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Castellini S, Brizioli M, Giraudet C, Carpineti M, Croccolo F, Giavazzi F, Vailati A. Modeling and correction of image drift in dynamic shadowgraphy experiments. THE EUROPEAN PHYSICAL JOURNAL. E, SOFT MATTER 2024; 47:25. [PMID: 38587607 PMCID: PMC11249426 DOI: 10.1140/epje/s10189-024-00413-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 03/03/2024] [Indexed: 04/09/2024]
Abstract
The study of phoretic transport phenomena under non-stationary conditions presents several challenges, mostly related to the stability of the experimental apparatus. This is particularly true when investigating with optical means the subtle temperature and concentration fluctuations that arise during diffusion processes, superimposed to the macroscopic state of the system. Under these conditions, the tenuous signal from fluctuations is easily altered by the presence of artifacts. Here, we address an experimental issue frequently reported in the investigation by means of dynamic shadowgraphy of the non-equilibrium fluctuations arising in liquid mixtures under non-stationary conditions, such as those arising after the imposition or removal of a thermal stress, where experiments show systematically the presence of a spurious contribution in the reconstructed structure function of the fluctuations, which depends quadratically from the time delay. We clarify the mechanisms responsible for this artifact, showing that it is caused by the imperfect alignment of the sample cell with respect to gravity, which couples the temporal evolution of the concentration profile within the sample with the optical signal collected by the shadowgraph diagnostics. We propose a data analysis protocol that enables disentangling the spurious contributions and the genuine dynamics of the fluctuations, which can be thus reliably reconstructed.
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Affiliation(s)
- Stefano Castellini
- Dipartimento di Fisica"A. Pontremoli", Università degli Studi di Milano, Milan, Italy
| | - Matteo Brizioli
- Dipartimento di Biotecnologie Mediche e Medicina Traslazionale, Università degli Studi di Milano, Segrate, Italy
| | - Cédric Giraudet
- LFCR UMR5150, E2S UPPA, CNRS, Universite de Pau et des Pays de l'Adour, Anglet, France
| | - Marina Carpineti
- Dipartimento di Fisica"A. Pontremoli", Università degli Studi di Milano, Milan, Italy
| | - Fabrizio Croccolo
- LFCR UMR5150, E2S UPPA, CNRS, Universite de Pau et des Pays de l'Adour, Anglet, France
| | - Fabio Giavazzi
- Dipartimento di Biotecnologie Mediche e Medicina Traslazionale, Università degli Studi di Milano, Segrate, Italy.
| | - Alberto Vailati
- Dipartimento di Fisica"A. Pontremoli", Università degli Studi di Milano, Milan, Italy
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Meleties M, Martineau RL, Gupta MK, Montclare JK. Particle-Based Microrheology As a Tool for Characterizing Protein-Based Materials. ACS Biomater Sci Eng 2022; 8:2747-2763. [PMID: 35678203 DOI: 10.1021/acsbiomaterials.2c00035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Microrheology based on video microscopy of embedded tracer particles has the potential to be used for high-throughput protein-based materials characterization. This potential is due to a number of characteristics of the techniques, including the suitability for measurement of low sample volumes, noninvasive and noncontact measurements, and the ability to set up a large number of samples for facile, sequential measurement. In addition to characterization of the bulk rheological properties of proteins in solution, for example, viscosity, microrheology can provide insight into the dynamics and self-assembly of protein-based materials as well as heterogeneities in the microenvironment being probed. Specifically, passive microrheology in the form of multiple particle tracking and differential dynamic microscopy holds promise for applications in high-throughput characterization because of the lack of user interaction required while making measurements. Herein, recent developments in the use of multiple particle tracking and differential dynamic microscopy are reviewed for protein characterization and their potential to be applied in a high-throughput, automatable setting.
