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Plasmonic semiconductors exhibit significant potential for harvesting near-IR solar energy, although their mechanisms of plasmon-induced hot electron transfer (HET) are poorly understood. We report a transient absorption study of plasmon-induced HET in p-Cu₇S₄/CdS type II heterojunctions. Near-IR excitation of the p-Cu₇S₄ plasmon band at ~1400 nm leads to ultrafast HET into the CdS conduction band with a time constant of <150 fs and a quantum efficiency of ~0.054%. The injected hot electrons remain in CdS with an amplitude-weighted average lifetime of 1.9 ± 0.5 ns, significantly longer than that in Au/CdS heterostructures, suggesting that plasmonic semiconductors can slow down charge recombination due to the presence of a bandgap. The excited near-IR plasmon does not decay by coupling to the interfacial charge transfer transition, likely due to its energy mismatch. This study provides a detailed mechanistic understanding and possible directions for improving plasmonic HET in plasmonic semiconductor heterojunctions.

The responses of South Asian Monsoon (SAM) circulation under global warming are known to be highly uncertain, leading to the wide spread of SAM rainfall projections among models. Here, we show that the uncertain SAM circulation in Coupled Model Intercomparison Project Phase 6 models consists of two robust components that partly offset each other: a weakening component linked to a global thermodynamic constraint and a northward shift component understood through a regional 2D energetic perspective. We further attribute the robust northward shift of SAM circulation to positive cloud feedback over the Eurasia Continent and heat uptake in the Southern Ocean. A set of climate model simulations supports the finding that SAM rainfall increase is primarily due to the northward shift of circulation driven by extratropical processes. This energetic perspective opens new avenues for predicting monsoon rainfall by connecting circulation changes to radiative forcing, feedbacks, and ocean heat uptake.

Monitoring nuclear reactor operations is vital for nuclear safeguards as it ensures that reactors are in compliance with international legal agreements. Validating nuclear facilities and activities, including potential clandestine activities, is currently accomplished by using remotely sensed data from satellites and aircrafts and on-site sampling. However, these techniques are temporally-limited as sampling and interpretation of environmental releases frequently involve labor-intensive, on-site collections. Here, we investigate whether remotely sensed data from eddy-covariance ecosystem monitoring networks, such as AmeriFlux, can be used to detect waste heat generated from four U.S.-based nuclear reactors, two pressurized water reactors (Callaway Nuclear Generating Station and Seabrook Nuclear Power Plant), and two boiling water reactors (Columbia Nuclear Generating Station and Enrico Fermi Nuclear Generating Station). Though both pressurized and boiling water reactors release latent and sensible heat into the environment in a similar way, we evaluated whether different signatures exist among the two types of nuclear facilities. Additionally, we evaluated whether different signatures exist among those reactors that release waste heat into the atmosphere via latent heat or into the ocean via sensible heat. To do this, we used logistic generalized additive models to investigate whether reactor operational status (i.e., on versus off) can be estimated from two environmental heat fluxes, latent and sensible heat. We also evaluated whether wind direction, seasonality and vegetation type influences potential latent and sensible heat signatures from reactors. Using a Dirichlet Process Means clustering analysis, we investigated whether certain weather conditions are more conducive to detecting reactor status. Our results suggest that eddy-covariance towers can detect waste heat flux signatures from nuclear reactors, particularly latent heat. Our results also suggest that weather conditions most conducive to detecting changes in latent and sensible heat as a result of reactor status are present on relatively dry, calm, cloudless days. These results contribute to a growing body of literature utilizing new methodologies in remotely monitoring nuclear reactor operations.

Plasmonic nanoparticles are widely recognized as photothermal conversion agents, i.e., nanotransducers or nanoheaters. Translation of these materials into practical applications requires quantitative analyses of their photothermal conversion efficiencies (η). However, the value of η obtained for different materials is dramatically influenced by the experimental setup and method of calculation. Here, we evaluate the most common methods for estimating η (Roper’s and Wang’s) and compare these with numerical estimates using the simulation software ANSYS. Experiments were performed with colloidal gold nanorod solutions suspended in a hanging droplet irradiated by an 808 nm diode laser and monitored by a thermal camera. The ANSYS simulations accounted for both heating and evaporation, providing η values consistent with the Wang method but higher than the Roper approach. This study details methods for estimating the photothermal efficiency and finds ANSYS to be a robust tool where experimental constraints complicate traditional methods.

