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  1. Article ; Online: The multivariate interaction between Au and TiO

    Lau, Kinran / Giera, Brian / Barcikowski, Stephan / Reichenberger, Sven

    Nanoscale

    2024  Volume 16, Issue 5, Page(s) 2552–2564

    Abstract: The established DLVO theory explains colloidal stability by the electrostatic repulsion between electrical double layers. While the routinely measured zeta potential can estimate the charges of double layers, it is only an average surface property which ... ...

    Abstract The established DLVO theory explains colloidal stability by the electrostatic repulsion between electrical double layers. While the routinely measured zeta potential can estimate the charges of double layers, it is only an average surface property which might deviate from the local environment. Moreover, other factors such as the ionic strength and the presence of defects should also be considered. To investigate this multivariate problem, here we model the interaction between a negatively charged Au particle and a negatively charged TiO
    Language English
    Publishing date 2024-02-01
    Publishing country England
    Document type Journal Article
    ZDB-ID 2515664-0
    ISSN 2040-3372 ; 2040-3364
    ISSN (online) 2040-3372
    ISSN 2040-3364
    DOI 10.1039/d3nr06205h
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  2. Article ; Online: Two Photon lithography additive manufacturing: Video dataset of parameter sweep of light dosages, photo-curable resins, and structures.

    Lee, Xian Yeow / Saha, Sourabh K / Sarkar, Soumik / Giera, Brian

    Data in brief

    2020  Volume 32, Page(s) 106119

    Abstract: This document describes the collection and organization of a dataset that consists of raw videos and extracted sub-images from video frames of a promising additive manufacturing technique called Two-Photon Lithography (TPL).  Four unprocessed videos were ...

    Abstract This document describes the collection and organization of a dataset that consists of raw videos and extracted sub-images from video frames of a promising additive manufacturing technique called Two-Photon Lithography (TPL).  Four unprocessed videos were collected, with each video capturing the printing process of different combinations of 3D parts on different photoresists at varying light dosages.  These videos were further trimmed to obtain short clips that are organized by experimental parameters. Additionally, this dataset also contains a python script to reproduce an organized directory of cropped video frames extracted from the trimmed videos. These cropped frames focus on a region of interest around the parts being printed. We envision that the raw videos and cropped frames provided in this dataset will be used to train various computer vision and machine learning algorithms for applications such as object segmentation and localization applications. The cropped video frames were manually labelled by an expert to determine the quality of the printed part and for printing parameter optimization as presented in "Automated Detection of Part Quality during Two-Photon Lithography via Deep Learning" [1].
    Language English
    Publishing date 2020-08-03
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2786545-9
    ISSN 2352-3409 ; 2352-3409
    ISSN (online) 2352-3409
    ISSN 2352-3409
    DOI 10.1016/j.dib.2020.106119
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Two Photon lithography additive manufacturing: Video dataset of parameter sweep of light dosages, photo-curable resins, and structures

    Lee, Xian Yeow / Saha, Sourabh K. / Sarkar, Soumik / Giera, Brian

    Data in Brief. 2020 Oct., v. 32

    2020  

    Abstract: This document describes the collection and organization of a dataset that consists of raw videos and extracted sub-images from video frames of a promising additive manufacturing technique called Two-Photon Lithography (TPL). Four unprocessed videos were ... ...

    Abstract This document describes the collection and organization of a dataset that consists of raw videos and extracted sub-images from video frames of a promising additive manufacturing technique called Two-Photon Lithography (TPL). Four unprocessed videos were collected, with each video capturing the printing process of different combinations of 3D parts on different photoresists at varying light dosages. These videos were further trimmed to obtain short clips that are organized by experimental parameters. Additionally, this dataset also contains a python script to reproduce an organized directory of cropped video frames extracted from the trimmed videos. These cropped frames focus on a region of interest around the parts being printed. We envision that the raw videos and cropped frames provided in this dataset will be used to train various computer vision and machine learning algorithms for applications such as object segmentation and localization applications. The cropped video frames were manually labelled by an expert to determine the quality of the printed part and for printing parameter optimization as presented in “Automated Detection of Part Quality during Two-Photon Lithography via Deep Learning” [1].
    Keywords automation ; computer software ; computer vision ; data collection ; photons
    Language English
    Dates of publication 2020-10
    Publishing place Elsevier Inc.
    Document type Article
    ZDB-ID 2786545-9
    ISSN 2352-3409
    ISSN 2352-3409
    DOI 10.1016/j.dib.2020.106119
    Database NAL-Catalogue (AGRICOLA)

