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When applying homogenization techniques to problems involving lattice structures, it is necessary to extend certain functions defined on a perforated domain to a simply connected domain. This paper provides general extension operators which preserve bounds on derivatives of order l. Only the special case of honeycomb structures is considered.
Here, we introduce a stochastic methodology to reproduce the complex pore structure observed in commercial iridium catalyst layers. This method preserves the α pore (pores smaller than 250 nm) and β pore (pores greater than or equal to 250 nm) regions of the catalyst layer. The morphology of the generated materials was validated by comparing the pore size distributions of generated materials against those obtained from commercial materials imaged using x-ray nano computed tomography. We further demonstrate that the pore size distributions of the generated materials are statistically indistinguishable from the imaged catalyst layers, indicating that the stochastic methodology is capable of accurately reproducing catalyst layer morphology. Pore network modelling was conducted on the generated catalyst materials to simulate single-phase permeability, electrical conductivity, and ionic conductivity, and these properties were found to be within experimentally measured ranges for electrolyzer catalyst layers. Additionally, simulations were performed on the generated materials with varying ionomer and iridium catalyst loadings. As the ionomer loading is added, proton conductivity increases exponentially, which demonstrates the importance of optimizing ionomer loading, considering that these effects will be exacerbated in the hydration and temperature conditions of operating electrolyzers. The stochastic material generation method presented in this work is a powerful tool for the development of novel low loading catalyst layers, where the effect of various structural parameters on electrolyzer performance characteristics can be explored.
Hyporheic zone sediments regulate organic matter turnover and in-stream respiration, yet controls on sediment respiration remain poorly constrained across heterogeneous river networks, limiting prediction of stream metabolism and carbon processing at continental scales. Here, we integrate observations from ~90 river corridors across the United States in the WHONDRS consortium with a knowledge-guided machine learning (KGML) framework that couples thermodynamic rate theory with machine learning to identify dominant controls on hyporheic respiration. Diagnostic analyses show that organic matter concentration and thermodynamic favorability define an upper bound on respiration potential, whereas biological catalytic capacity and physical accessibility jointly govern realized respiration rates through interaction effects. To represent unmeasurable accessibility constraints, we use the mechanistic model as a scaffold for KGML, allowing machine learning to target residual structure not explained by process theory. This hybrid framework improves predictive skill relative to both the mechanistic model alone and fully data-driven models while preserving interpretability. These results indicate that variability in hyporheic respiration is largely mechanistically structured and demonstrate how integrating process theory with explainable AI enhances predictive performance while enabling scalable synthesis of river corridor observations.
In this work, a methodology for incorporating measured modal data into an existing refined finite element model is examined with the objective of detecting and locating structural damage. The algorithm is based on the partial inverse problem, in that only partial spectral information is required. The technique utilizes a symmetric eigenstructure assignment algorithm to perform the partial spectral assignment. Algorithms to enhance mode shape assignability and to preserve sparsity in the damaged FEM are developed. The sparsity preservation is of particular importance when considering damage detection in trusslike structures. Several examples are presented to highlight the key points made within the paper.
