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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Aside from the immediate, visible damage, extreme weather events have a longer lasting impact on PV systems. Here, NREL's Dirk C. Jordan, Kirsten Perry, Robert White, Josh Parker, Byron McDanold and Chris Deline report on research revealing the long-term consequences of hail, wind and other weather phenomena on PV production
Abstract The work function is the key surface property that determines the energy required to extract an electron from the surface of a material. This property is crucial for thermionic energy conversion, band alignment in heterostructures, and electron emission devices. This work presents a high‐throughput workflow using density functional theory (DFT) to calculate the work function and cleavage energy of 33,631 slabs (58,332 work functions) that are created from 3,716 bulk materials. The number of calculated surface properties surpasses the previously largest database by a factor of ≈27. Several surfaces with an ultra‐low (<2 eV) and ultra‐high (>7 eV) work function are identified. Specifically, the (100)‐Ba‐O surface of BaMoO 3 and the (001)‐F surface of Ag 2 F have record‐low (1.25 eV) and record‐high (9.06 eV) steady‐state work functions. Based on this database a physics‐based approach to featurize surfaces is utilized to predict the work function. The random forest model achieves a test mean absolute error (MAE) of 0.09 eV, comparable to the accuracy of DFT. This surrogate model enables rapid predictions of the work function (≈ 10 5 faster than DFT) across a vast chemical space and facilitates the discovery of material surfaces with extreme work functions for energy conversion and electronic device applications.
Newly discovered 2D Janus transition metal dichalcogenides layers have gained much attention from a theory perspective owing to their unique atomic structure and exotic materials properties, but little to no experimental data are available on these materials. Here, experimental and theoretical studies establish the vibrational and optical behavior of 2D Janus S–W–Se and S–Mo–Se monolayers under high pressures for the first time. Chemical vapor deposition (CVD)-grown classical transition metal dichalcogenides (TMD) monolayers are first transferred onto van der Waals (vdW) mica substrates and converted to 2D Janus sheets by surface plasma technique, and then integrated into a 500 µm size diamond anvil cell for high-pressure studies. Overall, the results show that 2D Janus layers do not undergo phase transition up to 15 GPa, and in this pressure regime, their vibrational modes exhibit a nonmonotonic response to the applied pressures (dω/dP). Interestingly, these 2D Janus monolayers exhibit unique blueshift in photoluminescence (PL) upon compression, which is in contrast to many other traditional semiconductor materials. Overall theoretical simulations offer in-depth insights and reveal that the overall optical response is a result of competition between the ab-plane (blueshift) and c-axis (redshift) compression. The overall findings shed the very first light on how 2D Janus monolayers respond under extreme pressures and expand the fundamental understanding of these materials.
A nanoscale hierarchical dual-phase structure is reported to form in a nanocrystalline NiFeCoCrCu high-entropy-alloy (HEA) film via ion irradiation. Under the extreme energy deposition and consequent thermal energy dissipation induced by energetic particles, a fundamentally new phenomenon is revealed, in which the original single-phase face-centered-cubic (FCC) structure partially transforms into alternating nanometer layers of a body-centered-cubic (BCC) structure. The orientation relationship follows the Nishiyama–Wasser-man relationship, that is, (011) BCC || (1¯1¯1) FCC and [100] BCC || [11¯0] FCC . Simulation results indicate that Cr, as a BCC stabilizing element, exhibits a tendency to segregate to the stacking faults (SFs). Furthermore, the high densities of SFs and twin boundaries in each nanocrystalline grain serve to accelerate the nucleation and growth of the BCC phase during irradiation. By adjusting the irradiation parameters, desired thicknesses of the FCC and BCC phases in the laminates can be achieved. Finally, this work demonstrates the controlled formation of an attractive dual-phase nanolaminate structure under ion irradiation and provides a strategy for designing new derivate structures of HEAs.
