and mechanistic features of five DNA transaction enzymes and how they can be used for various applications including the development of new drugs or uncovering how mutations affect enzymatic catalysis.

Session 3 - Friday, August 30

Transport in Solids: An Open Quantum Systems Approach

– Jorge Sofo – PennState University

Abstract

Decoherence, dissipation, and thermalization are key ingredients for a quantum theory of transport processes. To go beyond the semiclassical description given by the quantum Boltzmann equation, we explore the use of the generalized, quantum Langevin equation. We describe the hydrodynamic regime with a single memory function approximation. We find that interband coherences are relevant even in the limit of weak scattering, where the Boltzmann description is deemed appropriate. As an example, we discuss the case of narrow band gap semiconductors at low doping that are commonly used in thermoelectric applications. In these materials, Boltzmann wrongly predicts zero conductivity at zero temperature, while we obtain a finite residual conductivity. This improvement in the description of transport coefficients is achieved without extra computational cost and can be easily implemented in current electronic structure codes and is already implemented in Exciting and PAOFLOW. The memory-function approach to quantum dynamics has a long history of development. I will review the basics of this approach and provide a perspective on possible applications in the description of decoherence and dissipation in materials.

Current vortices in aromatic carbon molecules

– Yenny Priscila Ortiz Acero – Universidad de Barcelona

Abstract

The local current flow through three small aromatic carbon molecules, namely, benzene, naphthalene, and anthracene, is studied. Applying density functional theory and the nonequilibrium Green’s function method for transport, we demonstrate that pronounced current vortices exist at certain electron energies for these molecules. The intensity of these circular currents, which appear not only at the antiresonances of the transmission but also in the vicinity of its maxima, can exceed the total current flowing through the molecular junction and generate considerable magnetic fields. The π electron system of the molecular junctions is emulated experimentally by a network of macroscopic microwave resonators. The local current flows in these experiments confirm the existence of current vortices as a robust property of ring structures. The circular currents can be understood in terms of a simple nearest-neighbor tight-binding Hückel model. Current vortices are caused by the interplay of the complex eigenstates of the open system which have energies close to the considered electron energy. Degeneracies, as observed in benzene and anthracene, can thus generate strong circular currents, but also nondegenerate systems like naphthalene exhibit current vortices. Small imperfections and perturbations can couple otherwise uncoupled states and induce circular currents.

GPU accelerated QM/MM molecular dynamics simulations of biomolecular
systems

– Andreas Goetz – University of California San Diego

Abstract

Quantum mechanics / molecular mechanics (QM/MM) approaches enable simulations of molecular properties and reaction mechanisms in enzymes and complex condensed phase systems. However, QM/MM simulations are orders of magnitude more computationally intensive than MM simulations. Efficient software implementations are thus essential to enable meaningful QM/MM molecular dynamics (MD) simulations. I will give a background on the current high-performance computing hardware landscape and discuss our efforts in developing QUICK and its integration with the AmberTools biomolecular simulations package to enable large scale QM/MM MD simulations. QUICK is a massively parallel open-source quantum chemistry program for Hartree-Fock and density functional theory (DFT) calculations with Gaussian basis functions that runs on graphics processing units (GPUs). Both Nvidia and AMD hardware is supported. Importantly, the implementation in AmberTools includes the ambient potential composite Ewald method that incorporates long-range electrostatic interactions without truncation for condensed phase simulations under periodic boundary conditions. This makes it particularly easy to perform accurate QM/MM MD simulations without introducing numerical noise or neglecting potentially relevant electrostatic interactions between QM and MM regions. 

Spin Topology in Insulating Materials

– Rafael Gonzalez-Hernandes – Universidad del Norte

Abstract

In this work, we study the role of electron spin in establishing topological invariants in insulating materials. We explore how the spin valence operator, induced by the spin operator, provides crucial information about spin Chern class phases. Gapped spin valence spectra denote constant spin Chern numbers, defining materials as spin Chern insulators [1]. Conversely, changes in spin Chern numbers occur at zero spin spectrum values, characterizing materials as spin Weyl topological insulators [2]. We also introduce the average spin Chern number [3] to classify non-trivial spin transport properties in 3D topological insulators, which closely correlates with the spin Hall conductivity within the
bandgap.


[1] E. Prodan, Phys. Rev. B 80, 125327 (2009), https://link.aps.org/doi/10.1103/PhysRevB.80.125327
[2] R. González-Hernández and B. Uribe, Phys. Rev. B 109, 045126 (2024),
https://link.aps.org/doi/10.1103/PhysRevB.109.045126.
[3] R. González-Hernández and B. Uribe, arxiv: 2404.08595 (2024).
https://doi.org/10.48550/arXiv.2404.08595.

Más allá de los fermiones de Weyl y Dirac: Multifolds, topología y propiedades de espín

Íñigo Robredo Donostia International Physics Center, 20018 Donostia-San Sebastian, Spain

Max Planck Institute for Chemical Physics of Solids, 01187 Dresden, Germany

Abstract

El descubrimiento de semimetales topológicos con cruces de bandas multifold ha abierto una nueva y emocionante frontera en el campo de la física topológica. Estos materiales exhiben grandes números de Chern, lo que conduce a largos arcos de Fermi, protegidos por simetrías cristalinas o por topología. El impacto de estos cruces multifold se extiende más allá de la ciencia de superficies, ya que no están restringidos por la clasificación de Poincaré de cuasipartículas y solo necesitan respetar la simetría cristalina de uno de los 1651 grupos espaciales magnéticos, no teniendo análogo en altas energías. Los últimos años, estas cuasipartículas han sido estudiadas por sus propiedades de espín, como prometedores materiales no magnéticos en el campo de la espintrónica. En esta charla, analizaremos las propiedades básicas de estas nuevas cuasipartículas, así como los materiales donde se han descubierto.

Experimental and Computational Studies of 2D Carbides and Carbonitrides (MXenes)

Yury GogotsiDrexel University

Abstract

2D carbides, nitrides, and carbonitrides of early transition metals known as MXenes are among the few nanomaterials that have jumped into the limelight not only because of their exotic structure or attractive properties but also because of numerous practical applications [1]. The family of MXenes has  been expanding rapidly since the discovery of Ti3C2 at Drexel University in 2011. Close to 50 different stoichiometric MXenes, dozens of solid solutions, high-entropy materials and MXenes with various surface terminations have been reported. The structure and properties of numerous other MXenes have been predicted by DFT. We are working to synthesize some of the predicted MXene compositions. The availability of solid solutions on M and X sites, multi-element high-entropy MXenes, control of surface terminations, and the discovery of out-of-plane ordered double-M o-MXenes (e.g., Mo2TiC2), as well as in-plane ordered i-MAX phases and their i-MXenes offer the potential for producing an infinite number of new 2D materials. This presentation will describe the state of the art in the field of MXene synthesis [2,3]. Synthesis-structure-properties relations of MXenes will be described [4]. The versatile chemistry of the MXene family renders their properties tunable for a large variety of energy-related, electronic, optical, biomedical, and other applications. In particular, the applications of MXenes in electrochemical energy storage and harvesting, electrocatalytic water splitting and water purification/desalination are promising [1]. However, MXene antennas, sensors, actuators, as well as coatings for EMI shielding and thermal regulation are equally attractive. 

  1. A. VahidMohammadi, J. Rosen, Y. Gogotsi, The World of Two-Dimensional Carbides and Nitrides (MXenes), Science, 372, eabf1581 (2021).
  2. H. Ding, Y. et al, Chemical-scissor-mediated structural editing of layered transition metal carbides, Science, 379, 1130–1135 (2023).
  3. H. Shao, S. Luo, A. Descamps-Mandine, K. Ge, Z. Lin, P.-L. Taberna, Y. Gogotsi, P. Simon, Synthesis of MAX phase nanofibers and nanoflakes and the resulting MXenes, Advanced Science, 10 (1) 2205509 (2023).
  4. K. R. G. Lim, M. Shekhirev, B. C. Wyatt, B. Anasori, Y. Gogotsi, Z. W. Seh, Fundamentals of MXene synthesis, Nature Synthesis, 1 (8) 601-614 (2022).

Plenary Speakers

Distinguished University and Charles T. and Ruth M. Bach Professor

Drexel University

Professor

Tulane University

Professor and Department Head-Physics

University of Texas

Professor

University of Luxembourg

Professor

Stony Brook University

PennState University

Invited Speakers

Professor

Rutgers University-Newark

Principal Investigator

University of California San Diego

Professor

University of Valencia

Postdoctoral Researcher

University of California San Diego

Assistant Professor

McMaster University

Postdoctoral Researcher

Universidad de Barcelona

Assistant Professor

University of Fribourg

Assistant Professor

Universidad Autónoma de Baja California

Professor

Universidad del Norte

Assistant Professor

Rutgers University-New Brunswick

Postdoc

Max Planck Institute for Chemical Physics of Solids

Researcher

CeMM Research Center for Molecular Medicine

Short Courses

Hands-on workshops (from 15:00 to 19:00 hrs, Pacific Standard Time).

We will send a personalized link to all attendees registered for the short courses shortly.

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