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Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions
(2023-12-26) Prüser, Jan; Huber, Florian
Modeling and predicting extreme movements in GDP is notoriously difficult, and the selection of appropriate covariates and/or possible forms of nonlinearities are key in obtaining precise forecasts. In this paper, our focus is on using large datasets in quantile regression models to forecast the conditional distribution of US GDP growth. To capture possible nonlinearities, we include several nonlinear specifications. The resulting models will be huge dimensional, and we thus rely on a set of shrinkage priors. Since Markov chain Monte Carlo estimation becomes slow in these dimensions, we rely on fast variational Bayes approximations to the posterior distribution of the coefficients and the latent states. We find that our proposed set of models produces precise forecasts. These gains are especially pronounced in the tails. Using Gaussian processes to approximate the nonlinear component of the model further improves the good performance, in particular in the right tail.
Pyridinium‐derived mesoionic N‐heterocyclic olefins (py‑mNHOs)
(2023-12-28) Sun, Qiu; Eitzinger, Andreas; Esken, Robin; Antoni, Patrick W.; Mayer, Robert J.; Ofial, Armin R.; Hansmann, Max M.
Mesoionic polarization allows access to electron-rich olefins that have found application as organocatalysts, ligands, or nucleophiles. Herein, we report the synthesis and characterization of a series of 3-methylpyridinium-derived mesoionic olefins (py-mNHOs). We used a DFT-supported design concept, which showed that the introduction of aryl groups in the 1-, 2-, 4-, and 6-positions of the heterocyclic core allowed the kinetic stabilization of the novel mesoionic compounds. Tolman electronic parameters indicate that py-mNHOs are remarkably strong σ-donor ligands toward transition metals and main group Lewis acids. Additionally, they are among the strongest nucleophiles on the Mayr reactivity scale. In reactions of py-mNHOs with electron-poor π-systems, a gradual transition from the formation of zwitterionic adducts via stepwise to concerted 1,3-dipolar cycloadditions was observed experimentally and analyzed by quantum-chemical calculations.
Structural control of highly efficient thermally activated delayed fluorescence in carbene zinc(II) dithiolates
(2023-12-08) Mitra, Mousree; Mrózek, Ondřej; Putscher, Markus; Guhl, Jasper; Hupp, Benjamin; Belyaev, Andrey; Marian, Christel M.; Steffen, Andreas
Luminescent metal complexes based on earth abundant elements are a valuable target to substitute 4d/5d transition metal complexes as triplet emitters in advanced photonic applications. Whereas CuI complexes have been thoroughly investigated in the last two decades for this purpose, no structure-property-relationships for efficient luminescence involving triplet excited states from ZnII complexes are established. Herein, we report on the design of monomeric carbene zinc(II) dithiolates (CZT) featuring a donor-acceptor-motif that leads to highly efficient thermally activated delayed fluorescence (TADF) with for ZnII compounds unprecedented radiative rate constants kTADF=1.2×106 s−1 at 297 K. Our high-level DFT/MRCI calculations revealed that the relative orientation of the ligands involved in the ligand-to-ligand charge transfer (1/3LLCT) states is paramount to control the TADF process. Specifically, a dihedral angle of 36–40° leads to very efficient reverse intersystem-crossing (rISC) on the order of 109 s−1 due to spin-orbit coupling (SOC) mediated by the sulfur atoms in combination with a small ΔES1-T1 of ca. 56 meV.
Exciton–polaritons in CsPbBr3 crystals revealed by optical reflectivity in high magnetic fields and two‐photon spectroscopy
(2023-11-06) Yakovlev, Dmitri R.; Crooker, Scott A.; Semina, Marina A.; Rautert, Janina; Mund, Johannes; Dirin, Dmitry N.; Kovalenko, Maksym V.; Bayer, Manfred
Cesium lead bromide (CsPbBr3) is a representative material of the emerging class of lead halide perovskite semiconductors that possess remarkable optoelectronic properties. Its optical properties in the vicinity of the bandgap energy are greatly contributed by excitons, which form exciton polaritons due to strong light–matter interactions. Exciton–polaritons in solution-grown CsPbBr3 crystals are examined by means of circularly polarized reflection spectroscopy measured in high magnetic fields up to 60 T. The excited 2P exciton state is measured by two-photon absorption. Comprehensive modeling and analysis provides detailed quantitative information about the exciton–polariton parameters: exciton binding energy of 32.5 meV, oscillator strength characterized by longitudinal–transverse splitting of 5.3 meV, damping of 6.7 meV, reduced exciton mass of 0.18m0, exciton diamagnetic shift of 1.6 μeV T−2, and exciton Landé factor gx = +2.35. It is shown that the exciton states can be described within a hydrogen-like model with an effective dielectric constant of 8.7. From the measured exciton longitudinal–transverse splitting, Kane energy of Ep = 15 eV is evaluated, which is in reasonable agreement with values of 11.8–12.5 eV derived from the carrier effective masses.
Optimal design and operation of reactive extrusion processes: modeling, model validation, and optimization algorithm
(2023-10-05) Cegla, Maximilian; Engell, Sebastian
In this work, a methodology for the optimal design and operation of reactive extrusion processes in twin-screw extruders is presented. As a process model, a very accurate mechanistic finite volume twin-screw extruder model is used which is adapted to the reactive extrusion case. In the model, in contrast to other models, the pressure is described as a differential state in order to have a consistent set of equations. The model is compared to other models and advantages and disadvantages with respect to accuracy and computation time are discussed. For optimization, a memetic optimization algorithm (MA) that consists of a combination of a local optimization for the continuous operating parameters and an evolutionary algorithm (EA) for the global optimization of the discrete decision variables is employed to overcome the drawback of the longer model simulation time compared to simpler models. A reduction of optimization time by 90% for the MA compared to the EA was observed. The presented modeling and optimization methodology is validated on the widely investigated reactive extrusion process for ε-Caprolactone. The methodology is very flexible and the underlying model has good prediction characteristics, thus it is applicable to a wide range of reactive extrusion processes of industrial interest.