Microbiome–metabolite linkages drive greenhouse gas dynamics over a permafrost thaw gradient
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An integral LiMn 1.5 Ni 0.5 O 4 shell completely wets ∼10 μm LiCoO 2 single crystals to cut off global oxygen migration and enables >4.6 V cycling.
Non-constant temperature profile across extended systems affects dynamics and opens route to quantum control.
The diffusivities of nitrite in concentrated sodium nitrite and simulant radioactive waste observed with 15 N PFGSTE-NMR spectroscopy exceeded predictions based on the Stokes–Einstein relationship.
Both equilibration time and the transfer of Winsor-III microemulsion systems from one container to another affect the structure of the bicontinuous phase in the vertical direction.
The phase state of atmospheric particles impacts atmospheric processes like heterogeneous reactions, cloud droplet activation, and ice nucleation. This study highlights vertically resolved measurements of the phase state of individual particles.
The parameter derivative of the expectation value of the energy, ∂E/∂p, is a key ingredient in variational Monte Carlo (VMC) wave function optimization methods. In some cases, a naïve estimate of this derivative suffers from an infinite variance, which inhibits the efficiency of optimization methods that rely on a stable estimate of the derivative. In this work, we derive a simple regularization of the naïve estimator, which is trivial to implement in existing VMC codes, has finite variance, and a negligible bias, which can be extrapolated to zero bias with no extra cost. We use this estimator to construct an unbiased, finite variance estimation of ∂E/∂p for a multi-Slater–Jastrow trial wave function on the LiH molecule and in the optimization of a multi-Slater–Jastrow trial wave function on the CuO molecule. This regularized estimator is a simple and efficient estimator of ∂E/∂p for VMC optimization techniques.
In this work, we present a machine learning approach to calculating electronic specific heat capacities for a variety of benchmark molecular systems. Our models are based on data from density matrix quantum Monte Carlo, which is a stochastic method that can calculate the electronic energy at finite temperature. As these energies typically have noise, numerical derivatives of the energy can be challenging to find reliably. In order to circumvent this problem, we use Gaussian process regression to model the energy and use analytical derivatives to produce the specific heat capacity. From there, we also calculate the entropy by numerical integration. We compare our results to cubic splines and finite differences in a variety of molecules in which Hamiltonians can be diagonalized exactly with full configuration interaction. We finally apply this method to look at larger molecules where exact diagonalization is not possible and make comparisons with more approximate ways to calculate the specific heat capacity and entropy.
Despite having advantageous superconducting properties, Nb3Sn superconducting radiofrequency (SRF) cavities still have practical challenges compared to Nb SRF cavities due to the brittle nature of Nb3Sn. Performance degradation can occur when a Nb3Sn SRF cavity experiences mechanical stresses such as during handling and tuning of the cavity. In this study, we present a potential treatment for SRF cavities that have experienced stress induced performance degradation that involves a recoating procedure. The degraded cavity is coated with a small amount of Sn using a single step vapor-diffusion methodology. Using this approach we can recover a significant portion of the lost performance of a Nb3Sn SRF cavity.
The efficiency of the polarisation mechanisms of laser cooling of atoms is analysed using narrow optical transitions for which the recoil energy is greater than or comparable to the natural line width. By the example of atoms with the J{sub g} = 1 → J{sub e} = 2 optical transition (J{sub g} and J{sub e} are the total angular momenta of the ground and excited states) in the resonant light fields of σ{sub +} – σ{sub –} and lin⊥lin configurations, the analysis of the minimum achievable energies of laser-cooled atoms is performed. It is shown that the polarisation mechanisms of laser cooling under conditions of a significant influence of recoil effects become less efficient and do not lead to average kinetic energies of an ensemble of atoms below the Doppler limit. (paper)
Based on the numerical solution of the quantum kinetic equation for the atomic density matrix, which makes it possible to accurately take into account the recoil effects in the interaction of atoms with field photons, we have studied the limits of laser cooling of atoms using closed optical transitions characterised by different recoil parameters (the ratio of the recoil energy to the natural linewidth). It is shown that for optical transitions with an insufficiently small recoil parameter, the polarisation effects, which lead to the possibility of sub-Doppler laser cooling, lose their efficiency and do not ensure an attainment of the temperature below the Doppler limit. The analysis performed allows one to outline the boundaries of the sub-Doppler theory of laser cooling of atoms. (paper)
Significance The loss of ocean oxygen caused by climate warming is a serious environmental issue and could lead to major declines in animal habitats. However, current Earth system models struggle in explaining observed trends in global ocean oxygen. Using a model, we demonstrate that marine oxygen concentrations depend sensitively on a rarely considered quantity known as the respiration quotient to prescribe the oxygen consumed per mole of organic carbon respired. Using a combination of direct chemical measurements across major biomes in the eastern Pacific Ocean plus changes in the global distribution of oxygen and carbon, we show how the respiration quotient increases systematically with temperature. The findings imply that we can experience more intense declines in ocean oxygen with warming.