Boiling heat transfer plays a crucial role in a wide range of applications, such as power generation, refrigeration, electronics cooling, and pharmaceutics. Among the various factors that influence boiling heat transfer, the dynamics of vapor bubble nucleation, growth, and departure from the heated surface stand out as particularly important. An emerging phenomenon that can promote the departure of bubbles smaller than the Fritz diameter is coalescence-induced departure. If the dynamics of this process are fully understood, then surfaces can be engineered to promote faster bubble departure and substantially increase the performance of boiling heat transfer. Further, this work expands on published results by presenting a detailed numerical analysis of bubble coalescence and departure for a range of initial bubble diameters and size ratios between coalescing bubbles. Analysis of the results is focused on explaining how the release of surface energy and bubble surface dynamics lead to bubble departure, as well as fundamentally distinguishing capillary–inertial jumping and buoyant–inertial departure mechanisms across different bubble sizes and size ratios. The results show that both the initial sizes of the coalescing bubbles and the ratio between their sizes can determine whether the merged bubble will leave the surface through capillary–inertial jumping or buoyant departure. Below a certain bubble size, the release of surface energy by the merger is not sufficient to propel the merged bubble from the surface.

Temperature stress is one of the major limiting environmental factors that negatively impact global crop yields. Kalanchoë fedtschenkoi is an obligate crassulacean acid metabolism (CAM) plant species, exhibiting much higher water-use efficiency and tolerance to drought and heat stresses than C₃ or C₄ plant species. Previous studies on gene expression responses to low- or high-temperature stress have been focused on C₃ and C₄ plants. There is a lack of information about the regulation of gene expression by low and high temperatures in CAM plants. To address this knowledge gap, we performed transcriptome sequencing (RNA-Seq) of leaf and root tissues of K. fedtschenkoi under cold (8 °C), normal (25 °C), and heat (37 °C) conditions at dawn (i.e., 2 h before the light period) and dusk (i.e., 2 h before the dark period). Our analysis revealed differentially expressed genes (DEGs) under cold or heat treatment in comparison to normal conditions in leaf or root tissue at each of the two time points. In particular, DEGs exhibiting either the same or opposite direction of expression change (either up-regulated or down-regulated) under cold and heat treatments were identified. In addition, we analyzed gene co-expression modules regulated by cold or heat treatment, and we performed in-depth analyses of expression regulation by temperature stresses for selected gene categories, including CAM-related genes, genes encoding heat shock factors and heat shock proteins, circadian rhythm genes, and stomatal movement genes. Our study highlights both the common and distinct molecular strategies employed by CAM and C₃/C₄ plants in adapting to extreme temperatures, providing new insights into the molecular mechanisms underlying temperature stress responses in CAM species.

There is a global goal to reduce greenhouse gas emissions by 43% by 2023. Nuclear microreactors, a subset of small modular reactors, offer a potential solution due to their compact size, transportability, and carbon-neutral power generation capabilities. This study explores the feasibility of using heat from nuclear microreactors for bioconversion and agricultural processes, including transforming biomass into energy carriers and products such as syngas, bio-oil, and pasteurized milk. Operating requirements for gasification, pyrolysis, hydrothermal carbonization, hydrothermal liquefaction, hydrothermal gasification, ethanol production, anaerobic digestion, and pasteurization were obtained through a literature review. A Brayton cycle model based on the eVinci^TM microreactor was developed to assess the feasibility of powering these processes using nuclear microreactor heat. Exergetic efficiency values for high-temperature processes ranged from 72% to 100%, whereas lower-temperature processes ranged from 2% to 53%. These efficiencies depend on the available source temperature for each microreactor design. There were trade-offs between producing net power and using process heat, particularly for high-temperature processes. Three heat exchanger locations were considered: before the turbine (600 °C), between the turbine and regenerator (370 °C), and after the regenerator (192 °C). High-temperature processes like gasification require temperatures too high for feasibility. Middle temperature processes are better suited to a heat exchanger between the turbine and regenerator, while also operable before the turbine. Lower-temperature processes like pasteurization and anaerobic digestion can use waste heat after the regenerator and do not impact power production. These findings are valuable for optimizing nuclear microreactor heat use and aligning with global climate initiatives.

