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Beth A Lindquist - One of the best experts on this subject based on the ideXlab platform.

  • the role of pressure in inverse Design for Assembly
    Journal of Chemical Physics, 2019
    Co-Authors: Beth A Lindquist, Ryan B Jadrich, Michael P Howard, Thomas M Truskett
    Abstract:

    Isotropic pairwise interactions that promote the self-Assembly of complex particle morphologies have been discovered by inverse Design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-Assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. The benefits of this approach are twofold. First, the structure and the thermodynamics associated with the optimized interaction can be controlled simultaneously. Second, by varying the pressure in the optimization, a family of interparticle potentials that all self-assemble the same structure can be systematically discovered, allowing for a deeper understanding of self-Assembly of a given target structure and providing multiple Assembly routes for its realization. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general Design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential.Isotropic pairwise interactions that promote the self-Assembly of complex particle morphologies have been discovered by inverse Design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-Assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. The benefits of this approach are twofold. First, the structure and the thermodynamics associated with the optimized interaction can be controlled simultaneously. Second, by varying the pressure in the optimization, a family of interparticle potentials that all self-assemble the same structure can be systematically discovered, allowing for a deeper understanding of...

  • the role of pressure in inverse Design for Assembly
    arXiv: Statistical Mechanics, 2019
    Co-Authors: Beth A Lindquist, Ryan B Jadrich, Michael P Howard, Thomas M Truskett
    Abstract:

    Isotropic pairwise interactions that promote the self Assembly of complex particle morphologies have been discovered by inverse Design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-Assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. By tuning the pressure in the optimization, we generate a family of simple pair potentials that all self-assemble the same structure. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general Design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential.

Thomas M Truskett - One of the best experts on this subject based on the ideXlab platform.

  • the role of pressure in inverse Design for Assembly
    Journal of Chemical Physics, 2019
    Co-Authors: Beth A Lindquist, Ryan B Jadrich, Michael P Howard, Thomas M Truskett
    Abstract:

    Isotropic pairwise interactions that promote the self-Assembly of complex particle morphologies have been discovered by inverse Design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-Assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. The benefits of this approach are twofold. First, the structure and the thermodynamics associated with the optimized interaction can be controlled simultaneously. Second, by varying the pressure in the optimization, a family of interparticle potentials that all self-assemble the same structure can be systematically discovered, allowing for a deeper understanding of self-Assembly of a given target structure and providing multiple Assembly routes for its realization. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general Design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential.Isotropic pairwise interactions that promote the self-Assembly of complex particle morphologies have been discovered by inverse Design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-Assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. The benefits of this approach are twofold. First, the structure and the thermodynamics associated with the optimized interaction can be controlled simultaneously. Second, by varying the pressure in the optimization, a family of interparticle potentials that all self-assemble the same structure can be systematically discovered, allowing for a deeper understanding of...

  • the role of pressure in inverse Design for Assembly
    arXiv: Statistical Mechanics, 2019
    Co-Authors: Beth A Lindquist, Ryan B Jadrich, Michael P Howard, Thomas M Truskett
    Abstract:

    Isotropic pairwise interactions that promote the self Assembly of complex particle morphologies have been discovered by inverse Design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-Assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. By tuning the pressure in the optimization, we generate a family of simple pair potentials that all self-assemble the same structure. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general Design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential.

Ryan B Jadrich - One of the best experts on this subject based on the ideXlab platform.

  • the role of pressure in inverse Design for Assembly
    Journal of Chemical Physics, 2019
    Co-Authors: Beth A Lindquist, Ryan B Jadrich, Michael P Howard, Thomas M Truskett
    Abstract:

    Isotropic pairwise interactions that promote the self-Assembly of complex particle morphologies have been discovered by inverse Design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-Assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. The benefits of this approach are twofold. First, the structure and the thermodynamics associated with the optimized interaction can be controlled simultaneously. Second, by varying the pressure in the optimization, a family of interparticle potentials that all self-assemble the same structure can be systematically discovered, allowing for a deeper understanding of self-Assembly of a given target structure and providing multiple Assembly routes for its realization. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general Design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential.Isotropic pairwise interactions that promote the self-Assembly of complex particle morphologies have been discovered by inverse Design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-Assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. The benefits of this approach are twofold. First, the structure and the thermodynamics associated with the optimized interaction can be controlled simultaneously. Second, by varying the pressure in the optimization, a family of interparticle potentials that all self-assemble the same structure can be systematically discovered, allowing for a deeper understanding of...

  • the role of pressure in inverse Design for Assembly
    arXiv: Statistical Mechanics, 2019
    Co-Authors: Beth A Lindquist, Ryan B Jadrich, Michael P Howard, Thomas M Truskett
    Abstract:

    Isotropic pairwise interactions that promote the self Assembly of complex particle morphologies have been discovered by inverse Design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-Assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. By tuning the pressure in the optimization, we generate a family of simple pair potentials that all self-assemble the same structure. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general Design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential.

Daniel E. Whitney - One of the best experts on this subject based on the ideXlab platform.

