Article
Multidisciplinary Sciences
Qi Zhang, Wei Li, Kaiyao Qiao, Yilong Han
Summary: The nature of liquid-to-glass transition and glass-to-liquid transition is investigated in this study, especially focusing on the surface effects. Colloidal glasses are assembled by vapor deposition and melted by adjusting particle attractions. The results show the presence of a surface liquid layer and an intermediate glassy layer, and similar melting behaviors to crystal premelting and melting. Single-particle kinetics measurements confirm theoretical predictions for the glass surface layer.
Article
Multidisciplinary Sciences
Scott M. Fenton, Poornima Padmanabhan, Brian K. Ryu, Tuan T. D. Nguyen, Roseanna N. Zia, Matthew E. Helgeson
Summary: Colloidal gelation is a method to form processable soft solids using various functional materials. The microscopic processes during gelation that differentiate different types of gels are not well understood. This study presents a method that predicts the minimal conditions for gel solidification and connects the quench path to the emergence of gelled states. The results show that all gels incorporate elements of percolation, phase separation, and glassy arrest, and the slope of the gelation boundary corresponds to the dominant gelation mechanism.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Chemistry, Physical
Xiaoguang Ma, Chandan K. Mishra, P. Habdas, A. G. Yodh
Summary: The study reveals that in two-dimensional, bidisperse colloidal glasses and supercooled liquids, the anharmonicity of in-cage vibrations and effective spring constants show non-monotonic variations with increasing interparticle depletion attraction strength.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Physics, Fluids & Plasmas
Joost de Graaf, Kim William Torre, Wilson C. K. Poon, Michiel Hermes
Summary: Attractive colloids form gels, which are solidlike particle networks suspended in a fluid. The impact of gravity on the gelation process has been rarely studied. In this study, we used simulations to investigate the effect of gravity on gel formation. We found that gravity-induced flows disrupt gelation at low volume fractions, but above a critical volume fraction, the forming gel network dominates the dynamics. The settling of colloids does not significantly affect the final colloidal gel-like sediment.
Article
Physics, Multidisciplinary
Yiming Xia, Xiunan Yang, Junchao Huang, Rui Liu, Ning Xu, Mingcheng Yang, Ke Chen
Summary: We constructed structural order parameters based on local angular and radial distribution functions in dense colloidal suspensions and found significant correlations between these parameters and local dynamics. In particular, the correlation between local orientational order and dynamical heterogeneity was consistently higher than the correlation between conventional two-body structural entropy and local dynamics. The structure-dynamics correlations can be explained by an excitation model where the energy barrier depends on local structural order. Our results suggest that in dense disordered packings, local orientational order is higher than translational order and plays a more important role in determining the dynamics in glassy systems.
PHYSICAL REVIEW LETTERS
(2023)
Article
Multidisciplinary Sciences
Bavand Keshavarz, Donatien Gomes Rodrigues, Jean-Baptiste Champenois, Matthew G. Frith, Jan Ilavsky, Michela Geri, Thibaut Divoux, Gareth H. McKinley, Arnaud Poulesquen
Summary: Colloidal gels are formed by the aggregation of suspended particles in a solvent, exhibiting symmetric relaxation time spectrum and dual properties. The microstructural mechanical network of colloidal gels shows glassy and gel-like characteristics at different length and time scales, which can be described by a simple three-parameter constitutive model.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Chemistry, Physical
Michio Tateno, Taiki Yanagishima, Hajime Tanaka
Summary: The study on colloidal gelation using core-shell fluorescent colloidal particles reveals that the enhancement of local packing and the formation of locally stable rigid structures are the key factors leading to gel formation during phase separation. These findings support a mechanical perspective on dynamic arrest of sticky-sphere systems based on microstructure, replacing conventional explanations based on macroscopic vitrification of colloidal-rich phase.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Review
Physics, Condensed Matter
C. Patrick Royall, Malcolm A. Faers, Sian L. Fussell, James E. Hallett
Summary: Colloidal gels are important materials with a wide range of applications, exhibiting complex time-dependent behaviors. Research using simple models and experimental systems has revealed insights into the understanding of colloidal gels, including rigidity mechanisms, time-dependent behaviors, and responses to deformation.
