Quantum Chemical Simulation of the Qy Absorption Spectrum of Zn Chlorin Aggregates for Artificial Photosynthesis

Density functional theory simulations were employed to explore the geometric, electronic and optical properties of two croconate dye molecules adsorbed on TiO2 brookite nanocluster. The calculations were based on determination of conjugate length, absorption spectra and light harvesting efficiency. The absorption energies, absorption spectra and electronic states of the dye-TiO2 complex were calculated using TD/DFT. The analysis of the excited state properties shows that CR1 and CR2 showed excitation around 580 nm and 680 nm respectively with a corresponding maximum light harvesting efficiency of 66% and 33.9% for CR1 and CR2 respectively. The absorption wavelength support that the croconate dye molecules can improve the efficiency of DSSCs as they can absorb the near infrared photons which increases the absorption range of DSSCs on the solar spectrum. The adsorption energies of CR1 and CR2 on TiO2 brookite are 3.93 eV and 5.53 eV respectively, suggesting a stable grafting of the dyes onto the surface of the semiconductor. The shifting of the absorption wavelength towards the infrared region upon adsorption gives probability of more electron transport into the large band gap of TiO2.

Download Full-text

Microscopic picture of molecular double doping

10.33774/chemrxiv-2021-v9q4z ◽

2021 ◽

Author(s):

Thomas Bathe ◽

Chuan-Ding Dong ◽

Stefan Schumacher

Keyword(s):

Absorption Spectrum ◽

Charge Transfer ◽

Density Functional ◽

Near Infrared ◽

Infrared Absorption Spectrum ◽

Functional Theory ◽

Double Doping ◽

Molecular Doping ◽

P Type ◽

Dopant Molecule

Double doping, in which a single dopant molecule induces two charge carriers in an organic semiconductor (OSC), was recently experimentally observed and promises to enhance the efficiency of molecular doping. Here we present a theoretical investigation of p-type molecular double doping in a CN6-CP:bithiophene–thienothiophene OSC system. Our analysis is based on density functional theory (DFT) calculations for the electronic ground state. In a molecular complex with two OSC oligomers and one CN6-CP dopant molecule we explicitly demonstrate double integer charge transfer and find formation of two individual polarons on the OSC molecules and a di-anion dopant molecule. We show that the vibrational modes and related infrared absorption spectrum of this complex can be traced back to those of the charged dopant and OSC molecules in their isolated forms. The near-infrared optical absorption spectrum calculated by time-dependent DFT shows both features of typical intra-molecular polaron excitations and weak inter-molecular charge transfer excitations associated with the doping-induced polaron states.

Download Full-text

Bridging the experiment-calculation divide: machine learning corrections to redox potential calculations in implicit and explicit solvent models

10.33774/chemrxiv-2021-mthjp-v2 ◽

2021 ◽

Author(s):

Eugen Hruska ◽

Ariel Gale ◽

Fang Liu

Keyword(s):

Machine Learning ◽

Redox Potential ◽

Density Functional ◽

Implicit Solvent ◽

Systematic Bias ◽

Redox Potentials ◽

Solvent Models ◽

Explicit Solvent ◽

Solvent Model ◽

Implicit And Explicit

Prediction of redox potentials is essential for catalysis and energy storage. Although density functional theory (DFT) calculations have enabled rapid redox potential predictions for numerous compounds, prominent errors persist compared to experimental measurements. In this work, we develop machine learning (ML) models to reduce the errors of redox potential calculations in both implicit and explicit solvent models. Training and testing of the ML correction models are based on the diverse ROP313 dataset with experimental redox potentials measured for organic and organometallic compounds in a variety of solvents. For the implicit solvent approach, our ML models can reduce both the systematic bias and the number of outliers. ML corrected redox potentials also demonstrate less sensitivity to DFT functional choice. For the explicit solvent approach, we significantly reduce the computational costs by embedding the microsolvated cluster in implicit bulk solvent, obtaining converged redox potential results with a smaller solvation shell. This combined implicit-explicit solvent model, together with GPU-accelerated quantum chemistry methods, enabled rapid generation of a large dataset of explicit-solvent-calculated redox potentials for 165 organic compounds, allowing detailed investigation of the error sources in explicit solvent redox potential calculations.

Download Full-text

TDDFT study of absorption spectrum of ketocyanine dye complexes with metal ions: explicit solvent model

Theoretical Chemistry Accounts ◽

10.1007/s00214-010-0791-x ◽

2010 ◽

Vol 127 (5-6) ◽

pp. 743-750 ◽

Cited By ~ 10

Author(s):

Andrzej Eilmes

Keyword(s):

Absorption Spectrum ◽

Metal Ions ◽

Explicit Solvent ◽

Solvent Model ◽

Explicit Solvent Model ◽

Complexes With Metal Ions

Download Full-text

Bridging the experiment-calculation divide: machine learning corrections to redox potential calculations in implicit and explicit solvent models

10.33774/chemrxiv-2021-mthjp ◽

2021 ◽

Author(s):

Eugen Hruska ◽

Ariel Gale ◽

Fang Liu

Keyword(s):

