Probing spin dynamics of ultra-thin van der Waals magnets via photon-magnon coupling.

Layered van der Waals (vdW) magnets can maintain a magnetic order even down to the single-layer regime and hold promise for integrated spintronic devices. While the magnetic ground state of vdW magnets was extensively studied, key parameters of spin dynamics, like the Gilbert damping, crucial for designing ultra-fast spintronic devices, remains largely unexplored. Despite recent studies by optical excitation and detection, achieving spin wave control with microwaves is highly desirable, as modern integrated information technologies predominantly are operated with these. The intrinsically small numbers of spins, however, poses a major challenge to this. Here, we present a hybrid approach to detect spin dynamics mediated by photon-magnon coupling between high-Q superconducting resonators and ultra-thin flakes of Cr2Ge2Te6 (CGT) as thin as 11 nm. We test and benchmark our technique with 23 individual CGT flakes and extract an upper limit for the Gilbert damping parameter. These results are crucial in designing on-chip integrated circuits using vdW magnets and offer prospects for probing spin dynamics of monolayer vdW magnets.

Biomass dynamics in a logged forest: the role of wood density.

Wood density (WD) is believed to be a key trait in driving growth strategies of tropical forest species, and as it entails the amount of mass per volume of wood, it also tends to correlate with forest carbon stocks. Yet there is relatively little information on how interspecific variation in WD correlates with biomass dynamics at the species and population level. We determined changes in biomass in permanent plots in a logged forest in Vietnam from 2004 to 2012, a period representing the last 8 years of a 30 years logging cycle. We measured diameter at breast height (DBH) and estimated aboveground biomass (AGB) growth, mortality, and net AGB increment (the difference between AGB gains and losses through growth and mortality) per species at the individual and population (i.e. corrected for species abundance) level, and correlated these with WD. At the population level, mean net AGB increment rates were 6.47 Mg ha-1 year-1 resulting from a mean AGB growth of 8.30 Mg ha-1 year-1, AGB recruitment of 0.67 Mg ha-1 year-1 and AGB losses through mortality of 2.50 Mg ha-1 year-1. Across species there was a negative relationship between WD and mortality rate, WD and DBH growth rate, and a positive relationship between WD and tree standing biomass. Standing biomass in turn was positively related to AGB growth, and net AGB increment both at the individual and population level. Our findings support the view that high wood density species contribute more to total biomass and indirectly to biomass increment than low wood density species in tropical forests. Maintaining high wood density species thus has potential to increase biomass recovery and carbon sequestration after logging.

Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest in Vietnam.

Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam.