Juan J. de Pablo

Juan J. de Pablo

University of Chicago

H-index: 117

North America-United States

Professor Information

University

University of Chicago

Position

Professor of Molecular Engineering

Citations(all)

52441

Citations(since 2020)

16707

Cited By

42455

hIndex(all)

117

hIndex(since 2020)

61

i10Index(all)

608

i10Index(since 2020)

411

Email

University Profile Page

University of Chicago

Research & Interests List

molecular modeling

polymers

liquid crystals

DNA

proteins

Top articles of Juan J. de Pablo

Blue phase liquid crystals in a Grandjean–Cano cell

Blue phase liquid crystals are soft photonic crystals that are of interest for sensing and display applications. In recent years, considerable progress has been made in forming blue phase single crystals on chemical patterns. Blue phase single crystals are appealing for technological applications owing to their optical homogeneity. To study single crystal formation when the thickness is incommensurate with blue phase lattice size we prepare cells with a thickness gradient or a “Grandjean–Cano cell”. We observe formation of stripes in the direction perpendicular to the thickness gradient in blue phase single crystals. The stripes occur at a thickness interval significantly smaller than the lattice size. To understand the origin of these mysterious stripes we perform Landau-de Gennes based continuum simulations. Based on experimental and theoretical findings we speculate that the spacing between stripes is related to the …

Authors

Kushal Bagchi,Tadej Emersic,José Martínez-González,Juan De Pablo,Paul Nealey

Journal

Bulletin of the American Physical Society

Published Date

2024/3/4

Understanding and Controlling Polymer-Porous Solid Interactions for Polymer Upcycling

Recent reports have shown that metal-functionalized high surface area porous materials can catalyze the deconstruction of various polymers. To enable efficient and selective polymer upcycling reactions, it is critical to understand and control the interactions between polymers and porous catalyst materials. In this presentation, I will describe our collaborative efforts to understand these interactions by modifying silica-based porous solids with atomic layer deposition (ALD). Based on capillary rise infiltration measurement of polyethylene and polystyrene into ALD-modified porous solids and calorimetry characterization of hexane and benzene adsorption onto such porous solids, we show that there is a strong correlation between the polymer-solid interfacial energy and the heat of gas adsorption. This trend is rationalized by calculating the interaction energy between small molecules and surfaces using density …

Authors

Daeyeon Lee,Tian Ren,Renjing Huang,Ching-Yu Wang,Chuting Deng,Yinan Xu,Kai Shen,John Vohs,Juan De Pablo,Raymond Gorte

Journal

Bulletin of the American Physical Society

Published Date

2024/3/7

Simulation Study of Self Assembly of Block Copolymers upon Solvent Evaporation

Block copolymers (BCPs) have great technological potential due to their capacity to generate uniform and periodic nanoscale structures through microphase separation depending on the composition, and the segregation strength. For membranes applications, BCPs provide a bottom-up approach to form isoporous membranes that are useful for ultrafiltration processes involving functional macromolecules, colloids, and water purification. Isoporous BCP membrane fabrication occurs by evaporating solvent particles from well-mixed solutions of asymmetric BCPs and solvents in film states, and micro-phase separated structures propagate throughout the film. While the self-assembled structure of block copolymers in bulk systems has been extensively studied, the morphological changes of these block copolymers during solvent evaporation have not been fully explored.In this study, we examined the properties of …

Authors

Juhae Park,Ludwig Schneider,Juan De Pablo

Journal

Bulletin of the American Physical Society

Published Date

2024/3/6

Data-Driven Simulation of Chromatin Structure and the Epigenetic Code

The interplay between epigenetic marks and chromatin structure is increasingly appreciated as crucial to biological function. However, the full features of chromatin organization in three dimensoins are not fully understood and are actively being investigated in both theory and experiment. Here we present a chromosome scale model to study the relationship between one-dimensional epigenetic sequences and three-dimensional chromatin structure. The sequence-structure relationship presents some similarities to conventional block copolymers, as described by previous models, but also departs from a purely synthetic polymer due to the overlapping and interacting nature of epigenetic marks and machinery. Understanding these unique features of the epigenetic code will be crutial to future diagnostic and therapeudic efforts to modulate chromatin organization by way of targeted epigenetic engineering.

