Electrical leakage is an inherent problem in solid-oxide fuel and electrolyzer cells, limiting their energy-conversion efficiency. High concentrations of electrons or holes can exacerbate this issue. However, it is largely unclear how the typical high operating temperatures of the systems influence their charge-carrier concentrations. In this work, we use first-principles calculations to examine how lattice vibrations impact electrical conductivity in conventional electrolytes, using $\mathrm{Ba}\mathrm{Zr}\mathrm{O}$${}_3$ as a representative material. Our analysis shows that phonon-induced shifts in the band gap and band edges lead to a dramatic increase in $p$-type carrier concentrations at temperatures above 600 K, compared to models that neglect temperature effects. Additionally, we reveal the importance of oxygen-ion motion on band-edge positions, which makes valence-band-edge shift dominate the band-gap change. Our study provides a protocol for calculating phonon-induced changes in similar oxides, paving the way for interrogating electrical leakage in electrolytes for high-temperature operation.

Because of their rapid ionic diffusion, $\mathrm{Ag}$-based argyrodites have great potential as solid-state electrolytes. The fundamental thermal transport in these materials is important for the overall all-solid-state battery design. Using an accurate ab initio framework and a unified heat-transport theory, we compute both the particle-like (${\kappa }_{\mathrm{p}}$) and the glass-like (${\kappa }_{\mathrm{c}}$) components of the lattice thermal conductivity (${\kappa }_{\mathrm{L}}$) of ${\mathrm{Ag}}_8{\mathrm{Sn}\mathrm{Se}}_6$ in the orthorhombic phase. Despite being a crystal, ${\mathrm{Ag}}_8{\mathrm{Sn}\mathrm{Se}}_6$ exhibits an exceptionally low room-temperature ${\kappa }_{\mathrm{L}}={\kappa }_{\mathrm{p}}+{\kappa }_{\mathrm{c}}$ of 0.274 W/mK, which is nearly temperature independent over the 100–350 K range. This unusual behavior is linked to the lonesome $\mathrm{Ag}$ atoms, which, in this temperature range, exhibit intense vibrations while remaining weakly bonded to the $\mathrm{Sn}$-$\mathrm{Se}$ framework. While their bonding anharmonicity significantly reduces ${\kappa }_{\mathrm{p}}$, the $\mathrm{Ag}$-dominated extended vibrations make ${\kappa }_{\mathrm{c}}$ the primary heat-transfer mode. By unveiling the role of $\mathrm{Ag}$ in the heat transport of ${\mathrm{Ag}}_8{\mathrm{Sn}\mathrm{Se}}_6$, we support the notion that the bonding and structural characteristics responsible for fast ionic conduction can also help identify extreme materials with glass-like thermal transport.

While the dynamics of hydrogen bubbles during water electrolysis have been intensively studied in recent years, adequate insights into the dynamics of oxygen bubbles are still lacking. Therefore, this study presents a comparative analysis of hydrogen and oxygen bubble dynamics during potentiostatic water electrolysis in an acidic electrolyte. Complementary optical techniques, such as high-speed shadowgraphy, particle tracking velocimetry, and schlieren imaging are applied to measure geometric features of the evolving bubbles and the microscale Marangoni convection, as well as the refractive index field around the growing bubbles. Distinct differences between oxygen and hydrogen bubbles are found in the average current, in the Marangoni convection pattern, and in the degree of refractive index reduction at the bubble foot, suggesting a synergetic action of both thermal and solutal effects at oxygen bubbles.

Heusler compounds with six valence electrons per atom have attracted interest as thermoelectric materials owing to their semimetallic and semiconducting properties. Here, we theoretically and experimentally investigate electronic transport in ${\mathrm{Ru}}_2\mathrm{Ti}\mathrm{Si}$-based full-Heuslers. We show that electronic transport in this system can be well captured by a two-parabolic-band model. The larger band gap of ${\mathrm{Ru}}_2\mathrm{Ti}\mathrm{Si}$ promises a higher thermoelectric performance, compared to its isovalent family member ${\mathrm{Fe}}_2\mathrm{V}\mathrm{Al}$, which has been studied as a thermoelectric material for over two decades. Additionally, we identify $p$-type ${\mathrm{Ru}}_2\mathrm{Ti}\mathrm{Si}$ as far more efficient than previously studied $n$-type compounds and demonstrate that this can be traced back to much lighter and more mobile holes originating from dispersive valence bands. Our findings suggest that an exceptionally high dimensionless figure of merit $zT>1$ can be realized in these $p$-type compounds around 700 K upon proper reduction of the lattice thermal conductivity, e.g., by substituting $\mathrm{Zr}$ or $\mathrm{Hf}$ for $\mathrm{Ti}$.