JOURNAL OF PHYSICS-CONDENSED MATTER
(2021)
Article
Chemistry, Physical
Taejin Kwon, Tanner A. Wilcoxson, Delia J. Milliron, Thomas M. Truskett
Summary: This study investigates the dynamic behavior of linked networks of patchy colloids using a coarse-grained model and reveals the control of colloid-colloid bond persistence time on the slow relaxation of the self-intermediate scattering function. The model exhibits characteristic equilibrium gel formation and re-entrant network formation without phase separation as a function of linker concentration.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Multidisciplinary
Leandro Goncalves, Pedro Lavrador, Aderito J. R. Amaral, Luis P. Ferreira, Vitor M. Gaspar, Joao F. Mano
Summary: By engineering colloidal gel inks, the challenges of controlling nanoparticles distribution across multiple scales can be overcome through 3D printing. Oppositely charged proteinaceous-polymeric nanoparticles are combined to create multi-component colloidal gel inks for fabricating supraparticle volumetric architectures. The double-interlinked supraparticle assemblies are established via electrostatic interactions and on-demand covalent photocrosslinking.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Multidisciplinary Sciences
Yujie Jiang, Ryohei Seto
Summary: Using simulations, the authors identify the interplay between two lengthscales that generically controls gelation in composite gels. Composite gels, which consist of gel and non-sticky inclusions, are more commonly encountered in reality. Numerical simulations show that the non-sticky particles confine gelation in terms of an effective volume fraction and introduce another competing lengthscale. The ratio of these two lengthscales controls the effects in colloidal composites.
NATURE COMMUNICATIONS
(2023)
Article
Chemistry, Physical
Mohammad Manjiul Islam, Daniel Robert Lester
Summary: This study explores the consolidation mechanics of strong colloidal gels under arbitrary compressive loadings through 2D DEM biaxial simulations. It shows that the maximum normal stress during consolidation is a unique function of the volumetric strain and concentration of the solids phase. A generalized constitutive model for macroscopic compressive rheology under arbitrary compressive loadings is developed, which can predict multidimensional consolidation without needing further characterization beyond uniaxial consolidation.
Article
Multidisciplinary Sciences
Zahra Ghaffari, Hosein Rezvani, Ali Khalilnezhad, Farid B. Cortes, Masoud Riazi
Summary: High water production in oil fields is a concerning issue due to its economic and wellhead damages. This study investigates the use of colloidal gels as an alternative to polymers for water conformance control. The properties and applicability of solid gels were characterized through bottle tests and glass micromodel experiments. The results showed that different solution concentrations and ion replacements can affect the properties of the gels, and solid gels have potential for water conformance control.
SCIENTIFIC REPORTS
(2022)
Article
Mechanics
Louis-Vincent Bouthier, Thomas Gibaud
Summary: Based on recent experimental investigations, two models are proposed to explain the structure and rheological properties of atypical colloidal gels that display three distinct length scales when flow interferes with gelation. Both models consider the condensation of colloids into fractal clusters.
JOURNAL OF RHEOLOGY
(2023)
Review
Energy & Fuels
Dongmei Wang, Randall S. Seright
Summary: This paper reviews literature on the efficacy of floods with colloidal dispersion gels (CDGs) compared to polymer floods for oil recovery. The conclusion suggests that CDGs do not provide better results than polymer floods, and highlights the misleading claims made about CDGs' effectiveness.
