Benchmarking DFT approaches for the calculation of polarizability inputs for refractive index predictions in organic polymers

2019 ◽  
Vol 21 (8) ◽  
pp. 4452-4460 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Johannes Hachmann
Keyword(s):  
Refractive Index ◽  
High Throughput ◽  
High Index ◽  
Index Of Refraction ◽  
Organic Polymers ◽  
Dft Model

We benchmark DFT model chemistries to identify approaches that optimize the balance between accuracy and efficiency for this virtual high-throughput studies of polymers with high index of refraction.

scholarly journals Benchmarking DFT Approaches for the Calculation of Polarizability Inputs for Refractive Index Predictions in Organic Polymers

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Johannes Hachmann
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Ad Hoc ◽  
Late Onset ◽  
Index Of Refraction ◽  
Organic Polymers ◽  
Lorenz Equation ◽  
The Density Functional Theory ◽  
Extrapolation Scheme ◽  
Dft Model

<pre>In a previous study, we introduced a new computational protocol to accurately predict the index of refraction (RI) of organic polymers using a combination of <i>first-principles</i> and data modeling. This protocol is based on the Lorentz-Lorenz equation and involves the calculation of static polarizabilities and number densities of oligomer sequences, which are extrapolated to the polymer limit. We chose to compute the polarizabilities within the density functional theory (DFT) framework using the PBE0/def2-TZVP-D3 model chemistry. While this <i>ad hoc</i> choice proved remarkably successful, it is also relatively expensive from a computational perspective. It represents the bottleneck step in the overall RI modeling protocol, thus limiting its utility for virtual high-throughput screening studies, in which efficiency is essential. For polymers that exhibit late-onset extensivity, the employed linear extrapolation scheme can require demanding calculations on long-oligomer sequences, thus becoming another bottleneck.</pre> <pre>In the work presented here, we benchmark DFT model chemistries to identify approaches that optimize the balance between accuracy and efficiency for this application domain. We compare results for conjugated and non-conjugated polymers, augment our original extrapolation approach with a non-linear option, analyze how the polarizability errors propagate into the RI predictions, and offer guidance for method selection. </pre>

scholarly journals Numerical investigation of terahertz polarization-independent multiband ultrahigh refractive index metamaterial by bilayer metallic rectangular ring structure

RSC Advances ◽  
2018 ◽  
Vol 8 (40) ◽  
pp. 22361-22369 ◽  
Author(s):  
Bo Fang ◽  
Lin Chen ◽  
Yuqiang Deng ◽  
Xufeng Jing ◽  
Xue Li
Keyword(s):  
Refractive Index ◽  
Numerical Investigation ◽  
Ring Structure ◽  
High Index ◽  
Index Of Refraction ◽  
Ring Type ◽  
Thin Ring ◽  
Unit Cells ◽  
Polarization Independent ◽  
Terahertz Metamaterials

Multiband high index of refraction can be realized by thin ring-type terahertz metamaterials composed of multilayer coupled unit cells.

scholarly journals Benchmarking DFT Approaches for the Calculation of Polarizability Inputs for Refractive Index Predictions in Organic Polymers

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Johannes Hachmann
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Ad Hoc ◽  
Late Onset ◽  
Index Of Refraction ◽  
Organic Polymers ◽  
Lorenz Equation ◽  
The Density Functional Theory ◽  
Extrapolation Scheme ◽  
Dft Model

<pre>In a previous study, we introduced a new computational protocol to accurately predict the index of refraction (RI) of organic polymers using a combination of <i>first-principles</i> and data modeling. This protocol is based on the Lorentz-Lorenz equation and involves the calculation of static polarizabilities and number densities of oligomer sequences, which are extrapolated to the polymer limit. We chose to compute the polarizabilities within the density functional theory (DFT) framework using the PBE0/def2-TZVP-D3 model chemistry. While this <i>ad hoc</i> choice proved remarkably successful, it is also relatively expensive from a computational perspective. It represents the bottleneck step in the overall RI modeling protocol, thus limiting its utility for virtual high-throughput screening studies, in which efficiency is essential. For polymers that exhibit late-onset extensivity, the employed linear extrapolation scheme can require demanding calculations on long-oligomer sequences, thus becoming another bottleneck.</pre> <pre>In the work presented here, we benchmark DFT model chemistries to identify approaches that optimize the balance between accuracy and efficiency for this application domain. We compare results for conjugated and non-conjugated polymers, augment our original extrapolation approach with a non-linear option, analyze how the polarizability errors propagate into the RI predictions, and offer guidance for method selection. </pre>

scholarly journals Running Droplet Optical Multiplexer

2014 ◽  
Vol 1 (1) ◽  
Author(s):  
Lukas Brandhoff ◽  
Mahmuda Akhtar ◽  
Mike Bülters ◽  
Ralf B. Bergmann ◽  
Michael J. Vellekoop
Keyword(s):  
Refractive Index ◽  
Microfluidic Channel ◽  
High Index ◽  
Index Of Refraction ◽  
The Other ◽  
Specific Input ◽  
Low Refractive Index

AbstractWe present an optofluidic device for switching light from multiple inputs to one common output. The device uses a microfluidic channel filled with high index of refraction oil as a waveguide, and moves low refractive index interruptions in the form of aqueous droplets through the channel. Whenever a droplet passes one of the optical inputs, this specific input is switched through to the output. This produces a running switching of one output following the other creating a 8x1 multiplexer.

scholarly journals Benchmarking DFT Approaches for the Calculation of Polarizability Inputs for Refractive Index Predictions in Organic Polymers