Machine Learning ◽

Redox Potential ◽

Density Functional ◽

Implicit Solvent ◽

Systematic Bias ◽

Redox Potentials ◽

Solvent Models ◽

Explicit Solvent ◽

Solvent Model ◽

Implicit And Explicit

Prediction of redox potentials is essential for catalysis and energy storage. Although density functional theory (DFT) calculations have enabled rapid redox potential predictions for numerous compounds, prominent errors persist compared to experimental measurements. In this work, we develop machine learning (ML) models to reduce the errors of redox potential calculations in both implicit and explicit solvent models. Training and testing of the ML correction models are based on the diverse ROP313 dataset with experimental redox potentials measured for organic and organometallic compounds in a variety of solvents. For the implicit solvent approach, our ML models can reduce both the systematic bias and the number of outliers. ML corrected redox potentials also demonstrate less sensitivity to DFT functional choice. For the explicit solvent approach, we significantly reduce the computational costs by embedding the microsolvated cluster in implicit bulk solvent, obtaining converged redox potential results with a smaller solvation shell. This combined implicit-explicit solvent model, together with GPU-accelerated quantum chemistry methods, enabled rapid generation of a large dataset of explicit-solvent-calculated redox potentials for 165 organic compounds, allowing detailed investigation of the error sources in explicit solvent redox potential calculations.

Download Full-text

Microscopic density functional theory of wetting and drying of a solid substrate by an explicit solvent model of ionic solutions

Molecular Physics ◽

10.1080/00268970903469022 ◽

2009 ◽

Vol 107 (23-24) ◽

pp. 2609-2624 ◽

Cited By ~ 20

Author(s):

Anna Oleksy ◽

Jean-Pierre Hansen

Keyword(s):

Density Functional Theory ◽

Density Functional ◽

Solid Substrate ◽

Functional Theory ◽

Wetting And Drying ◽

Ionic Solutions ◽

Explicit Solvent ◽

Solvent Model ◽

Explicit Solvent Model

Download Full-text

Theoretical prediction of coordination environments and stability constants of lanthanum lactate complexes in solution

Dalton Transactions ◽

10.1039/c5dt03385c ◽

2016 ◽

Vol 45 (39) ◽

pp. 15517-15522 ◽

Cited By ~ 6

Author(s):

Lindsay E. Roy ◽

Leigh R. Martin

Keyword(s):

Density Functional Theory ◽

Theoretical Prediction ◽

Stability Constants ◽

Density Functional ◽

Density Functional Theory Calculations ◽

Functional Theory ◽

Coordination Environment ◽

Continuum Solvent Model ◽

Explicit Solvent ◽

Solvent Model

Using Density Functional Theory calculations in combination with explicit solvent and a continuum solvent model, this work sets out to understand the coordination environment and relevant thermodynamics of La(iii)-lactate complexes.

Download Full-text

Dermacozine N, the First Natural Linear Pentacyclic Oxazinophenazine with UV–Vis Absorption Maxima in the Near Infrared Region, Along with Dermacozines O and P Isolated from the Mariana Trench Sediment Strain Dermacoccus abyssi MT 1.1T

Marine Drugs ◽

10.3390/md19060325 ◽

2021 ◽

Vol 19 (6) ◽

pp. 325

Author(s):

Bertalan Juhasz ◽

Dawrin Pech-Puch ◽

Jioji N. Tabudravu ◽

Bastien Cautain ◽

Fernando Reyes ◽

...

Keyword(s):

Linear Regression ◽

Density Functional ◽

Near Infrared ◽

Linear Regression Analysis ◽

2D Nmr ◽

Multiple Linear Regression Analysis ◽

Infrared Region ◽

Cellular Level ◽

Mariana Trench ◽

Uv Visible

Three dermacozines, dermacozines N–P (1–3), were isolated from the piezotolerant Actinomycete strain Dermacoccus abyssi MT 1.1T, which was isolated from a Mariana Trench sediment in 2006. Herein, we report the elucidation of their structures using a combination of 1D/2D NMR, LC-HRESI-MSn, UV–Visible, and IR spectroscopy. Further confirmation of the structures was achieved through the analysis of data from density functional theory (DFT)–UV–Visible spectral calculations and statistical analysis such as two tailed t-test, linear regression-, and multiple linear regression analysis applied to either solely experimental or to experimental and calculated 13C-NMR chemical shift data. Dermacozine N (1) bears a novel linear pentacyclic phenoxazine framework that has never been reported as a natural product. Dermacozine O (2) is a constitutional isomer of the known dermacozine F while dermacozine P (3) is 8-benzoyl-6-carbamoylphenazine-1-carboxylic acid. Dermacozine N (1) is unique among phenoxazines due to its near infrared (NIR) absorption maxima, which would make this compound an excellent candidate for research in biosensing chemistry, photodynamic therapy (PDT), opto-electronic applications, and metabolic mapping at the cellular level. Furthermore, dermacozine N (1) possesses weak cytotoxic activity against melanoma (A2058) and hepatocellular carcinoma cells (HepG2) with IC50 values of 51 and 38 μM, respectively.

Download Full-text