The U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) proposes to demolish five buildings and five accessory resources in the Area 6 Control Point at the Nevada National Security Site (NNSS) in Nye County, Nevada. The demolition and removal of the buildings and accessories constitute an undertaking subject to review under Section 106 of the National Historic Preservation Act (NHPA) (54 United States Code [USC] § 306101) and its implementing regulations, 36 Code of Federal Regulations (CFR) Part 800. The buildings and accessories were recorded in Identification and Evaluation of 14 Architectural Resources Scheduled for Demolition, Area 6 Control Point and Vicinity, Nevada National Security Site, Nye County, Nevada (Menocal et al. 2020). The report found that the five buildings were not individually eligible for listing in the National Register of Historic Places (NRHP, National Register) but were potentially eligible as contributing elements to an unrecorded Area 6 Control Point district. The report also found that the five accessory resources were not individually eligible for the NRHP but they contributed to other historic properties, including the contributing elements to the unrecorded district. Finally, the report found that the undertaking would result in an adverse effect to historic properties. The State Historic Preservation Office (SHPO) concurred with the report’s findings regarding the eligibility of the buildings and structures in the Area of Potential Effect (APE) and that the undertaking would result in an adverse effect (Reed 2020). The NNSA/NFO, in consultation with the SHPO, then developed the Memorandum of Agreement DE-GM58-21NA25543 Between the U.S. Department of Energy and the Nevada State Historic Preservation Officer Regarding Demolition of Fourteen Buildings and Structures in Area 6 of the Nevada National Security Site, Nye County, hereafter referred to as the MOA. The MOA stipulates that a district boundary be delineated with an accompanying boundary report and supporting photographs (Stipulation III.A) followed by an architectural survey of the potential historic district (Stipulation III.B). The SHPO reviewed and concurred with the proposed district boundary and accompanying boundary report and photographs (O’Neill et al. 2021) on August 23, 2021, in fulfillment of Stipulation III.A (Reed 2021). This architectural survey report has been prepared in accordance with Stipulation III.B. It includes an NRHP evaluation of the district, identifies contributing and non-contributing elements, and is accompanied by Architectural Resource Assessment (ARA) forms. The NRHP evaluation concludes that the Area 6 Control Point is recommended eligible as a historic district under the Secretary of the Interior’s Significance Criterion A at the national level as the location of the command center and various support facilities directly related to timing and firing operations for nuclear testing on the NNSS from 1951 to 1992. It is also recommended eligible under Significance Criterion C for embodying the distinctive characteristics of a nuclear command center in the context of the Cold War and as a significant and distinguishable entity. There are a total of 29 primary resources within the district boundary. Of these, 28 are recommended as contributing elements to the Area 6 Control Point Historic District and one is recommended as non-contributing.
Cantaloupe terrain is unique to Triton. It is Triton's oldest terrain and includes about 250,000 km sq. region displaying sparsely cratered, closely spaced, nearly circular dimples about 30-40 km across. This terrain is found on no other planet because, only on Triton the final major global thermal pulse (1) caused completed (or nearly) interior melting resulting in a cooling history where large thermal stresses shattered and contorted a thin, weak lithosphere, and (2) occurred after heavy bombardment so that the surface features were preserved. The cantaloupe terrain is composed of intersecting sets of structures (folds and/or faults) that have developed as a result of global compression generated by volumetric changes associated with cooling of Triton's interior. Further, it is proposed that these structures developed after the period of heavy bombardment, and resulted from the last major global thermal epoch in Triton's unique history (either caused by tidal or radio metric heating). Initially, as the body cooled and the structures formed, their surface topography was most likely modified by thermal relaxation of the warm surface ices. In other bodies like Mercury, thermal stresses generated from global cooling and contraction have resulted in widely spaced thrust faults, whereas on Triton, thermal stresses produced more closely-spaced folds and faults sets. This difference in structural style is probably due to differences in lithospheric properties (thickness, strength, etc.), the magnitude of stress (directly dependent on the thermal history), and when the structures formed, relative to the period of heavy bombardment.
This paper investigates the effect of nonlinear large deflection bending on the aerodynamic performance of a high aspect ratio flexible wing. A set of nonlinear static aeroelastic equations are derived for the large bending deflection of a high aspect ratio wing structure. An analysis is conducted to compare the nonlinear bending theory with the linear bending theory. The results show that the nonlinear bending theory is length-preserving whereas the linear bending theory causes a non-physical effect of lengthening the wing structure under the no axial load condition. A modified lifting line theory is developed to compute the lift and drag coefficients of a wing structure undergoing a large bending deflection. The lift and drag coefficients are more accurately estimated by the nonlinear bending theory due to its length-preserving property. The nonlinear bending theory yields lower lift and span efficiency than the linear bending theory. A coupled aerodynamic-nonlinear finite element model is developed to implement the nonlinear bending theory for a Common Research Model (CRM) flexible wing wind tunnel model to be tested in the University of Washington Aeronautical Laboratory (UWAL). The structural stiffness of the model is designed to give about 10% wing tip deflection which is large enough that could cause the nonlinear deflection effect to become significant. The computational results show that the nonlinear bending theory yields slightly less lift than the linear bending theory for this wind tunnel model. As a result, the linear bending theory is deemed adequate for the CRM wind tunnel model.
