Reliable Chemical Synthesis of Oligoribonucleotides (RNA) with 2′‐O‐[(Triisopropylsilyl)oxy]methyl(2′‐O‐tom)‐Protected Phosphoramidites

A method for the introduction of the 2′‐O‐[(triisopropylsilyl)oxy]methyl (=tom) group into N‐acetylated, 5′‐O‐dimethoxytritylated ribonucleosides is presented. The corresponding 2′‐O‐tom‐protected phosphoramidite building blocks were obtained in pure form and were successfully employed for the routine synthesis of oligoribonucleotides on DNA synthesizers. Under DNA coupling conditions (2.5 min coupling time for a 1.5‐μmol synthesis scale) and with 5‐(benzylthio)‐1H‐tetrazole (BTT) as activator, 2′‐O‐tom‐protected phosphoramidites exhibited average coupling yields >99.4%. The combination of N‐acetyl and 2′‐O‐tom protecting groups allowed a reliable and complete two‐step deprotection, first with MeNH₂ in EtOH/H₂O and then with Bu₄NF in THF, without concomitant destruction of the product RNA sequences.     

Opposite Orientation of Backbone Inclination in Pyranosyl‐RNA and Homo‐DNA Correlates with Opposite Directionality of Duplex Properties

Backbone inclination is a parameter which can be used for the classification of the structure type of oligonucleotide duplexes. Its significance for the interpretation of the sequence dependence of duplex stability is illustrated based on examples of the p‐RNA and homo‐DNA series.     

Eulerian transported probability density function sub-filter model for large-eddy simulations of turbulent combustion

Reactive flow simulations using large-eddy simulations (LES) require modelling of sub-filter fluctuations. Although conserved scalars like mixture fraction can be represented using a beta-function, the reactive scalar probability density function (PDF) does not follow an universal shape. A one-point one-time joint composition PDF transport equation can be used to describe the evolution of the scalar PDF. The high-dimensional nature of this PDF transport equation requires the use of a statistical ensemble of notional particles and is directly coupled to the LES flow solver. However, the large grid sizes used in LES simulations will make such Lagrangian simulations computationally intractable. Here we propose the use of a Eulerian version of the transported-PDF scheme for simulating turbulent reactive flows. The direct quadrature method of moments (DQMOM) uses scalar-type equations with appropriate source terms to evolve the sub-filter PDF in terms of a finite number of delta-functions. Each delta-peak is characterized by a location and weight that are obtained from individual transport equations. To illustrate the feasibility of the scheme, we compare the model against a particle-based Lagrangian scheme and a presumed PDF model for the evolution of the mixture fraction PDF. All these models are applied to an experimental bluff-body flame and the simulated scalar and flow fields are compared with experimental data. The DQMOM model results show good agreement with the experimental data as well as the other sub-filter models used.     

Generalised scale-by-scale energy-budget equations and large-eddy simulations of anisotropic scalar turbulence at various Schmidt numbers

A necessary condition for the accurate prediction of turbulent flows using large-eddy simulation (LES) is the correct representation of energy transfer between the different scales of turbulence in the LES. For scalar turbulence, transfer of energy between turbulent length scales is described by a transport equation for the second moment of the scalar increment. For homogeneous isotropic turbulence, the underlying equation is the well-known Yaglom equation. In the present work, we study the turbulent mixing of a passive scalar with an imposed mean gradient by homogeneous isotropic turbulence. Both direct numerical simulations (DNS) and LES are performed for this configuration at various Schmidt numbers, ranging from 0.11 to 5.56. As the assumptions made in the derivation of the Yaglom equation are violated for the case considered here, a generalised Yaglom equation accounting for anisotropic effects, induced by the mean gradient, is derived in this work. This equation can be interpreted as a scale-by-scale energy-budget equation, as it relates at a certain scale r terms representing the production, turbulent transport, diffusive transport and dissipation of scalar energy. The equation is evaluated for the conducted DNS, followed by a discussion of physical effects present at different scales for various Schmidt numbers. For an analysis of the energy transfer in LES, a generalised Yaglom equation for the second moment of the filtered scalar increment is derived. In this equation, new terms appear due to the interaction between resolved and unresolved scales. In an a-priori test, this filtered energy-budget equation is evaluated by means of explicitly filtered DNS data. In addition, LES calculations of the same configuration are performed, and the energy budget as well as the different terms are thereby analysed in an a-posteriori test. It is shown that LES using an eddy viscosity model is able to fulfil the generalised filtered Yaglom equation for the present configuration. Further, the dependence of the terms appearing in the filtered energy-budget equation on varying Schmidt numbers is discussed.     