  • prototyping and Design for Assembly analysis using multimodal virtual environments
    Computer-aided Design, 1997
    Co-Authors: Rakesh Gupta, Daniel E. Whitney, David Zeltzer
    Abstract:

    Abstract The goal of this work is to investigate whether estimates of ease of part handling and part insertion can be provided by multimodal simulation using virtual environment (VE) technology, rather than by using conventional table-based methods such as Boothroyd and Dewhurst Charts. The long term goal is to extend cad systems to evaluate and compare alternative Designs using Design for Assembly Analysis. A unified physically based model has been developed for modeling dynamic interactions among virtual objects and haptic interactions between the human Designer and the virtual objects. This model is augmented with auditory events in a multimodal VE system called the Virtual Environment for Design for Assembly (VEDA). The Designer sees a visual representation of the objects, hears collision sounds when objects hit each other and can feel and manipulate the objects through haptic interface devices with force feedback. Currently these models are 2D in order to preserve interactive update rates. Experiments were conducted with human subjects using two-dimensional peg-in-hole apparatus and a VEDA simulation of the same apparatus. The simulation duplicated as well as possible the weight, shape, size, peg-hole clearance, and frictional characteristics of the physical apparatus. The experiments showed that the Multimodal VE is able to replicate experimental results in which increased task completion times correlated with increasing task difficulty (measured as increased friction, increased handling distance combined with decreased peg-hole clearance). However, the Multimodal VE task completion times are approximately two times the physical apparatus completion times. A number of possible factors for this temporal discrepancy have been identified but their effect has not been quantified.

  • Experiments using multimodal virtual environments in Design for Assembly analysis
    Presence: Teleoperators & Virtual Environments, 1997
    Co-Authors: Rakesh Gupta, Thomas B. Sheridan, Daniel E. Whitney
    Abstract:

    The goal of this work is to investigate whether estimates of ease of part handling and part insertion can be provided by multimodal simulation using virtual environment VE technology. The long-term goal is to use this data to extend computer-aided Design CAD systems in order to evaluate and compare alternate Designs using Design for Assembly analysis. A unified, physically-based model has been developed for modeling dynamic interactions and has been built into a multimodal VE system called the Virtual Environment for Design for Assembly VEDA. The Designer sees a visual representation of objects, hears collision sounds when objects hit each other, and can feel and manipulate the objects through haptic interface devices with force feedback. Currently these models are 2D in order to preserve interactive update rates. Experiments were conducted with human subjects using a two-dimensional peg-in-hole apparatus and a VEDA simulation of the same apparatus. The simulation duplicated as well as possible the weight, shape, size, peg-hole clearance, and fictional characteristics of the physical apparatus. The experiments showed that the multimodal VE is able to replicate experimental results in which increased task completion times correlated with increasing task difficulty measured as increased friction, increased handling distance, and decreased peg-hole clearance. However, the multimodal VE task completion times are approximately twice those of the physical apparatus completion process. A number of possible factors have been identified, but the effect of these factors has not been quantified.

Rakesh Gupta - One of the best experts on this subject based on the ideXlab platform.

  • prototyping and Design for Assembly analysis using multimodal virtual environments
    Computer-aided Design, 1997
    Co-Authors: Rakesh Gupta, Daniel E. Whitney, David Zeltzer
    Abstract:

    Abstract The goal of this work is to investigate whether estimates of ease of part handling and part insertion can be provided by multimodal simulation using virtual environment (VE) technology, rather than by using conventional table-based methods such as Boothroyd and Dewhurst Charts. The long term goal is to extend cad systems to evaluate and compare alternative Designs using Design for Assembly Analysis. A unified physically based model has been developed for modeling dynamic interactions among virtual objects and haptic interactions between the human Designer and the virtual objects. This model is augmented with auditory events in a multimodal VE system called the Virtual Environment for Design for Assembly (VEDA). The Designer sees a visual representation of the objects, hears collision sounds when objects hit each other and can feel and manipulate the objects through haptic interface devices with force feedback. Currently these models are 2D in order to preserve interactive update rates. Experiments were conducted with human subjects using two-dimensional peg-in-hole apparatus and a VEDA simulation of the same apparatus. The simulation duplicated as well as possible the weight, shape, size, peg-hole clearance, and frictional characteristics of the physical apparatus. The experiments showed that the Multimodal VE is able to replicate experimental results in which increased task completion times correlated with increasing task difficulty (measured as increased friction, increased handling distance combined with decreased peg-hole clearance). However, the Multimodal VE task completion times are approximately two times the physical apparatus completion times. A number of possible factors for this temporal discrepancy have been identified but their effect has not been quantified.

  • Experiments using multimodal virtual environments in Design for Assembly analysis
    Presence: Teleoperators & Virtual Environments, 1997
    Co-Authors: Rakesh Gupta, Thomas B. Sheridan, Daniel E. Whitney
    Abstract:

    The goal of this work is to investigate whether estimates of ease of part handling and part insertion can be provided by multimodal simulation using virtual environment VE technology. The long-term goal is to use this data to extend computer-aided Design CAD systems in order to evaluate and compare alternate Designs using Design for Assembly analysis. A unified, physically-based model has been developed for modeling dynamic interactions and has been built into a multimodal VE system called the Virtual Environment for Design for Assembly VEDA. The Designer sees a visual representation of objects, hears collision sounds when objects hit each other, and can feel and manipulate the objects through haptic interface devices with force feedback. Currently these models are 2D in order to preserve interactive update rates. Experiments were conducted with human subjects using a two-dimensional peg-in-hole apparatus and a VEDA simulation of the same apparatus. The simulation duplicated as well as possible the weight, shape, size, peg-hole clearance, and fictional characteristics of the physical apparatus. The experiments showed that the multimodal VE is able to replicate experimental results in which increased task completion times correlated with increasing task difficulty measured as increased friction, increased handling distance, and decreased peg-hole clearance. However, the multimodal VE task completion times are approximately twice those of the physical apparatus completion process. A number of possible factors have been identified, but the effect of these factors has not been quantified.