Multilayer graphane (hydride of graphite) is a crystalline hydrocarbon of composition CH, which can be synthesized from graphite and molecular hydrogen at pressures above 2GPa [V.E. Antonov et al. Carbon 100 (2016) 465]. Using X-ray diffraction, this compound was tentatively identified as the “graphane II” phase of 3D-graphane predicted by ab initio calculations [X.-D. Wen et al. PNAS 108 (2011) 6833] and consisting of layers of 2D-graphane in the “chair” conformation. When heated in a vacuum, the compound does not form any intermediate hydrocarbons and reversibly decomposes back into graphite and hydrogen at 770–920 K. In the present work, almost single-phase samples of graphite hydride and deuteride were synthesized at 7.4 GPa and 870 K. Their investigation by inelastic neutron scattering supplemented by ab initio calculations gave spectra g(E) of the phonon density of states with a gap of about 15 meV at approx. 100 meV, which is a unique identifier for the chair form of graphane. The equation of state V(P) of the hydride was studied at room temperature and hydrogen pressures up to 53 GPa by synchrotron X-ray diffraction in a diamond anvil cell. Further, the graphane II phase did not react with the surrounding hydrogen and did not undergo any phase transformations upon the compression and after heating to 1500 K at 53GPa. The high thermal and pressure stability of this exotic phase makes it an important part of the C–H system. The obtained g(E) spectra of graphite hydride and deuteride were used to calculate temperature dependences of their heat capacity. Measurements of the heat capacity at temperatures 120–673 K confirmed the good accuracy of these calculations.

Phonon quasi-particles have been monumental in microscopically understanding thermodynamics and transport properties in condensed matter for decades. Phonons have one-to-one correspondence with harmonic eigenstates and their energies are often described by simple independent harmonic oscillator models. Higher order terms in the potential energy lead to interactions among them, resulting in finite lifetimes and frequency shifts, even in perfect crystals. However, increasing evidence including constant volume heat capacity violating the Dulong-Petit law suggests the need for re-evaluation of phonons as having independent harmonic energies. In this work, we explicitly examine inter-mode dependence of phonon energies of a prototypical crystal, silicon, through energy covariance calculations and demonstrate the concerted nature of phonon energies even at 300°K, questioning independent harmonic oscillator assumptions commonly used for phonon energy descriptions of thermodynamics and transport.

The use of inert and redox-active particles for high-temperature energy storage requires the development of components that can efficiently transfer energy to high-pressure working fluids like supercritical carbon dioxide (sCO₂). Dilute flow reactors can enable high working fluid outlet temperatures and minimal parasitic losses compared to moving packed bed and fluidized bed reactors. This research uses both computational and experimental methods to explore the design trade-offs and practical challenges of a novel component for transferring energy from dilute flows of hot, reduced metal oxide (MO_x) particles to sCO₂ in tubes. A discretized thermal resistance network model, which accounts for particle hydrodynamics, multi-mode heat transfer, and reaction equilibrium, guides the design of a prototype device. This device is experimentally tested with a surrogate heat transfer fluids and inert particle temperatures up to 400°C and a heat duty exceeding 1 kW. The data are used to validate the thermal hydraulic sub-models, allowing for the simulation of reacting particle scenarios. Under nominal design conditions, the flow rate of reactive particles is predicted to be 30% lower than that of inert particles for the same energy recovered, with over 70% of the stored particle energy transferred to the sCO₂. Furthermore, these findings can inform the design of more efficient energy recovery reactors for particle-based systems and can be integrated into system-level concentrated solar power models with thermal storage to optimize operating conditions.