The high-voltage (more than 4.2 V versus graphite) electrochemical degradation of layered nickel-rich lithium 3d transition metal oxide (${\mathrm{Li}\mathrm{Ni}}_x{\mathrm{Mn}}_y{\mathrm{Co}}_{1-x-y}{\mathrm{O}}_2$, where x ≥ 0.6) cathodes currently limits their practical energy densities. The degradation primarily stems from surface oxygen loss and its consequent effects, which leads to rapid capacity fade and voltage hysteresis. Addressing this necessitates not only novel material engineering approaches but also a deeper comprehension of how it leads to performance enhancement. Here, using in-house operando x-ray diffraction studies of $\sim$3.4 mA h/${\mathrm{cm}}^2$ polycrystalline ${\mathrm{Li}\mathrm{Ni}}_{0.8}{\mathrm{Mn}}_{0.1}{\mathrm{Co}}_{0.1}{\mathrm{O}}_2$ (NMC811)-graphite pilot-line-built pouch cells cycled between 3 and 4.4 V, we show that particle atomic layer deposition (ALD) of an aluminum phosphate surface layer on the NMC811 cathode particles suppresses the formation of electrochemically fatigued phases within the cathode bulk, leading to notable performance enhancements. This study contributes to our growing understanding of how scalable ALD processing is essential for stabilizing the high-voltage performance of $\mathrm{Ni}$-rich layered oxide cathodes.

The evolution of the microstructure of materials is primarily governed by defect-mediated diffusion. Here, we examine the intriguing role played by vacancies in tungsten, a strategic metal for high-temperature fusion-energy systems. We address the existing apparent contradictions between experimental observations indicating the presence of voids and theoretical predictions of vacancy self-repulsion by employing both experimental and theoretical methods. We have designed a transmission-electron-microscopy experiment and developed a theoretical data-driven approach using the Bayesian adaptive biasing force method to investigate the finite-temperature properties of mono- and di-vacancies and characterize their relative stability via their formation free energies. Our investigation reveals that di-vacancies are energetically unfavorable at low temperatures but stabilize entropically as the temperature increases. This result is entirely consistent with experimental observations of the clustering of quenched-in vacancies in tungsten during reannealing treatments at intermediate temperatures. This work provides critical insights into the temperature-dependent stability of defects, bridging the gap between theoretical predictions and experimental observations, with significant implications for the design and optimization of high-temperature materials for fusion.

We describe and analyze a new class of direct energy conversion schemes based on the adiabatic magnetic drift of charged particles in axisymmetric magnetic fields. The efficiency of conversion as well as the geometrical and dynamical limitations of the recoverable power are calculated. The geometries of these axisymmetric field configurations are suited for direct energy conversion in radiating advanced aneutronic reactors and in advanced divertors of deuterium-tritium tokamak reactors. The $\mathbf{E}\times \mathbf{B}$ configurations considered here do not suffer from the classical drawbacks and limitations of thermionic and magnetohydrodynamic high-temperature direct energy conversion devices.

Functional thin films play a critical role in efforts toward efficient devices for energy conversion and storage, as well as low-loss electronics. These films need to be manufactured at scale, cost-effectively, and with precision. Atmospheric pressure spatial atomic layer deposition (AP-SALD) has emerged as a promising technique for fulfilling these requirements. AP-SALD replicates the subnanometer control of thickness, uniformity, crystallinity, and conformality to the substrate featured in conventional atomic-layer-deposited films, but has the important advantage of depositing these films with growth rates that are orders of magnitude higher. This review discusses the opportunities and advantages that AP-SALD opens up in energy-conversion and storage devices, as well as low-loss electronics. In particular, the review features recent work on using AP-SALD-grown films for photovoltaics, light-emitting diodes, self-powered sensors, and photoelectrochemical cells and batteries, as well as in transparent conductive materials and the epitaxial growth of thin films. Perspectives on future unexplored opportunities for AP-SALD in energy and low-loss electronics are also discussed.