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Affiliation(s)
- Michael Meleties
- Department of Chemical and Biomolecular Engineering, Tandon School of Engineering, New York University, New York, New York 11201, United States
| | - Rhett L Martineau
- Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson AFB, Ohio 45433, United States.,Biological and Nanoscale Technologies Division, UES Inc., Dayton, Ohio 45432, United States
| | - Maneesh K Gupta
- Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson AFB, Ohio 45433, United States
| | - Jin Kim Montclare
- Department of Chemical and Biomolecular Engineering, Tandon School of Engineering, New York University, New York, New York 11201, United States.,Department of Radiology, New York University Langone Health, New York, New York 10016, United States.,Department of Biomaterials, College of Dentistry, New York University, New York, New York 10010, United States.,Department of Chemistry, New York University, New York, New York 10003, United States
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Meleties M, Britton D, Katyal P, Lin B, Martineau RL, Gupta MK, Montclare JK. High-Throughput Microrheology for the Assessment of Protein Gelation Kinetics. Macromolecules 2022. [DOI: 10.1021/acs.macromol.1c02281] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Michael Meleties
- Department of Chemical and Biomolecular Engineering, New York University Tandon School of Engineering, Brooklyn, New York 11201, United States
| | - Dustin Britton
- Department of Chemical and Biomolecular Engineering, New York University Tandon School of Engineering, Brooklyn, New York 11201, United States
| | - Priya Katyal
- Department of Chemical and Biomolecular Engineering, New York University Tandon School of Engineering, Brooklyn, New York 11201, United States
| | - Bonnie Lin
- Department of Chemical and Biomolecular Engineering, New York University Tandon School of Engineering, Brooklyn, New York 11201, United States
| | - Rhett L. Martineau
- Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio 45433, United States
| | - Maneesh K. Gupta
- Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio 45433, United States
| | - Jin Kim Montclare
- Department of Chemical and Biomolecular Engineering, New York University Tandon School of Engineering, Brooklyn, New York 11201, United States
- Department of Radiology, New York University Langone Health, New York, New York 10016, United States
- Department of Biomaterials, New York University College of Dentistry, New York, New York 10010, United States
- Department of Chemistry, New York University, New York, New York 10003, United States
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Martineau RL, Bayles AV, Hung CS, Reyes KG, Helgeson ME, Gupta MK. Engineering Gelation Kinetics in Living Silk Hydrogels by Differential Dynamic Microscopy Microrheology and Machine Learning. Adv Biol (Weinh) 2021; 6:e2101070. [PMID: 34811969 DOI: 10.1002/adbi.202101070] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 09/20/2021] [Indexed: 12/20/2022]
Abstract
Microbes embedded in hydrogels comprise one form of living material. Discovering formulations that balance potentially competing for mechanical and biological properties in living hydrogels-for example, gel time of the hydrogel formulation and viability of the embedded organisms-can be challenging. In this study, a pipeline is developed to automate the characterization of the gel time of hydrogel formulations. Using this pipeline, living materials comprised of enzymatically crosslinked silk and embedded E. coli-formulated from within a 4D parameter space-are engineered to gel within a pre-selected timeframe. Gelation time is estimated using a novel adaptation of microrheology analysis using differential dynamic microscopy (DDM). In order to expedite the discovery of gelation regime boundaries, Bayesian machine learning models are deployed with optimal decision-making under uncertainty. The rate of learning is observed to vary between artificial intelligence (AI)-assisted planning and human planning, with the fastest rate occurring during AI-assisted planning following a round of human planning. For a subset of formulations gelling within a targeted timeframe of 5-15 min, fluorophore production within the embedded cells is substantially similar across treatments, evidencing that gel time can be tuned independent of other material properties-at least over a finite range-while maintaining biological activity.
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Affiliation(s)
- Rhett L Martineau
- Materials and Manufacturing Directorate, Air Force Research Laboratory, 2179 12th St. B652/R122, WPAFB, OH, 45433-7717, USA
| | - Alexandra V Bayles
- Department of Chemical Engineering, University of California Santa Barbara, 3357 Engineering II, Santa Barbara, CA, 93106, USA
| | - Chia-Suei Hung
- Materials and Manufacturing Directorate, Air Force Research Laboratory, 2179 12th St. B652/R122, WPAFB, OH, 45433-7717, USA
| | - Kristofer G Reyes
- Department of Materials Design and Innovation, University at Buffalo, Buffalo, NY, 14260, USA
| | - Matthew E Helgeson
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA, 93106-5080, USA
| | - Maneesh K Gupta
- Materials and Manufacturing Directorate, Air Force Research Laboratory, 2179 12th St. B652/R122, WPAFB, OH, 45433-7717, USA
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Richards JA, Martinez VA, Arlt J. Characterising shear-induced dynamics in flowing complex fluids using differential dynamic microscopy. SOFT MATTER 2021; 17:8838-8849. [PMID: 34557882 PMCID: PMC8513683 DOI: 10.1039/d1sm01094h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 09/17/2021] [Indexed: 05/14/2023]
Abstract
Microscopic dynamics reveal the origin of the bulk rheological response in complex fluids. In model systems particle motion can be tracked, but for industrially relevant samples this is often impossible. Here we adapt differential dynamic microscopy (DDM) to study flowing highly-concentrated samples without particle resolution. By combining an investigation of oscillatory flow, using a novel "echo-DDM" analysis, and steady shear, through flow-DDM, we characterise the yielding of a silicone oil emulsion on both the microscopic and bulk level. Through measuring the rate of shear-induced droplet rearrangements and the flow velocity, the transition from a solid-like to liquid-like state is shown to occur in two steps: with droplet mobilisation marking the limit of linear visco-elasticity, followed by the development of shear localisation and macroscopic yielding. Using this suite of techniques, such insight could be developed for a wide variety of challenging complex fluids.
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Affiliation(s)
- James A Richards
- Edinburgh Complex Fluids Partnership and School of Physics and Astronomy, James Clerk Maxwell Building, Peter Guthrie Tait Road, King's Buildings, Edinburgh, EH9 3FD, UK.
| | - Vincent A Martinez
- Edinburgh Complex Fluids Partnership and School of Physics and Astronomy, James Clerk Maxwell Building, Peter Guthrie Tait Road, King's Buildings, Edinburgh, EH9 3FD, UK.
| | - Jochen Arlt
- Edinburgh Complex Fluids Partnership and School of Physics and Astronomy, James Clerk Maxwell Building, Peter Guthrie Tait Road, King's Buildings, Edinburgh, EH9 3FD, UK.
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