2018 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Johannes Hachmann
Keyword(s):  
High Throughput Screening ◽  
Density Functional ◽  
Ad Hoc ◽  
Late Onset ◽  
Index Of Refraction ◽  
Organic Polymers ◽  
Lorenz Equation ◽  
The Density Functional Theory ◽  
Extrapolation Scheme ◽  
Dft Model

<pre>In a previous study, we introduced a new computational protocol to accurately predict the index of refraction (RI) of organic polymers using a combination of <i>first-principles</i> and data modeling. This protocol is based on the Lorentz-Lorenz equation and involves the calculation of static polarizabilities and number densities of oligomer sequences, which are extrapolated to the polymer limit. We chose to compute the polarizabilities within the density functional theory (DFT) framework using the PBE0/def2-TZVP-D3 model chemistry. While this <i>ad hoc</i> choice proved remarkably successful, it is also relatively expensive from a computational perspective. It represents the bottleneck step in the overall RI modeling protocol, thus limiting its utility for virtual high-throughput screening studies, in which efficiency is essential. For polymers that exhibit late-onset extensivity, the employed linear extrapolation scheme can require demanding calculations on long-oligomer sequences, thus becoming another bottleneck.</pre> <pre>In the work presented here, we benchmark DFT model chemistries to identify approaches that optimize the balance between accuracy and efficiency for this application domain. We compare results for conjugated and non-conjugated polymers, augment our original extrapolation approach with a non-linear option, analyze how the polarizability errors propagate into the RI predictions, and offer guidance for method selection. </pre>

TEM characterization of proton-exchanged LiNbO3 optical waveguides

1986 ◽  
Vol 44 ◽  
pp. 480-481
Author(s):  
W. E. Lee
Keyword(s):  
Refractive Index ◽  
Benzoic Acid ◽  
Optical Waveguides ◽  
Total Internal Reflection ◽  
Index Of Refraction ◽  
Optical Measurements ◽  
Lithium Ions ◽  
Wide Channel ◽  
Tem Characterization

An optical waveguide consists of a several-micron wide channel with a slightly different index of refraction than the host substrate; light can be trapped in the channel by total internal reflection.Optical waveguides can be formed from single-crystal LiNbO3 using the proton exhange technique. In this technique, polished specimens are masked with polycrystal1ine chromium in such a way as to leave 3-13 μm wide channels. These are held in benzoic acid at 249°C for 5 minutes allowing protons to exchange for lithium ions within the channels causing an increase in the refractive index of the channel and creating the waveguide. Unfortunately, optical measurements often reveal a loss in waveguiding ability up to several weeks after exchange.

Combining First-Principles and Data Modeling for the Accurate Prediction of the Refractive Index of Organic Polymers

2017 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
First Principles ◽  
Data Modeling ◽  
Accurate Prediction ◽  
Index Of Refraction ◽  
Structure Theory ◽  
Organic Polymers ◽  
Number Density ◽  
Lorenz Equation ◽  
In Silico Studies ◽  
Wide Range

Organic materials with a high index of refraction (RI) are attracting considerable interest due to their potential application in optic and optoelectronic devices. However, most of these applications require an RI value of 1.7 or larger, while typical carbon-based polymers only exhibit values in the range of 1.3–1.5. This paper introduces an efficient computational protocol for the accurate prediction of RI values in polymers to facilitate in silico studies that an guide the discovery and design of next-generation high-RI materials. Our protocol is based on the Lorentz-Lorenz equation and is parametrized by the polarizability and number density values of a given candidate compound. In the proposed scheme, we compute the former using first-principles electronic structure theory and the latter using an approximation based on van der Waals volumes. The critical parameter in the number density approximation is the packing fraction of the bulk polymer, for which we have devised a machine learning model. We demonstrate the performance of the proposed RI protocol by testing its predictions against the experimentally known RI values of 112 optical polymers. Our approach to combine first-principles and data modeling emerges as both a successful and highly economical path to determining the RI values for a wide range of organic polymers.

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
Data Mining ◽  
Refractive Index ◽  
High Throughput ◽  
First Principles ◽  
High Throughput Screening ◽  
Large Scale ◽  
Computational Study ◽  
High Refractive Index ◽  
Structural Features ◽  
Learning Program

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>

scholarly journals A deep neural network model for packing density predictions and its application in the study of 1.5 million organic molecules

2019 ◽  
Vol 10 (36) ◽  
pp. 8374-8383 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Aditya Sonpal ◽  
Mojtaba Haghighatlari ◽  
Andrew J. Schultz ◽  
Johannes Hachmann
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Refractive Index ◽  
High Throughput ◽  
Neural Network Model ◽  
High Throughput Screening ◽  
Deep Neural Network ◽  
Organic Molecules ◽  
High Refractive Index ◽  
Computational Pipeline

Computational pipeline for the accelerated discovery of organic materials with high refractive index via high-throughput screening and machine learning.

A Simple Method for Prediction of Effective Core Area and Index of Refraction of Single-mode Graded Index Fiber in the Low V Region

2014 ◽  
Vol 35 (4) ◽  
Author(s):  
Angshuman Majumdar ◽  
Satabdi Das ◽  
Sankar Gangopadhyay
Keyword(s):  
Refractive Index ◽  
Single Mode ◽  
Index Of Refraction ◽  
Core Area ◽  
Exact Results ◽  
Simple Method ◽  
Graded Index ◽  
Core Areas ◽  
V Region ◽  
User Friendly

AbstractBased on the simple power series formulation of fundamental mode developed by Chebyshev formalism in the low V region, we prescribe analytical expression for effective core area of graded index fiber. Taking step and parabolic index fibers as examples, we estimate the effective core areas as well as effective refractive index for different normalized frequencies (V number) having low values. We also show that our estimations match excellently with the available exact results. The concerned predictions by our method require little computation. Thus, this simple but accurate formalism will be user friendly for the system engineers.

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