Abstract Boiling is an effective energy‐transfer process with substantial utility in energy applications. Boiling performance is described mainly by the heat‐transfer coefficient (HTC) and critical heat flux (CHF). Recent efforts for the simultaneous enhancement of HTC and CHF have been limited by an intrinsic trade‐off between them—HTC enhancement requires high nucleation‐site density, which can increase bubble coalescence resulting in limited CHF enhancement. In this work, this trade‐off is overcome by designing three‐tier hierarchical structures. The bubble coalescence is minimized to enhance the CHF by defining nucleation sites with microcavities interspersed within hemi‐wicking structures. Meanwhile, the reduced nucleation‐site density is compensated for by incorporating nanostructures that promote evaporation for HTC enhancement. The hierarchical structures demonstrate the simultaneous enhancement of HTC and CHF up to 389% and 138%, respectively, compared to a smooth surface. This extreme boiling performance can lead to significant energy savings in a variety of boiling applications.
Abstract Hygroscopic hydrogels are emerging as scalable and low‐cost sorbents for atmospheric water harvesting, dehumidification, passive cooling, and thermal energy storage. However, devices using these materials still exhibit insufficient performance, partly due to the limited water vapor uptake of the hydrogels. Here, the swelling dynamics of hydrogels in aqueous lithiumchloride solutions, the implications on hydrogel salt loading, and the resulting vapor uptake of the synthesized hydrogel–salt composites are characterized. By tuning the salt concentration of the swelling solutions and the cross‐linking properties of the gels, hygroscopic hydrogels with extremely high salt loadings are synthesized, which enable unprecedented water uptakes of 1.79 and 3.86 gg −1 at relative humidity (RH) of 30% and 70%, respectively. At 30% RH, this exceeds previously reported water uptakes of metal–organic frameworks by over 100% and of hydrogels by 15%, bringing the uptake within 93% of the fundamental limit of hygroscopic salts while avoiding leakage problems common in salt solutions. By modeling the salt‐vapor equilibria, the maximum leakage‐free RH is elucidated as a function of hydrogel uptake and swelling ratio. These insights guide the design of hydrogels with exceptional hygroscopicity that enable sorption‐based devices to tackle water scarcity and the global energy crisis.
Symmetry breaking plays a crucial role in understanding the fundamental physics underlying numerous physical phenomena, including the electromagnetic response in resonators, giving rise to intriguing effects such as directional light scattering, supercavity lasing, and topologically protected states. Here, this work demonstrates that adding a small fraction of lossy metal (as low as 1 × 10 −6 in volume) to a lossless dielectric resonator breaks inversion symmetry (IS), thereby lifting its degeneracy, leading to a strong bianisotropic response. In the case of the metasurface composed of such resonators, this effect leads to unidirectional perfect absorption while maintaining nearly perfect reflection from the opposite direction. It has developed more general Onsager‐Casimir relations for the polarizabilities of particle arrays, taking into account the contributions of quadrupoles, which shows that bianisotropy is not solely due to dipoles, but also involves high‐order multipoles. The experimental validation demonstrates an extremely thin terahertz‐perfect absorber with a wavelength‐to‐thickness ratio of up to 25,000, where the material thickness is only 2% of the theoretical minimum thickness dictated by the fundamental limit. The findings can pave a new route to design devices for applications involving optical‐to‐heat conversion processes.
Abstract Thin layered mats comprised of an interconnected meandering network of multiwall carbon nanotubes (MWCNT) are subjected to a hypersonic micro‐projectile impact test. The mat morphology is highly compliant and while this leads to rather modest quasi‐static mechanical properties, at the extreme strain rates and large strains resulting from ballistic impact, the MWCNT structure has the ability to reconfigure resulting in extraordinary kinetic energy (KE) absorption. The KE of the projectile is dissipated via frictional interactions, adiabatic heating, tube stretching, and ultimately fracture of taut tubes and the newly formed fibrils. The energy absorbed per unit mass of the film can range from 7–12 MJ kg −1 , much greater than any other material.