Predicting radiation damage to materials requires estimating the threshold displacement energy ($E_d$). We calculate $E_d$ using ab initio molecular dynamics for the lead halide perovskites MA$\mathrm{Pb}\mathrm{I}$${}_3$, FA$\mathrm{Pb}\mathrm{I}$${}_3$, and $\mathrm{Cs}\mathrm{Pb}\mathrm{I}$${}_3$. The $E_d$ values that we obtain, which are considerably lower than those commonly assumed in the literature for several species, hold significant implications for predicting radiation damage to materials. We perform Monte Carlo simulations with the ab initio molecular dynamics (AIMD) obtained $E_d$ and compare them to simulations using the default $E_d$. Our results show an increase in specific vacancies in halide perovskites that is not captured in simulations using the default $E_d$ values. This suggests that the default $E_d$ values may not accurately predict the radiation damage in these materials, potentially leading to underestimation of the damage. These results are discussed in the context of the radiation hardness of the materials and suggest that they get damaged when exposed to radiation, but they are resilient due to self-healing processes.

Calculation of ionic conductivity including ion-ion correlation effects using equilibrium molecular dynamics (EMD) is computationally demanding, but the correlation is significant in many promising electrolytes such as solid electrolytes. Herein, we have developed a “constant-current” nonequilibrium MD (NEMD) simulation method, in contrast to the conventional constant-field approach, for ion-ion correlated conductivities from a constrained ionic current with fluctuating external field. The improved efficiency of the constant-current NEMD approach is demonstrated by applying it to a representative solid electrolyte, cubic ${\mathrm{Li}}_7{\mathrm{La}}_3{\mathrm{Zr}}_2{\mathrm{O}}_{12}$. The convergence of the correlated conductivity is faster than that of EMD by 2 orders of magnitude. The low-temperature NEMD simulations also reveal that the ionic conductivity of ${\mathrm{Li}}_7{\mathrm{La}}_3{\mathrm{Zr}}_2{\mathrm{O}}_{12}$ exhibits non-Arrhenius behavior of the activation energy that changes at around 600 K. This work presents not only the high sampling efficiency of constant-current NEMD to calculate the correlated ionic conductivity, but also the importance of direct computations of ionic conductivity at low temperature without Arrhenius extrapolation.

Bose-Einstein condensation of excitons, with its potential for frictionless energy transport, has recently been observed in materials at low temperatures. Here, we show that partial exciton condensation plays a significant role in the 18-chromophore B850 ring of the light-harvesting complex 2 (LH2) in purple bacteria. Even in the single-excitation regime, we observe that excitonic entanglement across multiple sites exhibits signatures of exciton condensation in the particle-hole reduced density matrix—a partial exciton condensate. Crucially, we find that, by distributing the exciton across multiple sites of the ring, the exciton-condensate-like state sets favorable conditions for enhanced energy transfer, both before and after decoherence. Surprisingly, this discovery reveals that excitonic condensation, previously thought to require extreme conditions, can occur in a partial form in biological systems under ambient conditions, providing new insight into energy transport. These results additionally bring new insight into the long-standing debate on quantum versus classical mechanisms in photosynthetic light harvesting by showing that quantum coherence, in the form of a partial exciton condensate, indirectly initializes subsequent classical transfer. Our findings not only deepen our understanding of quantum coherence in light harvesting but also suggest design principles for materials capable of leveraging excitonic entanglement for efficient energy transport.

The ever-increasing complexity of modern power grids makes them vulnerable to cyber and/or physical attacks. To protect them, accurate attack detection is essential. A challenging scenario is that a localized attack has occurred on a specific transmission line but only a small number of transmission lines elsewhere can be monitored. That is, full state observation of the whole power grid is not feasible, so attack detection and state estimation need to be done with only limited, partial state observations. We articulate a machine-learning framework to address this problem, where the necessity to deal with sequential time-series data with dynamical memories and to avoid a vanishing gradient has led us to choose the long short-term memory (LSTM) architecture. Leveraging the inherent capabilities of LSTM to handle sequential data and capture temporal dependencies, we demonstrate, using three benchmark power-grid networks, that the complete dynamical state of the whole power grid can be faithfully reconstructed and the attack can be accurately localized from limited, partial state observations even in the presence of noise. The performance improves as more observations become available. Further justification for using the LSTM is provided by our comparing its performance with that of alternative machine-learning architectures such as feedforward neural networks and random forest. Despite the gigantic existing literature on applications of LSTM to power grids, to our knowledge, the problem of locating an attack and estimating the state from limited observations had not been addressed before our work. The method developed can potentially be generalized to broad complex cyber-physical systems.