The phase space of a noncanonical Hamiltonian system is partially inaccessible due to dynamical constraints (Casimir invariants) arising from the kernel of the Poisson tensor. When an ensemble of noncanonical Hamiltonian systems is allowed to interact, dissipative processes eventually break the phase space constraints, resulting in a thermodynamic equilibrium described by a Maxwell–Boltzmann distribution. However, the time scale required to reach Maxwell–Boltzmann statistics is often much longer than the time scale over which a given system achieves a state of thermal equilibrium. Examples include diffusion in rigid mechanical systems, as well as collisionless relaxation in magnetized plasmas and stellar systems, where the interval between binary Coulomb or gravitational collisions can be longer than the time scale over which stable structures are self-organized. Here, we focus on self-organizing phenomena over spacetime scales such that particle interactions respect the noncanonical Hamiltonian structure, but yet act to create a state of thermodynamic equilibrium. We derive a collision operator for general noncanonical Hamiltonian systems, applicable to fast, localized interactions. This collision operator depends on the interaction exchanged by colliding particles and on the Poisson tensor encoding the noncanonical phase space structure, is consistent with entropy growth and conservation of particle number and energy, preserves the interior Casimir invariants, reduces to the Landau collision operator in the limit of grazing binary Coulomb collisions in canonical phase space, and exhibits a metriplectic structure. We further show how thermodynamic equilibria depart from Maxwell–Boltzmann statistics due to the noncanonical phase space structure, and how self-organization and collisionless relaxation in magnetized plasmas and stellar systems can be described through the derived collision operator.
Monte Carlo simulations are a powerful technique and are widely used in different fields. When applied to complex molecular systems with long chains, such as those in synthetic polymers and proteins, they have the advantage of providing a fast and computationally efficient way to sample equilibrium ensembles and calculate thermodynamic and structural properties under desired conditions. Conformational Monte Carlo techniques employ a move set to perform the transitions in the simulation Markov chain. While accepted conformations must preserve the sequential bonding of the protein chain model and excluded volume among its units, the moves themselves may take the chain across itself. We call this a break in linear topology preservation. In this manuscript, we show, using simple protein models, that there is no difference in equilibrium properties calculated with a move set that preserves linear topology and one that does not. However, for complex structures, such as those of deeply knotted proteins, the preservation of linear topology provides correct equilibrium results but only after long relaxation. In any case, to analyze folding pathways, knotting mechanisms and folding kinetics, the preservation of linear topology may be an unavoidable requirement.
Motile plant structures such as Mimosa pudica leaves, Impatiens glandulifera seedpods, and Dionaea muscipula leaves exhibit fast nastic movements in a few seconds or less. This motion is stimuli-independent mechanical movement following theorema egregium rules. Artificial analogs of tropistic motion in plants are exemplified by shape-morphing systems, which are characterized by high functional robustness and resilience for creating 3D structures. However, all shape-morphing systems developed so far rely exclusively on continuous external stimuli and result in slow response. Here, we report a Gaussian-preserved shape-morphing system to realize ultrafast shape morphing and non-volatile reconfiguration. Relying on the Gaussian-preserved rules, the transformation can be triggered by mechanical or thermal stimuli within a microsecond. Moreover, as localized energy minima are encountered during shape morphing, non-volatile configuration is preserved by geometrically enhanced rigidity. Using this system, we demonstrate a suite of electronic devices that are reconfigurable, and therefore, expand functional diversification.