As the battery industry shifts toward high Ni content cathodes, such as LiNi 0.8 Mn 0.1 Co 0.1 O 2 [NMC811], a complete understanding of the degradation mechanisms of NMC811 under extreme fast charging (XFC) (XFC, ≤10–15 min charging) conditions is needed. Such comprehensive understanding would identify the most critical materials gaps that need to be addressed for enabling XFC long-life cells for electric vehicles. This study maps out the key aging mechanisms for NMC811 cycled at different XFC conditions (between 1C and 9C) for up to 1000 cycles. To acquire a fundamental understanding of utilization and degradation, cells are evaluated using a range of electrochemical techniques, and multimodal and multiscale microscopy techniques to quantify chemical, structural, and crystallographic degradation as a function of cycling conditions for the NMC cathode. When comparing NMC811 to NMC532, it is observed that NMC811 has a greater subsurface crystallographic degradation and displays a similar magnitude of subparticle cracking. However, the NMC811 maintains superior performance despite those advanced degradations. Here, the superior cycle life performance is attributed to the NMC811 particles having radially oriented grains and improved transport properties. NMC811 shows between 4.6× and 3.15× reduction in capacity fade than NMC532 for charging rates between 4C (e.g., 15-min charging) and 6C (10-min charging).
We report charging lithium-ion batteries (LiBs) in 10 to 15 min via extreme fast-charging (XFC) is important for the widespread adoption of electric vehicles (EVs). Lately, the battery research community has focused on identifying XFC bottlenecks and determining novel design solutions. Like other LiB components, cathodes can present XFC bottlenecks, especially when considering long-term battery life. Therefore, it is necessary to develop a comprehensive understanding of how XFC conditions degrade LiB cathodes. The present article reviews relevant cathode-focused studies and summarizes the current understanding regarding cathode performance and aging issues under XFC conditions. Dominant aging modes and mechanisms are identified at different length-scales with electrochemical correlations for LiNi x Mn y Co z O 2 (NMC)-based cathodes. A range of electrochemical techniques and models provide key insights into cathode performance and life issues. A suite of multimodal and multiscale microscopy and X-ray techniques is surveyed to quantify chemical, structural, and crystallographic NMC-cathode degradation. Cathode cycle-life is scaled to equivalent EV miles to illustrate how cathode degradation translates to real-world scenarios and quantifies cathode-related bottlenecks that hinder XFC adoption. Finally, the article discusses several cathode cycle-life aging mitigation strategies with example case studies and identifies remaining challenges.
Abstract Cyanopyridines and cyanophenylpyridines were investigated as anolytes for nonaqueous redox flow batteries (RFBs). The three isomers of cyanopyridine are reduced at potentials of −2.2 V or lower vs. ferrocene +/0 (Fc +/0 ), but the 3‐CNPy⋅ − radical anion forms a sigma‐dimer that is re‐oxidized at E ≈−1.1 V, which would lead to poor voltaic efficiency in a RFB. Bulk electrochemical charge‐discharge cycling of the cyanopyridines in acetonitrile and 0.50 M [NBu 4 ][PF 6 ] shows that 2‐CNPy and 4‐CNPy lose capacity quickly under these conditions, due to irreversible chemical reaction/decomposition of the radical anions. Density‐functional theory (DFT) calculations indicated that adding a phenyl group to the cyanopyridines would, for some isomers, limit dimerization and improve the stability of the radical anions, while shifting their E 1/2 only about +0.10 V relative to the parent cyanopyridines. Among the cyanophenylpyridines, 3‐CN‐6‐PhPy and 3‐CN‐4‐PhPy are the most promising as anolytes. They exhibit reversible reductions at E 1/2 =−2.19 and −2.22 V vs. ferrocene +/0 , respectively, and retain about half of their capacity after 30 bulk charge‐discharge cycles. An improved version of 3‐CN‐6‐PhPy with three methyl groups (3‐cyano‐4‐methyl‐6‐(3,5‐dimethylphenyl)pyridine) has an extremely low reduction potential of −2.50 V vs. Fc +/0 (the lowest reported for a nonaqueous RFB anolyte) and loses only 0.21 % of capacity per cycle during charge‐discharge cycling in acetonitrile.