Article
Statistics & Probability
Ahmed El Alaoui, Florent Krzakala, Michael Jordan
ANNALS OF STATISTICS
(2020)
Article
Physics, Multidisciplinary
Marylou Gabrie, Jean Barbier, Florent Krzakala, Lenka Zdeborova
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2020)
Article
Physics, Multidisciplinary
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborova
Article
Computer Science, Information Systems
Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, Lenka Zdeborova
Summary: Investigated the statistical and algorithmic properties of random neural-network generative priors in spiked-matrix estimation, establishing the performance of Bayesian optimal estimator and identifying statistical threshold for weak-recovery of spike; derived a message-passing algorithm considering latent structure of spike, showing asymptotically optimal performance for natural generative network choices, highlighting absence of algorithmic gap compared to sparse spikes.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2021)
Article
Multidisciplinary Sciences
Antoine Baker, Indaco Biazzo, Alfredo Braunstein, Giovanni Catania, Luca Dall'Asta, Alessandro Ingrosso, Florent Krzakala, Fabio Mazza, Marc Mezard, Anna Paola Muntoni, Maria Refinetti, Stefano Sarao Mannelli, Lenka Zdeborova
Summary: Research suggests that probabilistic risk estimation can enhance the performance of digital contact tracing, aiding in mitigating the impact of epidemics.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Mechanics
Francesca Mignacco, Florent Krzakala, Pierfrancesco Urbani, And Lenka Zdeborova
Summary: This study analyzes the learning dynamics of stochastic gradient descent in a high-dimensional Gaussian mixture classification problem, revealing how the algorithm's performance varies with changes in control parameters in the loss landscape.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2021)
Article
Mechanics
Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mezard, Lenka Zdeborova
Summary: In this study, we focus on generalised linear regression and classification for a synthetically generated dataset, presenting closed-form expressions for asymptotic generalisation performance using the replica method from statistical physics. We highlight the double descent behavior in logistic regression and the superiority of orthogonal projections in learning with random features, while considering the role of correlations in data generated by the hidden manifold model. This theoretical formalism not only addresses specific problems but also opens a pathway for extending to more complex tasks.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2021)
Article
Mechanics
Antoine Maillard, Florent Krzakala, Marc Mezard, Lenka Zdeborova
Summary: The paper discusses matrix factorization and extensive-rank matrix denoising problems using high-temperature expansions to find more accurate solutions. It provides a systematic approach to derive corrections to existing approximations, taking into account the specific structure of correlations in the problems.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Mechanics
Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborova
Summary: This manuscript investigates kernel ridge regression (KRR) under the Gaussian design and explores the impact of the interplay between noise and regularization on the decay rates of excess generalization error. By studying different settings, we provide a characterization of all observed regimes and demonstrate the existence of a transition phenomenon in the noisy setting.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Mechanics
Bruno Loureiro, Cedric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mezard, Lenka Zdeborova
Summary: Teacher-student models provide a framework for describing the performance of high-dimensional supervised learning. This paper introduces a Gaussian covariate generalisation of the model that captures learning curves for a broad range of realistic data sets. The study also discusses the power and limitations of the framework.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Biochemical Research Methods
Sebastian Goldt, Florent Krzakala, Lenka Zdeborova, Nicolas Brunel
Summary: The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics. This study addresses the question of whether it is possible to reconstruct the information stored in a recurrent network of neurons given its synaptic connectivity matrix. It provides a practical algorithm based on statistical physics for approximate Bayesian inference to solve this inference problem.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Computer Science, Information Systems
Cedric Gerbelot, Alia Abbara, Florent Krzakala
Summary: There has been a recent surge of interest in studying the asymptotic reconstruction performance of generalized linear estimation problems, especially for the case of i.i.d standard normal matrices in the teacher-student setting. In this study, an analytical formula for the reconstruction performance of convex generalized linear models with rotationally-invariant data matrices is proven, confirming a conjecture derived using the replica method. The proof leverages on message passing algorithms and statistical properties of their iterates, characterizing the asymptotic empirical distribution of the estimator.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2023)
Article
Computer Science, Artificial Intelligence
Lucas Clarte, Bruno Loureiro, Florent Krzakala, Lenka Zdeborova
Summary: Being able to assess the accuracy and uncertainty of models' predictions is important in machine learning. Computational challenges arise in high-dimensional problems when sampling the posterior probability measure. This manuscript characterizes uncertainty for learning from limited samples and provides a formula for investigating the calibration of the logistic classifier.
MACHINE LEARNING-SCIENCE AND TECHNOLOGY
(2023)
Proceedings Paper
Acoustics
Alessandro Cappelli, Ruben Ohana, Julien Launay, Laurent Meunier, Iacopo Poli, Florent Krzakala
Summary: We propose a new defense mechanism inspired by an optical co-processor that provides robustness against adversarial attacks without compromising natural accuracy in both whitebox and black-box settings. This hardware co-processor performs a nonlinear fixed random transformation with unknown parameters that cannot be retrieved with sufficient precision. In the whitebox setting, our defense works by obfuscating the parameters of the random projection, but we find it challenging to build a reliable backward differentiable approximation for obfuscated parameters.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborova
Summary: Theoretical works indicate that two-layer neural networks with few neurons can outperform kernel learning on simple classification tasks, especially in high-dimensional limits. Small neural networks can achieve near-optimal performance, while lazy training methods like random features and kernel methods do not. Over-parameterizing neural networks can lead to faster convergence but does not necessarily improve final performance.
INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139
(2021)