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  4. Book ; Online: Particle-Based Simulations of Electrophoretic Deposition with Adaptive Physics Models

    Karnes, John J. / Pascall, Andrew J. / Rehbock, Christoph / Ramesh, Vaijayanthi / Worsley, Marcus A. / Barcikowski, Stephan / Lee, Elaine / Giera, Brian

    2023  

    Abstract: This work represents an extension of mesoscale particle-based modeling of electrophoretic deposition (EPD), which has relied exclusively on pairwise interparticle interactions described by Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. With this ... ...

    Abstract This work represents an extension of mesoscale particle-based modeling of electrophoretic deposition (EPD), which has relied exclusively on pairwise interparticle interactions described by Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. With this standard treatment, particles continuously move and interact via excluded volume and electrostatic pair potentials under the influence of external fields throughout the EPD process. The physics imposed by DLVO theory may not be appropriate to describe all systems, considering the vast material, operational, and application space available to EPD. As such, we present three modifications to standard particle-based models, each rooted in the ability to dynamically change interparticle interactions as simulated deposition progresses. This approach allows simulations to capture charge transfer and/or irreversible adsorption based on tunable parameters. We evaluate and compare simulated deposits formed under new physical assumptions, demonstrating the range of systems that these adaptive physics models may capture.

    Comment: 34 pages, 10 figures
    Keywords Condensed Matter - Mesoscale and Nanoscale Physics ; Condensed Matter - Materials Science ; Physics - Computational Physics
    Subject code 190
    Publishing date 2023-06-26
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Comparing Direct and Pulsed-Direct Current Electrophoretic Deposition on Neural Electrodes: Deposition Mechanism and Functional Influence.

    Ramesh, Vaijayanthi / Rehbock, Christoph / Giera, Brian / Karnes, John J / Forien, Jean-Baptiste / Angelov, Svilen D / Schwabe, Kerstin / Krauss, Joachim K / Barcikowski, Stephan

    Langmuir : the ACS journal of surfaces and colloids

    2021  

    Abstract: Electrophoretic deposition (EPD) of platinum nanoparticles (PtNPs) on platinum-iridium (Pt-Ir) neural electrode surfaces is a promising strategy to tune the impedance of electrodes implanted for deep brain stimulation in various neurological disorders ... ...

    Abstract Electrophoretic deposition (EPD) of platinum nanoparticles (PtNPs) on platinum-iridium (Pt-Ir) neural electrode surfaces is a promising strategy to tune the impedance of electrodes implanted for deep brain stimulation in various neurological disorders such as advanced Parkinson's disease and dystonia. However, previous results are contradicting as impedance reduction was observed on flat samples while in three-dimensional (3D) structures, an increase in impedance was observed. Hence, defined correlations between coating properties and impedance are to date not fully understood. In this work, the influence of direct current (DC) and pulsed-DC electric fields on NP deposition is systematically compared and clear correlations between surface coating homogeneity and
    Language English
    Publishing date 2021-08-06
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2005937-1
    ISSN 1520-5827 ; 0743-7463
    ISSN (online) 1520-5827
    ISSN 0743-7463
    DOI 10.1021/acs.langmuir.1c01081
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  6. Article: Comparing Direct and Pulsed-Direct Current Electrophoretic Deposition on Neural Electrodes: Deposition Mechanism and Functional Influence

    Ramesh, Vaijayanthi / Rehbock, Christoph / Giera, Brian / Karnes, John J. / Forien, Jean-Baptiste / Angelov, Svilen D. / Schwabe, Kerstin / Krauss, Joachim K. / Barcikowski, Stephan

    Langmuir. 2021 Aug. 06, v. 37, no. 32

    2021  

    Abstract: Electrophoretic deposition (EPD) of platinum nanoparticles (PtNPs) on platinum–iridium (Pt–Ir) neural electrode surfaces is a promising strategy to tune the impedance of electrodes implanted for deep brain stimulation in various neurological disorders ... ...