Abstract In order to eliminate the influence of scene illumination on the evaluation of the color difference of dyed fabrics, this paper proposes a dyed fabric illumination correction algorithm based on the extreme learning machine (ELM) with grey wolf optimizer (GWO)‐optimized ant lion optimizer (ALO). Firstly, the Grey Edge framework is used to extract the features of the dyed fabric image as the input vector. Then, to improve the optimization ability of the ALO algorithm, the GWO algorithm is used to provide a set of optimized initial populations to the ALO algorithm, and then the improved ALO algorithm is used to optimize the parameters of the ELM. Finally, the proposed GWO‐ALO‐ELM algorithm is used to correct the illumination of the dyed fabric, and restore the graphics to the effect display under standard illumination through the diagonal reduction model. Compared with the experimental results of GWO‐ELM, ALO‐ELM, backpropagation (BP), ELM, random vector function link (RVFL), and other algorithms, it can be seen that the GWO‐ALO‐ELM algorithm proposed in this paper has good predictive value and quasi‐bias effect, and good stability.
Irradiation of solid surfaces with intense ultrashort laser pulses represents a unique way of depositing energy into materials. It allows to realize states of extreme electronic excitation and/or very high temperature and pressure and to drive materials close to and beyond fundamental stability limits. As a consequence, structural changes and phase transitions often occur along unusual pathways and under strongly nonequilibrium conditions. Furthermore, due to the inherent multiscale nature—both temporally and spatially—of these irreversible processes, their direct experimental observation requires techniques that combine high temporal resolution with the appropriate spatial resolution and the capability to obtain good quality data on a single pulse/event basis. In this respect, fourth-generation light sources, namely, short wavelength and short pulse free electron lasers (FELs), are offering new and fascinating possibilities. As an example, this chapter will discuss the results of scattering experiments carried out at the FLASH free electron laser at DESY (Hamburg, Germany), which allowed us to resolve laser-induced structure formation at surfaces on the nanometer to submicron length scale and in temporal regimes ranging from picoseconds to several nanoseconds with sub-picosecond resolution.
The Python’s Lunch conjecture for the complexity of bulk reconstruction involves two types of nonminimal quantum extremal surfaces (QESs): bulges and throats, which differ by their local properties. The conjecture relies on the connection between bulk spatial geometry and quantum codes: a constricting geometry from bulge to throat encodes the bulk state nonisometrically, and so requires an exponentially complex Grover search to decode. However, thus far, the Python’s Lunch conjecture is only defined for spacetimes where all QESs are spacelike-separated from one another. Here we explicitly construct (time-reflection symmetric) spacetimes featuring both timelike-separated bulges and timelike-separated throats. Interestingly, all our examples also feature a third type of QES, locally resembling a de Sitter bifurcation surface, which we name a bounce. By analyzing the Hessian of generalized entropy at a QES, we argue that this classification into throats, bulges and bounces is exhaustive. We then propose an updated Python’s Lunch conjecture that can accommodate general timelike-separated QESs and bounces. Notably, our proposal suggests that the gravitational analogue of a tensor network is not necessarily the time-reflection symmetric slice, even when one exists.
We show that a naïve application of the quantum extremal surface (QES) prescription can lead to paradoxical results and must be corrected at leading order. The corrections arise when there is a second QES (with strictly larger generalized entropy at leading order than the minimal QES), together with a large amount of highly incompressible bulk entropy between the two surfaces. We trace the source of the corrections to a failure of the assumptions used in the replica trick derivation of the QES prescription, and show that a more careful derivation correctly computes the corrections. Using tools from one-shot quantum Shannon theory (smooth min- and max-entropies), we generalize these results to a set of refined conditions that determine whether the QES prescription holds. We find similar refinements to the conditions needed for entanglement wedge reconstruction (EWR), and show how EWR can be reinterpreted as the task of one-shot quantum state merging (using zero-bits rather than classical bits), a task gravity is able to achieve optimally efficiently.