Using physics-informed enhanced super-resolution generative adversarial networks for subfilter modeling in turbulent reactive flows

Turbulence is still one of the main challenges in accurate prediction of reactive flows. Therefore, the development of new turbulence closures that can be applied to combustion problems is essential. Over the last few years, data-driven modeling has become popular in many fields as large, often extensively labeled datasets are now available and training of large neural networks has become possible on graphics processing units (GPUs) that speed up the learning process tremendously. However, the successful application of deep neural networks in fluid dynamics, such as in subfilter modeling in the context of large-eddy simulations (LESs), is still challenging. Reasons for this are the large number of degrees of freedom in natural flows, high requirements of accuracy and error robustness, and open questions, for example, regarding the generalization capability of trained neural networks in such high-dimensional, physics-constrained scenarios. This work presents a novel subfilter modeling approach based on a generative adversarial network (GAN), which is trained with unsupervised deep learning (DL) using adversarial and physics-informed losses. A two-step training method is employed to improve the generalization capability, especially extrapolation, of the network. The novel approach gives good results in a priori and a posteriori tests with decaying turbulence including turbulent mixing, and the importance of the physics-informed continuity loss term is demonstrated. The applicability of the network in complex combustion scenarios is furthermore discussed by employing it in reactive and inert LESs of the Spray A case defined by the Engine Combustion Network (ECN).     

Unimolecular reactions of the resonance-stabilized cyclopentadienyl radicals and their role in the polycyclic aromatic hydrocarbon formation

Resonance-stabilized cyclopentadienyl radicals are important intermediate species in the combustion of transportation fuels. It not only serves as precursors for polycyclic aromatic hydrocarbon (PAH) formation, but also involves in the formation of fundamental PAH precursors such as propargyl and acetylene. In this work, the unimolecular reactions of the cyclopentadienyl radicals are theoretically studied based on high-level quantum chemistry and RRKM/master equation calculations. Stationary points on the potential energy surface (PES) are calculated at the CCSD(T)/CBS//M06–2X/6–311++(d,p) level of theory. The branching ratios of unimolecular reactions of the cyclopentadienyl radicals are analyzed for a broad temperature range from 500 to 2500 K and pressures from 0.01 to 100 atm. It is found that the isomerization reaction of the cyclopentadienyl radical via 1,2-hydrogen transfer dominates at low temperatures and high pressures, while the well-skipping decomposition reaction which forms propargyl and acetylene is important at high temperatures and low pressures. Both the decomposition reaction of the cyclopentadienyl radicals and its reverse reaction show pronounced pressure dependence, and their reaction rate constants are compared against available low-pressure experimental measurements and theoretical studies. The temperature- and pressure-dependent rate coefficients for important reactions involved on the C₅H₅ PES are calculated and updated in a chemical kinetic model. Impacts of the unimolecular reactions of the cyclopentadienyl radicals on the PAH formation are explored by the numerical modeling of a low-pressure cyclopentene counterflow diffusion flame.     

A joint volume-surface model of soot aggregation with the method of moments

In this work, a bivariate model of soot aggregation is formulated within the framework of the Method of Moments with Interpolative Closure (MOMIC). In the bivariate model, soot particles are represented by two independent variables: their volume and surface area. This joint formulation also allows for the blending of aggregation and coalescence with the two as limits. The new formulation is compared to the old formulation with the univariate model as well as both the Direct Quadrature Method of Moments (DQMOM) and Direct Simulation Monte Carlo (DSMC) for a laminar premixed ethylene flame. With the bivariate model, MOMIC is shown to predict volume fraction and number density very accurately and gives some insight into the properties of the aggregates.     

On Facts and Artefacts: The Difficulty to Evaluate an Artificial Nuclease

A number of promising synthetic catalysts for the hydrolytic degradation of RNA have been developed in recent years. Some of them show remarkable selectivity for pyrimidine nucleotides. The general problem of all these studies is to distinguish between real effects and artefacts caused by traces of contaminating natural ribonucleases. We show that methods representing the current state of the art (diethylpyrocarbonate treatment, sterilization, ultrafiltration, etc.) do not sufficiently protect against severe artefacts. However, an incorruptible assay could be found by comparing the cleavage of RNA and its mirror image. Enantiomeric RNA is completely resistant to enzymatic degradation, whereas achiral nonpeptide catalysts, by fundamental laws of symmetry, cannot distinguish between enantiomers and will induce exactly the same cleavage pattern with both substrates.