Digitalization in Thermodynamics

Digitalization is about data and how they are used. This has always been a key topic in applied thermodynamics. In the present work, the influence of the current wave of digitalization on thermodynamics is analyzed. Thermodynamic modeling and simulation is changing as large amounts of data of different nature and quality become easily available. The power and complexity of thermodynamic models and simulation techniques is rapidly increasing, and new routes become viable to link them to the data. Machine learning opens new perspectives, when it is suitably combined with classical thermodynamic theory. Illustrated by examples, different aspects of digitalization in thermodynamics are discussed: strengths and weaknesses as well as opportunities and threats

Disentangling global and local ring currents †

Magnetic field-induced ring currents in aromatic and antiaromatic molecules cause characteristic shielding and deshielding effects in the molecules' NMR spectra. However, it is difficult to analyze (anti)aromaticity directly from experimental NMR data if a molecule has multiple ring current pathways. Here we present a method for using the Biot-Savart law to deconvolute the contributions of different ring currents to the experimental NMR spectra of polycyclic compounds. This method accurately quantifies local and global ring current susceptibilities in porphyrin nanorings, as well as in a bicyclic dithienothiophene-bridged [34]octaphyrin. There is excellent agreement between ring current susceptibilities derived from both experimental and computationally-predicted chemical shifts, and with ring currents calculated by the GIMIC method. Our method can be applied to any polycyclic system, with any number of ring currents, provided that appropriate NMR data are available

A Synthesis of Hybrid RANS/LES CFD Results for F-16XL Aircraft Aerodynamics

A synthesis is presented of recent numerical predictions for the F-16XL aircraft flow fields and aerodynamics. The computational results were all performed with hybrid RANS/LES formulations, with an emphasis on unsteady flows and subsequent aerodynamics, and results from five computational methods are included. The work was focused on one particular low-speed, high angle-of-attack flight test condition, and comparisons against flight-test data are included. This work represents the third coordinated effort using the F-16XL aircraft, and a unique flight-test data set, to advance our knowledge of slender airframe aerodynamics as well as our capability for predicting these aerodynamics with advanced CFD formulations. The prior efforts were identified as Cranked Arrow Wing Aerodynamics Project International, with the acronyms CAWAPI and CAWAPI-2. All information in this paper is in the public domain

Synthesis of Hybrid Computational Fluid Dynamics Results for F-16XL Aircraft Aerodynamics

A synthesis is presented of recent numerical predictions for the F-16XL aircraft flowfields and aerodynamics. The computational results were all performed with hybrid RANS/LES formulations, with an emphasis on unsteady flows and subsequent aerodynamics, and results from five computational methods are included. The work was focused on one particular low-speed, high angle-of-attack flight test condition, and comparisons against flight-test data are included. This work represents the third coordinated effort using the F-16XL aircraft, and a unique flight-test data set, to advance our knowledge of slender airframe aerodynamics as well as our capability for predicting these aerodynamics with advanced CFD formulations. The prior efforts were identified as Cranked Arrow Wing Aerodynamics Project International, with the acronyms CAWAPI and CAWAPI-2

Exciton-Exciton Annihilation as a Probe of Exciton Diffusion in Large Porphyrin Nanorings

The photophysical behavior of natural and artificial cyclic supramolecular structures has been intensively investigated in the past decade. Among the artificial structures, large fully π-conjugated porphyrin nanorings are of particular interest because of their electronic, structural, and topological features, which make them suitable candidates for light-harvesting applications. A number of factors affect the efficiency with which such structures harvest and transmit energy. For instance, under intense irradiation conditions, the efficiency of light harvesting can be quenched by competing processes, such as exciton–exciton annihilation. Here, we investigate the pump fluence dependence of the transient absorption spectra of a series of porphyrin nanorings ranging in circumference between 13 and 52 nm (10–40 porphyrin units). This allowed the isolation of a fluence-dependent fast-decaying component in all but the smallest nanorings studied. This effect has been assigned to exciton–exciton annihilation and fit to a one-dimensional exciton diffusion model, which confirms that the exciton size and/or its mobility are inversely proportional to the nanoring size

Investigating and quantifying molecular complexity using assembly theory and spectroscopy