    Abstract Electrophoretic deposition (EPD) of platinum nanoparticles (PtNPs) on platinum–iridium (Pt–Ir) neural electrode surfaces is a promising strategy to tune the impedance of electrodes implanted for deep brain stimulation in various neurological disorders such as advanced Parkinson’s disease and dystonia. However, previous results are contradicting as impedance reduction was observed on flat samples while in three-dimensional (3D) structures, an increase in impedance was observed. Hence, defined correlations between coating properties and impedance are to date not fully understood. In this work, the influence of direct current (DC) and pulsed-DC electric fields on NP deposition is systematically compared and clear correlations between surface coating homogeneity and in vitro impedance are established. The ligand-free NPs were synthesized via pulsed laser processing in liquid, yielding monomodal particle size distributions, verified by analytical disk centrifugation (ADC). Deposits formed were quantified by UV–vis supernatant analysis and further characterized by scanning electron microscopy (SEM) with semiautomated interparticle distance analyses. Our findings reveal that pulsed-DC electric fields yield more ordered surface coatings with a lower abundance of particle assemblates, while DC fields produce coatings with more pronounced aggregation. Impedance measurements further highlight that impedance of the corresponding electrodes is significantly reduced in the case of more ordered coatings realized by pulsed-DC depositions. We attribute this phenomenon to the higher active surface area of the adsorbed NPs in homogeneous coatings and the reduced particle−electrode electrical contact in NP assemblates. These results provide insight for the efficient EPD of bare metal NPs on micron-sized surfaces for biomedical applications in neuroscience and correlate coating homogeneity with in vitro functionality.
    Keywords brain ; centrifugation ; electrodes ; electrophoresis ; liquids ; neurophysiology ; particle size ; platinum ; surface area
    Language English
    Dates of publication 2021-0806
    Size p. 9724-9734.
    Publishing place American Chemical Society
    Document type Article
    ZDB-ID 2005937-1
    ISSN 1520-5827 ; 0743-7463
    ISSN (online) 1520-5827
    ISSN 0743-7463
    DOI 10.1021/acs.langmuir.1c01081
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  7. Article ; Online: Experimental characterization and modeling of optical tweezer particle handling dynamics.

    Porter, Michael D / Giera, Brian / Panas, Robert M / Shaw, Lucas A / Shusteff, Maxim / Hopkins, Jonathan B

    Applied optics

    2018  Volume 57, Issue 22, Page(s) 6565–6571

    Abstract: We report a new framework for a quantitative understanding of optical trapping (OT) particle handling dynamics. We present a novel three-dimensional particle-based model that includes optical, hydrodynamic, and inter-particle forces. This semi-empirical ... ...

    Abstract We report a new framework for a quantitative understanding of optical trapping (OT) particle handling dynamics. We present a novel three-dimensional particle-based model that includes optical, hydrodynamic, and inter-particle forces. This semi-empirical colloid model is based on an open-source simulation code known as LAMMPS (large-scale atomic/molecular massively parallel simulator) and properly recapitulates the full OT force profile beyond the typical linear approximations valid near the trap center. Simulations are carried out with typical system parameters relevant for our experimental holographic optical trapping (HOT) system, including varied particle sizes, trap movement speeds, and beam powers. Furthermore, we present a new experimental method for measuring both the stable and metastable boundaries of the optical force profile to inform or validate the model's underlying force profile. We show that our framework is a powerful tool for accurately predicting particle behavior in a practical experimental OT setup and can be used to characterize and predict particle handling dynamics within any arbitrary OT force profile.
    Language English
    Publishing date 2018-08-17
    Publishing country United States
    Document type Journal Article
    ISSN 1539-4522
    ISSN (online) 1539-4522
    DOI 10.1364/AO.57.006565
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  8. Article: Mesoscale Particle-Based Model of Electrophoretic Deposition

    Giera, Brian / Pascall Andrew J / Weisgraber Todd H / Zepeda-Ruiz Luis A

    Langmuir. 2017 Jan. 17, v. 33, no. 2

    2017  

    Abstract: We present and evaluate a semiempirical particle-based model of electrophoretic deposition using extensive mesoscale simulations. We analyze particle configurations in order to observe how colloids accumulate at the electrode and arrange into deposits. ... ...