Muon tomography is a consolidated technique to investigate the internal components of high-opacity objects. With the use of detectors with high angular and spatial resolution (usually referred to as “muon telescopes”), the track reconstruction of the atmospheric muons after they have crossed the object provides muography images, also called “muon radiographs.” This work presents the muography (or muon radiography) reconstruction of a French historical UNGG (natural-uranium, graphite, and gas) nuclear reactor: the G3 reactor, located at CEA Marcoule. A measurement campaign involving 46 points of view below the reactor was conducted, providing a set of muography images. The method to analyze these muographies is detailed here. Besides, a method to combine these images to provide three-dimensional (2D) tomography of the reactor is also presented. After a general description of the project, all the methods performed to reconstruct and analyze muographies and the 3D reconstruction are presented. It comprises different tools based on data augmentation and machine learning, which proved to be very efficient on simulated data and increase the quality of the experimental data analysis. All these methods were evaluated with a set of synthetic data, providing a precise evaluation for better identification of the associated systematics. Finally, all the described methods were applied to the experimental data, leading to a full characterization of the reactor, in both two dimensions and three dimensions, and the identification of some discrepancies between the reactor actual structure and the original model. These anomalies are discussed, showing the potential of the technique to evaluate the internal structure of a nuclear reactor. This could have potential applications during the decommissioning phase and the dismantling phase of different kinds of nuclear installation.

Novel carbon dioxide removal (CDR) technologies are increasingly being considered as potentially useful tools to combat climate change. For specific atmospheric carbon dioxide management targets to be achieved, large-scale CDR strategies may be needed, even with aggressive efforts to reduce carbon dioxide emissions in the coming decades. This American Physical Society report breaks down the physical requirements necessary for large-scale implementation of CDR technologies, demonstrating the challenges inherent to incorporating CDR into any carbon dioxide management portfolio. It also provides a technical overview of new and current CDR approaches and evaluates their fundamental physical constraints. Based on the technical overview, the report makes several recommendations for the U.S. federal government and industry. These include ensuring that the potential for CDR does not compromise ongoing actions to reduce carbon emissions. The report observes, however, that while large-scale CDR technologies require a lot of energy and material resources, they might be needed in combination with emission reduction strategies to achieve specific climate goals. Research and development on CDR should be selectively pursued, despite the many challenges described in the report.

In this work, we demonstrate that time-resolved photoluminescence data of metal halide perovskites can be effectively evaluated by combining Bayesian inference with a Markov-chain Monte-Carlo algorithm and a physical model. This approach enables us to infer a high number of parameters that govern the performance of metal halide perovskite-based devices, alongside the probability distributions of those parameters, as well as correlations among all parameters. Via studying a set of halfstacks, comprising electron- and hole-transport materials contacting perovskite thin films, we determine surface recombination velocities at these interfaces with high precision. From the probability distributions of all inferred parameters, we can simulate intensity-dependent photoluminescence quantum efficiency and compare it to experimental data. Finally, we estimate mobility values for vertical charge-carrier transport, which is perpendicular to the plane of the substrate, for all samples using our approach. Since this mobility estimation is derived from charge-carrier diffusion over the length scale of the film thickness and in the vertical direction, it is highly relevant for transport in photovoltaic and light-emitting devices. Our approach of coupling spectroscopic measurements with advanced computational analysis will help speed up scientific research in the field of optoelectronic materials and devices and exemplifies how carefully constructed computational algorithms can derive valuable plurality of information from simple datasets. We expect that our approach can be expanded to a variety of other analysis techniques and that our method will be applicable to other semiconductors.

Metals have high electronic conductivities, but very low Seebeck coefficients, which traditionally make them unsuitable for thermoelectric materials. Recent studies, however, showed that metals could deliver ultrahigh thermoelectric power factors (PFs) under certain conditions. In this work, we theoretically examine the electronic structure and electronic transport specifications that allow for such high PFs. Using Boltzmann transport equation (BTE) simulations and a multiband electronic structure model, we show that metals with (i) a high degree of transport asymmetry between their bands, (ii) strong interband scattering, and (iii) a large degree of band overlap, can provide ultrahigh power factors. We show that each of these characteristics adds to the steepness of the transport distribution function of the BTE, which allows for an increase of the Seebeck coefficient to sizable values, simultaneously with an increase in the electrical conductivity. This work generalizes the concept that transport asymmetry (i.e., a mixture of energy regions of high and low contributions to the electrical conductivity), through a combination of different band masses, scattering strengths, energy filtering scenarios, etc., can indeed result in very high thermoelectric power factors, even in the absence of a material band gap. Under certain conditions, transport asymmetry can overcompensate for any performance degradation to the PF due to bipolar conduction and the naturally low Seebeck coefficients that otherwise exist in this class of materials.