Current approaches to evaluate molecular complexity use algorithmic complexity, rooted in computer science, and thus are not experimentally measurable. Directly evaluating molecular complexity could be used to study directed vs undirected processes in the creation of molecules, with potential applications in drug discovery, the origin of life, and artificial life. Assembly theory has been developed to quantify the complexity of a molecule by finding the shortest path to construct the molecule from building blocks, revealing its molecular assembly index (MA). In this study, we present an approach to rapidly infer the MA of molecules from spectroscopic measurements. We demonstrate that the MA can be experimentally measured by using three independent techniques: nuclear magnetic resonance (NMR), tandem mass spectrometry (MS/MS), and infrared spectroscopy (IR). By identifying and analyzing the number of absorbances in IR spectra, carbon resonances in NMR, or molecular fragments in tandem MS, the MA of an unknown molecule can be reliably estimated. This represents the first experimentally quantifiable approach to determining molecular assembly. This paves the way to use experimental techniques to explore the evolution of complex molecules as well as a unique marker of where an evolutionary process has been operating

Predicting Activity Coefficients at Infinite Dilution for Varying Temperatures by Matrix Completion

Activity coefficients describe the nonideality of liquid mixtures and are essential for calculating equilibria. The activity coefficients at infinite dilution in binary mixtures are particularly important as the activity coefficients at finite concentrations can be predicted based on their knowledge not only in binary mixtures but also in multicomponent mixtures. The available experimental data on these activity coefficients at infinite dilution in binary mixtures is readily accessible in databases and can be organized in a matrix with the rows representing the solutes and the columns representing the solvents or vice versa. As experimental data is lacking for many binary mixtures, this matrix is only sparsely populated. Filling its gaps using predictive methods is essential. Recently, matrix completion methods (MCMs) have been applied successfully for this purpose. However, only isothermal data sets have been considered. In the present work, we apply an MCM to predict activity coefficients at infinite dilution at varying temperatures. Furthermore, we show how one can incorporate physical knowledge on the nature of the temperature dependency of the activity coefficients at infinite dilution. The predictions obtained with this new approach outperform those obtained with the best currently available physical prediction method for activity coefficients at infinite dilution, the modified UNIFAC (Dortmund) method

Digitalization in Thermodynamics

Digitalization is about data and how they are used. This has always been a key topic in applied thermodynamics. In the present work, the influence of the current wave of digitalization on thermodynamics is analyzed. Thermodynamic modeling and simulation is changing as large amounts of data of different nature and quality become easily available. The power and complexity of thermodynamic models and simulation techniques is rapidly increasing, and new routes become viable to link them to the data. Machine learning opens new perspectives, when it is suitably combined with classical thermodynamic theory. Illustrated by examples, different aspects of digitalization in thermodynamics are discussed: strengths and weaknesses as well as opportunities and threats

Population and Coherence Dynamics in Large Conjugated Porphyrin Nanorings

In photosynthesis nature exploits the distinctive electronic properties of chromophores arranged in supramolecular rings for efficient light harvesting. Among synthetic supramolecular cyclic structures, porphyrin nanorings have attracted considerable attention as they have a resemblance to naturally occurring light-harvesting structures but offer the ability to control ring size and the level of disorder. Here, broadband femtosecond transient absorption spectroscopy, with pump pulses in resonance with either the high or the low energy sides of the inhomogeneously broadened absorption spectrum, is used to study the population dynamics and ground and excited state vibrational coherence in large porphyrin nanorings. A series of fully conjugated, alkyne bridged, nanorings constituted of between ten and forty porphyrin units is studied. Pump-wavelength dependent fast spectral evolution is observed. A fast rise or decay of the stimulated emission are observed when large porphyrin nanorings are excited on, respectively, the high or low energy side of the absorption spectrum. Such dynamics are consistent with the hypothesis of a variation in transition dipole moment across the inhomogeneously broadened ground state ensemble. Oscillatory dynamics on the sub-ps time domain are observed in both pumping conditions. A combined analysis of the excitation wavelength-dependent transient spectra along with the amplitude and phase evolution of the oscillations allows assignment to vibrational wavepackets evolving on either ground or excited states electronic potential energy surfaces. Even though porphyrin nanorings support highly delocalized electronic wavefunctions, with coherence length spanning tens of chromophores, the measured vibrational coherences remain localised on the monomers. The main contributions to the beatings are assigned to two vibrational modes localised on the porphyrin cores: a Zn-N stretching mode and a skeletal methinic/pyrrolic C-C stretching and in-plane bending mode

Global Aromaticity and Antiaromaticity in Porphyrin Nanoring Anions

Doping, through oxidation or reduction, is often used to modify the properties of π-conjugated oligomers. In most cases, the resulting charge distribution is difficult to determine. If the oligomer is cyclic and doping establishes global aromaticity or antiaromaticity, then it is certain that the charge is fully delocalized over the entire perimeter of the ring. Here we show that reduction of a six-porphyrin nanoring using decamethylcobaltocene results in global aromaticity (in the 6– state; [90 π]) and antiaromaticity (in the 4– state; [88 π]), consistent with Hückel’s rules. Aromaticity is assigned by NMR spectroscopy and density-functional theory calculations. <br /