The probability to observe a specific number of strange and multi-strange hadrons (nS), denoted as P(nS), is measured by ALICE at midrapidity (|y| < 0.5) in $$\sqrt{s}=5.02$$ TeV proton-proton (pp) collisions, dividing events into several multiplicity-density classes. Exploiting, for the first time, a technique based on counting the number of strange-particle candidates event-by-event, this measurement allows one to extend the study of strangeness production beyond the mean of the distribution. This constitutes a new test bench for production mechanisms, probing events with a large imbalance between strange and non-strange content. The analysis of a large-statistics data sample makes it possible to extract P(nS) up to a maximum nS of 7 for $${\text{K}}_{\text{S}}^{0}$$, 5 for Λ and $$\overline{\Lambda }$$, 4 for Ξ− and $${\overline{\Xi } }^{+}$$, and 2 for Ω− and $${\overline{\Omega } }^{+}$$. From this, the probability of producing strange hadron multiplets per event is calculated, thereby enabling the extension of the study of strangeness enhancement to extreme situations where several strange quarks hadronize in a single event at midrapidity. Moreover, comparing hadron combinations with different u and d quark compositions and equal overall s quark content, the contribution to the enhancement pattern coming from non-strangeness related mechanisms is isolated. The results are compared with state-of-the-art phenomenological models implemented in commonly used Monte Carlo event generators, including PYTHIA 8 Monash 2013, PYTHIA 8 with QCD-based Color Reconnection and Rope Hadronization (QCD-CR + Ropes), and EPOS LHC, which incorporates both partonic interactions and hydrodynamic evolution. These comparisons show that the new approach dramatically enhances the sensitivity to the different underlying physics mechanisms modeled by each generator.
We study the effectiveness of theoretically-motivated high-level jet observables in the extreme context of jets with a large number of hard sub-jets (up to N = 8). Previous studies indicate that high-level observables are powerful, interpretable tools to probe jet substructure for N ≤ 3 hard sub-jets, but that deep neural networks trained on low-level jet constituents match or slightly exceed their performance. We extend this work for up to N = 8 hard sub-jets, using deep particle-flow networks (PFNs) and Transformer based networks to estimate a loose upper bound on the classification performance. A fully-connected neural network operating on a standard set of high-level jet observables, 135 N-subjetiness observables and jet mass, reach classification accuracy of 86.90%, but fall short of the PFN and Transformer models, which reach classification accuracies of 89.19% and 91.27% respectively, suggesting that the constituent networks utilize information not captured by the set of high-level observables. We then identify additional high-level observables which are able to narrow this gap, and utilize LASSO regularization for feature selection to identify and rank the most relevant observables and provide further insights into the learning strategies used by the constituent-based neural networks. The final model contains only 31 high-level observables and is able to match the performance of the PFN and approximate the performance of the Transformer model to within 2%.
Quantum states with geometric duals are known to satisfy a stricter set of entropy inequalities than those obeyed by general quantum systems. The set of allowed entropies derived using the Ryu-Takayanagi (RT) formula defines the Holographic Entropy Cone (HEC). These inequalities are no longer satisfied once general quantum corrections are included by employing the Quantum Extremal Surface (QES) prescription. Nevertheless, the structure of the QES formula allows for a controlled study of how quantum contributions from bulk entropies interplay with HEC inequalities. In this paper, we initiate an exploration of this problem by relating bulk entropy constraints to boundary entropy inequalities. In particular, we show that requiring the bulk entropies to satisfy the HEC implies that the boundary entropies also satisfy the HEC. Further, we also show that requiring the bulk entropies to obey monogamy of mutual information (MMI) implies the boundary entropies also obey MMI.