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Austenitic stainless steels are used for core internal structures in sodium-cooled fast reactors (SFRs) and light-water reactors (LWRs) because of their high strength and retained toughness after irradiation (up to 80 dpa in LWRs), unlike ferritic steels that are embrittled at low doses (<1 dpa). For fast reactors, operating temperatures vary from 400 to 550 °C for the internal structures and up to 650 °C for the fuel cladding. The internal structures of the LWRs operate at temperatures between approximately 270 and 320 °C although some parts can be hotter (more than 400 °C) because of localised nuclear heating. The ongoing operability relies on being able to understand and predict how the mechanical properties and dimensional stability change over extended periods of operation. Test reactor irradiations and power reactor operating experience over more than 50 years has resulted in the accumulation of a large amount of data from which one can assess the effects of irradiation on the properties of austenitic stainless steels. The effect of irradiation on the intrinsic mechanical properties (strength, ductility, toughness, etc.) and dimensional stability derived from in- and out-reactor (post-irradiation) measurements and tests will be described and discussed. The main observations will be assessed using radiation damage and gas production models. Rate theory models will be used to show how the microstructural changes during irradiation affect mechanical properties and dimensional stability.

Soil heterotrophic respiration is strongly controlled by temperature. Thus, understanding how soil microbial respiration will acclimate to global warming is important for accurate predictions of soil carbon loss. Thermal acclimation of soil respiration has typically been measured using the Q₁₀ temperature coefficient or comparing absolute rates of respiration with varying conclusions. Discrepancies in these findings may be a result of these approaches not accounting for the temperature optima associated with microbial respiration. To address this issue, we periodically measured the temperature response of respiration for soils incubated at 4, 10, 20, and 35 °C for up to 310 days. We measured respiration rates from these soils placed in a temperature block for 5 h at ~ 1 °C increments with temperatures ranging from ~ 4 to 50 °C. To assess thermal acclimation, we used macromolecular rate theory to calculate the temperature optimum (T opt), the inflection point of the curve (T inf), and the change in heat capacity of the transition state ( Δ C P ‡ ), as a measure of the temperature response. We compared changes in T opt, T inf, and Δ C P ‡ over time between each of the long-term incubation temperatures. We found that T opt and T inf increased and Δ C P ‡ decreased at higher long-term incubation temperatures after approximately six months. However, these results appear largely driven by changes in carbon availability, suggesting that the temperature response of soil microbial respiration changes only as soil carbon depletes. This novel approach offers a new perspective on how soil microbial communities may acclimate to climate change and may be relevant for modelling of soil carbon losses.

Accurate description of temperature response and sensitivity of different carbon pools within soil is critical for accurately modelling soil carbon stocks and changes. Inconsistent sampling, incubation and fractionation methods highlights the need for new approaches to this area of study. We developed and tested a new protocol which allowed measurement of the temperature response of two carbon pools within soil. A Horotiu silt loam soil, wet up to 60% maximum water holding capacity, was mixed with ¹³C-enriched plant litter and incubated for 5 or 20 h, at 30 discrete temperatures (~ 2–50 °C). A mixing model was used to separate respired CO₂ into litter and soil organic matter sourced carbon pools, which were then fitted using macromolecular rate theory. Overall, litter sourced respiration had a low Topt (the temperature where respiration rate is maximal) and was less temperature sensitive (Q₁₀) than soil organic matter sourced respiration, which was more Arrhenius-like. We attribute these differences in temperature parameters to the factors that control the availability of carbon to microbes from the labile litter (enzyme kinetics with a clear temperature optimum) compared to the relatively stable soil organic matter (desorption and diffusion that exhibit Arrhenius behaviour). The developed method is rapid and reliable and may be suited to exploring temperature response of a variety of ¹³C-labelled pools in soil and more clearly demonstrates that labile carbon has very different temperature response than more stable carbon pools in soil.