Significance Increasing evidence suggests that evolutionary processes frequently shape ecological patterns; however, most microbiome studies thus far have focused on only the ecological responses of these communities. By using parallel field experiments and focusing in on a model soil bacterium, we showed that bacterial “species” are differentially adapted to local climates, leading to changes in their composition. Furthermore, we detected strain-level evolution, providing direct evidence that both ecological and evolutionary processes operate on annual timescales. The consideration of eco-evolutionary dynamics may therefore be important to understand the response of soil microbiomes to future environmental change.
The outstanding mechanical and chemical properties of dental enamel emerge from its complex hierarchical architecture. An accurate, detailed multiscale model of the structure and composition of enamel is important for understanding lesion formation in tooth decay (dental caries), enamel development (amelogenesis) and associated pathologies (e.g., amelogenesis imperfecta or molar hypomineralization), and minimally invasive dentistry. Although features at length scales smaller than 100 nm (individual crystallites) and greater than 50 µm (multiple rods) are well understood, competing field of view and sampling considerations have hindered exploration of mesoscale features, i.e., at the level of single enamel rods and the interrod enamel (1 to 10 µm). Here, we combine synchrotron X-ray diffraction at submicrometer resolution, analysis of crystallite orientation distribution, and unsupervised machine learning to show that crystallographic parameters differ between rod head and rod tail/interrod enamel. This variation strongly suggests that crystallites in different microarchitectural domains also differ in their composition. Thus, we use a dilute linear model to predict the concentrations of minority ions in hydroxylapatite (Mg 2+ and CO 3 2- /Na + ) that plausibly explain the observed lattice parameter variations. While differences within samples are highly significant and of similar magnitude, absolute values and the sign of the effect for some crystallographic parameters show interindividual variation that warrants further investigation. In conclusion, by revealing additional complexity at the rod/interrod level of human enamel and leaving open the possibility of modulation across larger length scales, these results inform future investigations into mechanisms governing amelogenesis and introduce another feature to consider when modeling the mechanical and chemical performance of enamel.
The need for energy-efficient recovery of organic solutes from aqueous streams is becoming more urgent as chemical manufacturing transitions toward nonconventional and bio-based feedstocks and processes. In addition to this, many aqueous waste streams contain recalcitrant organic contaminants, such as pharmaceuticals, industrial solvents, and personal care products, that must be removed prior to reuse. We observe that rigid carbon membrane materials can remove and concentrate organic contaminants via an unusual liquid-phase membrane permeation modality. Surprisingly, detailed thermodynamic calculations on the chemical potential of the organic contaminant reveal that the organic species has a higher chemical potential on the permeate side of the membrane than on the feed side of the membrane. This unusual observation challenges conventional membrane transport theory that posits that all permeating species move from high chemical potential states to lower chemical potential states. Based on experimental measurements, we hypothesize that the organic is concentrated in the membrane relative to water via favorable binding interactions between the organic and the carbon membrane. The concentrated organic is then swept through the membrane via the bulk flow of water in a modality known as “sorp-vection.” We highlight via simplified nonequilibrium thermodynamic models that this “uphill” chemical potential permeation of the organic does not result in second-law violations and can be deduced via measurements of the organic and water sorption and diffusion rates into the carbon membrane. Moreover, this work identifies the need to consider such nonidealities when incorporating unique, rigid materials for the separations of aqueous waste streams.
The chemical composition of wood plays a pivotal role in the adaptability and structural integrity of trees. However, few studies have investigated the environmental factors that determine lignin composition and its biological significance in plants. Here, we examined the lignin syringyl-to-guaiacyl (S/G) ratio in members of a Populus trichocarpa population sourced from their native habitat and conducted a genome wide association study to identify genes linked to lignin formation. Our results revealed many significant associations, suggesting that lignin biosynthesis is a complex polygenic trait. Additionally, we found an increase in the S/G ratio from northern to southern geographic origin of the trees sampled, along with a corresponding metabolic and transcriptional reprogramming of xylem cell wall biosynthesis. Further molecular analysis identified a mutation in a cell wall laccase genetically associated with higher S/G ratios that predominate in trees from warmer lower latitudes. Collectively, our findings suggest that lignin heterogeneity arises from an evolutionary process enabling poplar adaptation to different climatic challenges.
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