    Abstract We present and evaluate a semiempirical particle-based model of electrophoretic deposition using extensive mesoscale simulations. We analyze particle configurations in order to observe how colloids accumulate at the electrode and arrange into deposits. In agreement with existing continuum models, the thickness of the deposit increases linearly in time during deposition. Resulting colloidal deposits exhibit a transition between highly ordered and bulk disordered regions that can give rise to an appreciable density gradient under certain simulated conditions. The overall volume fraction increases and falls within a narrow range as the driving force due to the electric field increases and repulsive intercolloidal interactions decrease. We postulate ordering and stacking within the initial layer(s) dramatically impacts the microstructure of the deposits. We find a combination of parameters, i.e., electric field and suspension properties, whose interplay enhances colloidal ordering beyond the commonly known approach of only reducing the driving force.
    Keywords colloids ; electric field ; electrodes ; electrophoresis ; microstructure ; models
    Language English
    Dates of publication 2017-0117
    Size p. 652-661.
    Publishing place American Chemical Society
    Document type Article
    ZDB-ID 2005937-1
    ISSN 1520-5827 ; 0743-7463
    ISSN (online) 1520-5827
    ISSN 0743-7463
    DOI 10.1021%2Facs.langmuir.6b04010
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  9. Article ; Online: Mesoscale Particle-Based Model of Electrophoretic Deposition.

    Giera, Brian / Zepeda-Ruiz, Luis A / Pascall, Andrew J / Weisgraber, Todd H

    Langmuir : the ACS journal of surfaces and colloids

    2017  Volume 33, Issue 2, Page(s) 652–661

    Abstract: We present and evaluate a semiempirical particle-based model of electrophoretic deposition using extensive mesoscale simulations. We analyze particle configurations in order to observe how colloids accumulate at the electrode and arrange into deposits. ... ...

    Abstract We present and evaluate a semiempirical particle-based model of electrophoretic deposition using extensive mesoscale simulations. We analyze particle configurations in order to observe how colloids accumulate at the electrode and arrange into deposits. In agreement with existing continuum models, the thickness of the deposit increases linearly in time during deposition. Resulting colloidal deposits exhibit a transition between highly ordered and bulk disordered regions that can give rise to an appreciable density gradient under certain simulated conditions. The overall volume fraction increases and falls within a narrow range as the driving force due to the electric field increases and repulsive intercolloidal interactions decrease. We postulate ordering and stacking within the initial layer(s) dramatically impacts the microstructure of the deposits. We find a combination of parameters, i.e., electric field and suspension properties, whose interplay enhances colloidal ordering beyond the commonly known approach of only reducing the driving force.
    Language English
    Publishing date 2017-01-17
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2005937-1
    ISSN 1520-5827 ; 0743-7463
    ISSN (online) 1520-5827
    ISSN 0743-7463
    DOI 10.1021/acs.langmuir.6b04010
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  10. Article: Electric Double-Layer Structure in Primitive Model Electrolytes: Comparing Molecular Dynamics with Local-Density Approximations

    Giera, Brian / Henson Neil / Kober Edward M / Shell M. Scott / Squires Todd M

    Langmuir. 2015 Mar. 24, v. 31, no. 11

    2015  

    Abstract: We evaluate the accuracy of local-density approximations (LDAs) using explicit molecular dynamics simulations of binary electrolytes comprised of equisized ions in an implicit solvent. The Bikerman LDA, which considers ions to occupy a lattice, poorly ... ...

    Abstract We evaluate the accuracy of local-density approximations (LDAs) using explicit molecular dynamics simulations of binary electrolytes comprised of equisized ions in an implicit solvent. The Bikerman LDA, which considers ions to occupy a lattice, poorly captures excluded volume interactions between primitive model ions. Instead, LDAs based on the Carnahan–Starling (CS) hard-sphere equation of state capture simulated values of ideal and excess chemical potential profiles extremely well, as well as the relationship between surface charge density and electrostatic potential. Excellent agreement between the EDL capacitances predicted by CS-LDAs and computed in molecular simulations is found even in systems where ion correlations drive strong density and free charge oscillations within the EDL, despite the inability of LDAs to capture the oscillations in the detailed EDL profiles.
    Keywords equations ; ions ; models ; molecular dynamics ; solvents
    Language English
    Dates of publication 2015-0324
    Size p. 3553-3562.
    Publishing place American Chemical Society
    Document type Article
    ZDB-ID 2005937-1
    ISSN 1520-5827 ; 0743-7463
    ISSN (online) 1520-5827
    ISSN 0743-7463
    DOI 10.1021%2Fla5048936
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