Authors

Soren Kyhl,Juan De Pablo

Journal

Bulletin of the American Physical Society

Published Date

2024/3/6

Thermodynamic and Transport Properties of Binary Mixtures of Polyethylene and Higher n-Alkanes from Physics-Informed and Machine-Learned Models

Thermodynamic and transport properties for the binary mixtures of N-Ethylethanamine (EEA) with 1-pentanol up to 1-nonanol at temperatures 298.15 K, 308.15 K, and 318.15 K were reported in this study. Calculation of the excess molar volumes exhibits that the considered mixtures have a negative deviation from the Raoult’s Law. Deviation from ideality increases as the alkyl chain increases. Strong molecular interactions occur in the above binary mixtures due to the formation of hydrogen bonds, dipole-dipole interactions and dispersive forces. Obtaining results were analysed to gain information about the liquid structure in the binary mixtures. The investigation has shown that increasing the alcohol chain length reinforces the strength of intermolecular forces between EEA and 1-alkanol. The perturbed chain statistical association fluid theory (PC-SAFT) with the correlative ability was implemented to the densities of …

Authors

mohammad almasi

Journal

Physics and Chemistry of Liquids

Published Date

2021/2/19

Generative BigSMILES: an extension for polymer informatics, computer simulations & ML/AI

The BigSMILES notation, a concise tool for polymer ensemble representation, is augmented here by introducing an enhanced version called generative BigSMILES. G-BigSMILES is designed for generative workflows, and is complemented by tailored software tools for ease of use. This extension integrates additional data, including reactivity ratios (or connection probabilities among repeat units), molecular weight distributions, and ensemble size. An algorithm, interpretable as a generative graph is devised that utilizes these data, enabling molecule generation from defined polymer ensembles. Consequently, the G-BigSMILES notation allows for efficient specification of complex molecular ensembles via a streamlined line notation, thereby providing a foundational tool for automated polymeric materials design. In addition, the graph interpretation of the G-BigSMILES notation sets the stage for robust machine …

Authors

Ludwig Schneider,Dylan Walsh,Bradley Olsen,Juan de Pablo

Journal

Digital Discovery

Published Date

2024

PySAGES: Flexible, advanced sampling methods accelerated with GPUs

Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community-supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a …

Authors

Pablo F Zubieta Rico,Ludwig Schneider,Gustavo R Pérez-Lemus,Riccardo Alessandri,Siva Dasetty,Trung D Nguyen,Cintia A Menéndez,Yiheng Wu,Yezhi Jin,Yinan Xu,Samuel Varner,John A Parker,Andrew L Ferguson,Jonathan K Whitmer,Juan J de Pablo

Journal

npj Computational Materials

Published Date

2024/2/14

Cholesteric Liquid Crystal Control Through Microfluidic Flow Manipulation

Materials capable of undergoing color changes in response to stimuli are of interest for various applications, including sensing, display technology, and camouflage. Cholesteric liquid crystals represent a unique class of soft materials due to their self-assembled helical structure, which is sensitive to various external stimuli and known for its selective light reflection. However, their response to pressure-driven flow in microfluidic channels has largely remained experimentally unexplored. Here, we investigate a cholesteric system with a helical pitch comparable to the wavelength of visible light, enabling it to exhibit structural coloration. We demonstrate that fluid flow can effectively align the helical axis of cholesterics within confined geometries. Before the application of flow, the color of the cholesteric phase remains independent of temperature. However, after flow alignment, a blue shift is observed as the temperature …

Authors

Tadej Emersic,Kushal Bagchi,Aiden Jensen,Paul Nealey,Juan De Pablo

Journal

Bulletin of the American Physical Society

Published Date

2024/3/4

Professor FAQs

What is Juan J. de Pablo's h-index at University of Chicago?

The h-index of Juan J. de Pablo has been 61 since 2020 and 117 in total.

What are Juan J. de Pablo's research interests?

The research interests of Juan J. de Pablo are: molecular modeling, polymers, liquid crystals, DNA, proteins

What is Juan J. de Pablo's total number of citations?

Juan J. de Pablo has 52,441 citations in total.

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