When data availability is limited, the prediction of properties through purely data-driven machine learning (ML) is challenging. Integrating physically-based modeling techniques into ML methods may lead to better performance. In a recent work by Chew et al. (“ Advancing material property prediction: using physics-informed machine learning models for viscosity ”) descriptors from classical molecular dynamics (MD) simulations were included into a quantitative structure–property relationship to accurately predict temperature-dependent viscosity of pure liquids. Through feature importance analysis, the authors found that heat of vaporization was the most relevant descriptor for the prediction of viscosity. In this comment, we would like to discuss the physical origin of this finding by referring to Eyring’s rate theory, and develop an alternative modeling approach using a thermodynamic-based architecture that requires less input data.

Plant leaf respiration is one of the critical components of the carbon cycle in terrestrial ecosystems. To predict changes of carbon emissions from leaves to the atmosphere under a warming climate, it is, therefore, important to understand the thermodynamics of the temperature response of leaf respiration. In this study, we measured the short-term temperature response of leaf respiration from five different urban tree species in a subtropical region of southern China. We applied two models, including an empirical model (the Kavanau model) and a mechanistic model (Macromolecular Rate Theory, MMRT), to investigate the thermodynamic properties in different plant species. Both models are equivalent in fitting measurements of the temperature response of leaf respiration with no significant difference ( p = 0.67) in model efficiency, while MMRT provides an easy way to determine the thermodynamic properties, i.e., enthalpy, entropy, and Gibbs free energy of activation, for plant respiration. We found a conserved temperature response in the five studied plant species, showing no difference in thermodynamic properties and the relative temperature sensitivity for different species at low temperatures (<42°C). However, divergent temperature response among species happened at high temperatures over 42°C, showing more than two-fold differences in relative respiration rate compared to that below 42°C, although the causes of the divergent temperature response remain unclear. Notably, the convergent temperature response at low temperatures could provide useful information for land surface models to improve predictions of climate change effects on plant respiration.

It is shown that the empirical pseudo-second order kinetic equation is a very efficient formula to correlate the kinetic data generated by applying theoretical expressions developed from the fundamental SRT (Statistical Rate Theory) approach to the interfacial transport. This is especially true when the most popular linear representation is used in which time/adsorbed amount is plotted vs. time. However, the commonly observed goodness of such linear plots does not necessarily speak for the applicability of the pseudo-second order kinetic equation. A reliable estimation, for instance, of the equilibrium adsorbed amount is possible only when a substantial part of a kinetic isotherms corresponds to the conditions close to equilibrium. Energetic surface heterogeneity increases the goodness of these linear regressions. Then, experimental errors have only little effect on the pseudo-second linear plots.

We describe a new approach to incorporating quantum effects into chemical reaction rate theory using quantum trajectories. Our development is based on the entangled trajectory molecular dynamics method for simulating quantum processes using trajectory integration and ensemble averaging. By making dynamical approximations similar to those underlying classical transition state theory, quantum corrections are incorporated analytically into the quantum rate expression. We focus on a simple model of quantum decay in a metastable system and consider the deep tunneling limit where the classical rate vanishes and the process is entirely quantum mechanical. We compare our approximate estimate with the well-known WKB tunneling rate and find qualitative agreement.

