Difference between revisions of "Team:TAS Taipei/Model"

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                         <a href="#PR" class="pageNavBig">PR</a>
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                         <a href="#PR" class="pageNavBig">PROTEORHODOPSIN TRAPPING MODEL</a>
 
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                         <a href="#PRResults" class="pageNavSm">Results</a>
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                         <a href="#bind" class="pageNavSm">Binding Constants</a>
 
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                         <a href="#FDM" class="pageNavSm">Finite Difference Method</a>
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                         <a href="#app" class="pageNavSm">Example Application</a>
 
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                         <a href="#bio" class="pageNavBig">BIOFILM</a>
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                        <a href="#calc" class="pageNavSm">Calculations</a>
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                         <a href="#bio" class="pageNavBig">BIOFILM TRAPPING MODEL</a>
 
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                             Our goal is to remove as many NPs as possible from wastewater systems to minimize damage to the environment and our health. Due to the sheer variety of manufactured NPs and the significant chemical differences between them, we looked for common properties across different types of NPs. Most industrially produced NPs are coated with capping agents to prevent aggregation (ref). <b>We specifically target citrate, the most common NP capping agent</b> (<i>Levard et al.</i> 2012).
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                     <div class="row" id="PR">
 
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                         <h1 class="title2 col-lg-12">PROTEORHODOPSIN</h1>
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                         <h1 class="title2 col-lg-12">PROTEORHODOPSIN TRAPPING MODEL</h1>
 
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                         <h1 class="section-title col-lg-12">Proteorhodopsin and citrate binding modeled as a ligand-receptor interaction</h1>
 
                         <h1 class="section-title col-lg-12">Proteorhodopsin and citrate binding modeled as a ligand-receptor interaction</h1>
 
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                     <div class="row" id="bind">
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                         <h1 class="section-title col-lg-12">Determining NP binding rate (kon) and dissociation rate (koff) constants using experimental data</h1>
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                     <div class="row" id="PRResults">
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                         <h1 class="section-title col-lg-12">Results of Our Model</h1>
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                        <h1 class="section-title col-lg-12">Finite-Difference Method (FDM) Explanation</h1>
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                     <div class="row" id="calc">
 
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                         <h1 class="section-title col-lg-12">Calculator</h1>
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                         <h1 class="section-title col-lg-12">Calculations</h1>
 
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                         <h1 class="title2 col-lg-12">BIOFILM</h1>
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                         <h1 class="title2 col-lg-12">BIOFILM TRAPPING MODEL</h1>
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                     <div class="row" id="TR">
 
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                         <h1 class="section-title col-lg-12">Evaluating the trapping rate through the change in substrate concentration and volumetric flow rate</h1>
 
                         <h1 class="section-title col-lg-12">Evaluating the trapping rate through the change in substrate concentration and volumetric flow rate</h1>
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                         <h1 class="section-title col-lg-12">Determining the significance of different factors</h1>
 
                         <h1 class="section-title col-lg-12">Determining the significance of different factors</h1>
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                     <div class="row" id="SA">
 
                         <h1 class="section-title col-lg-12">Surface Area</h1>
 
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                         <h1 class="section-title col-lg-12">Biofilm time trial results, finding average trapping rate (per SA)</h1>
 
                         <h1 class="section-title col-lg-12">Biofilm time trial results, finding average trapping rate (per SA)</h1>
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Revision as of 02:51, 28 October 2017

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Project
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Project

Experiment

Modeling

Prototype

Human Practice

Biosafety

About Us

Attributions

Home

Modeling

Computational Biology provides us insight on how to apply experimental data to real world applications!

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MODELING

Our model aims to facilitate the implementation of our proteorhodopsin (PR)-expressing bacteria and biofilm prototype in wastewater treatment plants (WWTPs). Using variables which are specific to any WWTP (such as flow rate and water retention time in each tank), we can determine the amount of bacteria or surface area of biofilm needed to reduce nanoparticle concentration in the treated effluent.

INTRODUCTION

filler text

PROTEORHODOPSIN TRAPPING MODEL

Proteorhodopsin and citrate binding modeled as a ligand-receptor interaction

Determining NP binding rate (kon) and dissociation rate (koff) constants using experimental data

Calculations

Influent (Initial) NP Concentration in WWTP (umols/cm3)
Targeted Effluent (Initial) NP Concentration in WWTP (umols/cm3)
Volume of water in clarifier tank of WWTP (L)
Vertical velocity of water making contact with the biofilm (cm/minutes)
Time of contact between NP contaminated water and our biofilm construct (minutes)
cm2 of biofilm needed for clean up:

BIOFILM TRAPPING MODEL

Evaluating the trapping rate through the change in substrate concentration and volumetric flow rate

Determining the significance of different factors

Surface Area

Biofilm time trial results, finding average trapping rate (per SA)

Calculator

Initial volume of clarifier tank (L)
Final volume of clarifier tank (L)
Initial concentration of NP in tank (micromolar)
Targeted final concentration on NP in tank (micromolar)
Vertical velocity of water (or velocity of water in contact with biofilm, cm/min)
Time for biofilm to be in contact with NP solution (minutes)
Surface area of biofilm needed (cm2)

REFERENCES

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