With a record efficiency of 23.64% achieved in the past year, $\mathrm{Cu}$($\mathrm{In}$,$\mathrm{Ga}$)$\mathrm{Se}$${}_2$ chalcopyrites are the absorbers of choice for thin-film solar cells. In these devices, the $p$-type chalcopyrite absorber and the $n$-type window layer form the $p$-$n$ junction at the interface, which is mediated by a thin buffer layer. Due to its close proximity to the $p$-$n$ junction, the defect electronic properties of the absorber surface and its interface with the buffer layer are of significant importance to limit recombination losses of photogenerated carriers. Furthermore, the recent surge in the efficiency gains have been achieved with the aid of heavy alkali-metal elements, which are implemented via a postdeposition treatment of the absorber surface. Due to the complex defect physics of chalcopyrite materials, the effects and involved processes of these alkali-metal treatments are so far not well understood. As a fundamental requirement, understanding the intrinsic defect physics of chalcopyrite absorbers and how it is influenced by various surface treatments is of significant importance. In fact, it can provide a basis to develop knowledge-based strategies to reduce recombination losses due to the presence of electronic defect levels in the vicinity of the $p$-$n$ junction. To experimentally access such defects at the surface, it is essential that the chosen characterization techniques possess high surface sensitivity. Furthermore, due to the pronounced crystallographic lateral inhomogeneities of the polycrystalline chalcopyrite thin films, a high spatial resolution is desirable. A combined analytical approach using scanning probe microscopy and spectroscopy or Kelvin force microscopy and photoelectron spectroscopy methods can provide valuable insights. Despite the extensive literature available on related topics, a consolidated view of the various findings made in this regard and the direct consequences for the device efficiency is still lacking. Our review addresses the significant progress made in understanding the defect electronic properties of the chalcopyrite surface in the past decade. The findings are consolidated into five sections, which illuminate several external sources of electronic defects and surface-passivation procedures. This allows to develop specific strategies to reduce interface recombination losses for device optimization and improved solar-cell efficiencies.

Prevalent electrolyte effects across a wide range of electrocatalytic reactions underscore the general importance of the local reaction conditions in the electrical double layer (EDL). Compared to traditional EDLs, the electrocatalytic siblings feature partially charged chemisorbates that could blur our long-held views of surface charge densities and differential capacitances—two interrelated quantities shaping the crucial local reaction conditions. Herein, five variants of surface charge density and three variants of differential capacitance in the presence of chemisorbates are defined and compared. A semiclassical model of electrocatalytic EDLs is developed for a quantitative analysis of the differences and interrelationships between these variants of surface charge densities and differential capacitances. It is revealed that the potential- and concentration-dependent net charge on these chemisorbates dramatically changes the surface charge densities and differential capacitances. Specifically, the free surface charge density could decrease as the electrode potential becomes more positive, implying that the corresponding differential capacitance is negative. The relationship between the free and total surface charge densities is analyzed with aid of the concept of electrosorption valency. By linking the electrosorption valency with the differential capacitance in the absence of chemisorbates, we explain the potential and concentration dependence of the former. The conceptual analysis presented in this work has important implications for experimental characterization and first-principles-based atomistic simulations of electrocatalysis and EDL effects. Particularly, we disclose a hidden yet potentially crucial disadvantage of widely employed atomistic simulation models that fix the coverage of chemisorbates. Proposing the self-consistent implicit model as an expedient remedy for this disadvantage, this work contributes to more realistic modeling of electrocatalytic EDLs.

Materials with axis-dependent conduction polarity are known as $p\times n$-type or goniopolar conductors that can be used for transverse thermoelectric devices, allowing the longitudinal thermal current to be converted into the transverse electrical current. Here, we have performed experimental and computational studies on the transport properties of $\mathrm{WSi}$${}_2$ single crystals, in which such axis-dependent conduction polarity of the thermopower and the Hall coefficient have recently been reported, and demonstrated the transverse thermoelectric effect by applying the temperature gradient in a direction rotated ${45}^{\circ }$ from the crystallographic axis. We have observed strongly sample-dependent transport properties, which have also been observed in previous studies, and together with first-principles calculations we show that such sample-dependent transport properties originate from the band-dependent scattering rates of carriers. The calculated band-resolved Peltier conductivity shows that the mixed-dimensional electronic structure consisting of a quasi-one-dimensional electron Fermi surface and a quasi-two-dimensional hole surface is a key property for the axis-dependent conduction polarity. The directly obtained transverse thermoelectric figure of merit is comparable to that of the anomalous Nernst materials, implying that the present material is a potential candidate for transverse thermoelectric conversion.