Pulsed EPR Dipolar Spectroscopy under the Breakdown of the High-Field Approximation: The High-Spin Iron(III) Case

Pulsed EPR dipolar spectroscopy (PDS) offers several methods for measuring dipolar coupling and thus the distance between electron-spin centers. To date, PDS measurements to metal centers were limited to ions that adhere to the high-field approximation. Here, the PDS methodology is extended to cases where the high-field approximation breaks down on the example of the high-spin Fe³⁺/nitroxide spin-pair. First, the theory developed by Maryasov et al. (Appl. Magn. Reson. 2006 , 30, 683–702) was adapted to derive equations for the dipolar coupling constant, which revealed that the dipolar spectrum does not only depend on the length and orientation of the interspin distance vector with respect to the applied magnetic field but also on its orientation to the effective g-tensor of the Fe³⁺ ion. Then, it is shown on a model system and a heme protein that a PDS method called relaxation-induced dipolar modulation enhancement (RIDME) is well-suited to measuring such spectra and that the experimentally obtained dipolar spectra are in full agreement with the derived equations. Finally, a RIDME data analysis procedure was developed, which facilitates the determination of distance and angular distributions from the RIDME data. Thus, this study enables the application of PDS to for example, the highly relevant class of high-spin Fe³⁺ heme proteins.     

Tuning the phase behavior of semicrystalline hydrogenated polynorbornene via epimerization

Hydrogenated polynorbornene (hPN) synthesized by ring‐opening metathesis polymerization (ROMP) exhibits a thermoreversible change in crystal polymorph at a temperature T _cc below its melting point, T _m. The polymorphic transition corresponds to a sharp increase in rotational disorder around the chain axis as the temperature is increased above T _cc. Saturation of ROMP polynorbornene (PN) to hPN can be achieved through both catalytic and noncatalytic approaches. Here, three different hydrogenation routes were employed on the same precursor polymer: catalytic routes over either supported Pd⁰ or a Ni/Al complex, and noncatalytic saturation with diimide. The different hydrogenation routes result in hPNs with varying degrees of epimerization of the cyclopentylene ring (from cis to trans); these epimerized units are included in the hPN crystals. The crystal structure of the rotationally ordered hPN polymorph, observed below T _cc, changes sharply at low levels of epimerization and then is weakly influenced by further increases in trans content. The stability of the rotationally ordered hPN polymorph decreases with increasing epimerization, as reflected in a reduction of T _cc from 134 °C to 92 °C at 22% epimerization. T _cc is less affected by epimerization than by the inclusion of a similar content of 5‐methylnorbornene units, reflecting the smaller size of the trans defect. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019 , 57, 1188–1195     

Gold-surface binding of molecular switches studied by M?ssbauer spectroscopy

The nonanuclear coordination compound [Mo^IV{(CN)Fe^III(3-methyl-saldptn)}₈]Cl₄ exhibits multiple spin transitions (3-methyl-saldptn = N,N′-bis(3′′-methyl-2′′-hydroxy-benzyliden)-1,7-diamino-4-azaheptane). This spin crossover cluster is bound via a self-assembled monolayer onto a two dimensional array gold surface. M?ssbauer spectroscopy indicates that the thermally and optically induced spin crossover of the compound is maintained. Thereby, the foundation for its potential practical application (e.g. in the field of information storage) was laid.     

BAMLSS: Bayesian Additive Models for Location,Scale, and Shape (and Beyond)

Bayesian analysis provides a convenient setting for the estimation of complex generalized additive regression models (GAMs). Since computational power has tremendously increased in the past decade, it is now possible to tackle complicated inferential problems, for example, with Markov chain Monte Carlo simulation, on virtually any modern computer. This is one of the reasons why Bayesian methods have become increasingly popular, leading to a number of highly specialized and optimized estimation engines and with attention shifting from conditional mean models to probabilistic distributional models capturing location, scale, shape (and other aspects) of the response distribution. To embed many different approaches suggested in literature and software, a unified modeling architecture for distributional GAMs is established that exploits distributions, estimation techniques (posterior mode or posterior mean), and model terms (fixed, random, smooth, spatial,…). It is shown that within this framework implementing algorithms for complex regression problems, as well as the integration of already existing software, is relatively straightforward. The usefulness is emphasized with two complex and computationally demanding application case studies: a large daily precipitation climatology, as well as a Cox model for continuous time with space-time interactions. Supplementary material for this article is available online.