High-precision nuclear magnetic resonance probe suitable for in situ studies of high-temperature metallic melts

High-temperature nuclear magnetic resonance (NMR) has proven to be very useful for detecting the temperature-induced structural evolution and dynamics in melts. However, the sensitivity and precision of high-temperature NMR probes are limited. Here we report a sensitive and stable high-temperature NMR probe based on laser-heating, suitable for in situ studies of metallic melts, which can work stably at the temperature of up to 2000 K. In our design, a well-designed optical path and the use of a water-cooled copper radio-frequency (RF) coil significantly optimize the signal-to-noise ratio (S/NR) at high temperatures. Additionally, a precise temperature controlling system with an error of less than ±1 K has been designed. After temperature calibration, the temperature measurement error is controlled within ±2 K. As a performance testing, 27Al NMR spectra are measured in Zr-based metallic glass-forming liquid in situ. Results show that the S/NR reaches 45 within 90 s even when the sample's temperature is up to 1500 K and that the isothermal signal drift is better than 0.001 ppm per hour. This high-temperature NMR probe can be used to clarify some highly debated issues about metallic liquids, such as glass transition and liquid-liquid transition.

Structural Evolution, Redox Mechanism, and Ionic Diffusion in Rhombohedral Na2FeFe(CN)6 for Sodium-Ion Batteries: First-Principles Calculations

Prussian blue analogs (Na2FeFe(CN)6) have been regarded as potential cathode materials for sodium-ion batteries (SIBs) due to their low-cost iron resources and open framework. Herein, the detailed first-principles calculations have been performed to investigate the electrochemical properties of NaxFeFe(CN)6 during Na ion extraction. The material undergoes a phase transition from a dense rhombohedral to open cubic structure upon half-desodiation, which is resulted from competition of the Na−N Coulomb attraction and d−π covalent bonding of Fe−N. The analyses on the density of states, magnetic moments and Bader charges of NaxFeFe(CN)6 reveal that there involve in the successive redox reactions of high-spin Fe2+/Fe3+ and low-spin Fe2+/Fe3+ couples during desodiation. Moreover, the facile three-dimensional diffusion channels for Na+ ions exhibit low diffusion barriers of 0.4 eV ~ 0.44 eV, which ensures a rapid Na+ transport in the NaxFeFe(CN)6 framework, contributing to high rate performance of the battery. This study gives a deeper understanding of the electrochemical mechanisms of NaxFeFe(CN)6 during Na+ extraction, which is beneficial for the rational design of superior PBA cathodes for SIBs.

Covariant Fitness Clusters Reveal Structural Evolution of SARS-CoV-2 Polymerase Across the Human Population

Understanding the fitness landscape of viral mutations is crucial for uncovering the evolutionary mechanisms contributing to pandemic behavior. Here, we apply a Gaussian process regression (GPR) based machine learning approach that generates spatial covariance (SCV) relationships to construct stability fitness landscapes for the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. GPR generated fitness scores capture on a residue-by-residue basis a covariant fitness cluster centered at the C487-H642-C645-C646 Zn2+ binding motif that iteratively evolves since the early phase pandemic. In the Alpha and Delta variant of concern (VOC), multi-residue SCV interactions in the NiRAN domain form a second fitness cluster contributing to spread. Strikingly, a novel third fitness cluster harboring a Delta VOC basal mutation G671S augments RdRp structural plasticity to potentially promote rapid spread through viral load. GPR principled SCV provides a generalizable tool to mechanistically understand evolution of viral genomes at atomic resolution contributing to fitness at the pathogen-host interface.