This article surveys the empirical information which originated both by laboratory experiments and by computational simulations, and expands previous understanding of the rates of chemical processes in the low-temperature range, where deviations from linearity of Arrhenius plots were revealed. The phenomenological two-parameter Arrhenius equation requires improvement for applications where interpolation or extrapolations are demanded in various areas of modern science. Based on Tolman's theorem, the dependence of the reciprocal of the apparent activation energy as a function of reciprocal absolute temperature permits the introduction of a deviation parameter d covering uniformly a variety of rate processes, from those where quantum mechanical tunnelling is significant and d < 0, to those where d > 0, corresponding to the Pareto–Tsallis statistical weights: these generalize the Boltzmann–Gibbs weight, which is recovered for d = 0. It is shown here how the weights arise, relaxing the thermodynamic equilibrium limit, either for a binomial distribution if d > 0 or for a negative binomial distribution if d < 0, formally corresponding to Fermion-like or Boson-like statistics, respectively. The current status of the phenomenology is illustrated emphasizing case studies; specifically (i) the super-Arrhenius kinetics, where transport phenomena accelerate processes as the temperature increases; (ii) the sub-Arrhenius kinetics, where quantum mechanical tunnelling propitiates low-temperature reactivity; (iii) the anti-Arrhenius kinetics, where processes with no energetic obstacles are rate-limited by molecular reorientation requirements. Particular attention is given for case (i) to the treatment of diffusion and viscosity, for case (ii) to formulation of a transition rate theory for chemical kinetics including quantum mechanical tunnelling, and for case (iii) to the stereodirectional specificity of the dynamics of reactions strongly hindered by the increase of temperature. This article is part of the themed issue ‘Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces’.

Temperature observations of the upper-air atmosphere are now available for more than 40 years from both ground- and satellite-based observing systems. Recent years have seen substantial improvements in reducing long-standing discrepancies among datasets throughmajor reprocessing efforts. The advent of radio occultation (RO) observations in 2001 has led to further improvements in vertically resolved temperature measurements, enabling a detailed analysis of upper-troposphere/lower-stratosphere trends. This paper presents the current state of atmospheric temperature trends from the latest available observational records. We analyze observations from merged operational satellite measurements, radiosondes, lidars, and RO, spanning a vertical range fromthe lower troposphere to the upper stratosphere. The focus is on assessing climate trends and on identifying the degree of consistency among the observational systems. The results showa robust cooling of the stratosphere of about 1–3 K, and a robust warming of the troposphere of about 0.6–0.8K over the last four decades (1979–2018). Consistent results are found between the satellite-based layer-average temperatures and vertically resolved radiosonde records. The overall latitude–altitude trend patterns are consistent between RO and radiosonde records. Significant warming of the troposphere is evident in the RO measurements available after 2001, with trends of 0.25–0.35K per decade. Amplified warming in the tropical upper-troposphere compared to surface trends for 2002–18 is found based on ROand radiosonde records, in approximate agreement withmoist adiabatic lapse rate theory. The consistency of trend results from the latest upper-air datasets will help to improve understanding of climate changes and their drivers.

Aim The ‘rate‐of‐living’ theory predicts that life expectancy is a negative function of the rates at which organisms metabolize. According to this theory, factors that accelerate metabolic rates, such as high body temperature and active foraging, lead to organismic ‘wear‐out’. This process reduces life span through an accumulation of biochemical errors and the build‐up of toxic metabolic by‐products. Although the rate‐of‐living theory is a keystone underlying our understanding of life‐history trade‐offs, its validity has been recently questioned. The rate‐of‐living theory has never been tested on a global scale in a phylogenetic framework, or across both endotherms and ectotherms. Here, we test several of its fundamental predictions across the tetrapod tree of life. Location Global. Time period Present. Major taxa studied Land vertebrates. Methods Using a dataset spanning the life span data of 4,100 land vertebrate species (2,214 endotherms, 1,886 ectotherms), we performed the most comprehensive test to date of the fundamental predictions underlying the rate‐of‐living theory. We investigated how metabolic rates, and a range of factors generally perceived to be strongly associated with them, relate to longevity. Results Our findings did not support the predictions of the rate‐of‐living theory. Basal and field metabolic rates, seasonality, and activity times, as well as reptile body temperatures and foraging ecology, were found to be unrelated to longevity. In contrast, lower longevity across ectotherm species was associated with high environmental temperatures. Main conclusions We conclude that the rate‐of‐living theory does not hold true for terrestrial vertebrates, and suggest that life expectancy is driven by selection arising from extrinsic mortality factors. A simple link between metabolic rates, oxidative damage and life span is not supported. Importantly, our findings highlight the potential for rapid warming, resulting from the current increase in global temperatures, to drive accelerated rates of senescence in ectotherms.