Calculation of free shear flows was carried out to investigate the usefulness of several concepts which were previously successfully applied to wall flows. The method belongs to the class of differential approaches. The turbulence is taken into account by the introduction of one additional partial differential equation, the transport equation for the turbulent shear stress. The structure of turbulence is modeled after Bradshaw et al. This model was used successfully in boundary layers and its applicability to other flows is demonstrated. The work reported differs substantially from that of an earlier attempt to use this approach for calculation of free flows. The most important difference is that the region around the center line is treated by invoking the interaction hypothesis (concerning the structure of turbulence in the regions separated by the velocity extrema). The compressibility effects on shear layer spreading at low and moderate Mach numbers were investigated. In the absence of detailed experiments in free flows, the evidence from boundary layers that at low Mach numbers the structure of turbulence is unaffected by the compressibility was relied on. The present model was tested over a range of self-preserving and developing flows including pressure gradients using identical empirical input. The dependence of the structure of turbulence on the spreading rate of the shear layer was established.
Mixed-halide lead perovskites, with photoexcited charge-carrier properties suitable for high-efficiency photovoltaics, hold significant promise for high-efficiency tandem solar cells. However, phase segregation under illumination, where an iodide-rich phase forms carrier trap states, remains a barrier to application. This study employs plunge-freeze cryoelectron microscopy to visualize nanoscale phase segregation dynamics in CsPb(Br x I 1–x ) 3 films. By rapidly freezing the illuminated samples, we preserve transient photoexcited ion distributions for high-resolution structural and compositional analysis at the nanoscale. Cryogenic scanning transmission electron microscopy (STEM) techniques (electron energy loss spectroscopy [EELS] and 4D-STEM) captured the dynamics of photo-induced iodine migration from grain boundaries to centers, identified the buildup of anisotropic strain, and captured the heterogeneous evolution of this process within a single grain. These findings provide insight into microscopic phase segregation mechanisms and their dynamics, enhancing our understanding of mixed-halide perovskite photostability.
Chemical vapor transport (CVT) method is widely used for bulk black phosphorus (BP) fabrication. In this work, we demonstrate that CVT provides a route for the fabrication of BP nanoribbons and nanobelts. This method consists of a two-step procedure, including initial BP column growth using the CVT technique, followed by ultrasonic treatment and centrifugation. The obtained nanostructures preserve BP column dimensions, forming ultralong ribbon-like structures with the length to the width aspect ratio of up to 500. Computational modeling of the growth mechanism of a BP flake is also presented in support of the observed columnar growth. Calculation of the average energy of the molecule in the asymmetric flakes shows that the growth of the structure in the zigzag direction is more energetically favorable than in the armchair direction.
Understanding the reaction kinetics at catalytically active sites is crucial for integrating catalytic two-dimensional (2D) materials into industrial processes. This study focuses on in situ observation of ligand exchange kinetics and solvent-assisted structural restacking transition in the 2D paddle wheel-based MOF [Cu 2 (dttc) 2 ] n (DUT-134(Cu), dttc = dithieno[3,2-b:2′,3′- d]thiophene-2,6-dicarboxylate). The ligand exchange process, involving the replacement of dimethylformamide (DMF) with nitriles such as acetonitrile (ACN), pentanenitrile, and heptanenitrile, was investigated using advanced in situ characterization techniques with high temporal resolution, including powder X-ray diffraction and Raman spectroscopy. The larger analytes exhibited reduced exchange rates, consistent with enhanced steric hindrance and greater diffusion constraints. Interestingly, the study revealed that the exchange of DMF with ACN induces a structural transition to higher symmetry within few seconds, a transition from AB to AA stacking mode of the layers, and a widening of the interlayer distance. Crucially, this structural transition dramatically accelerates the solvent exchange process through cooperative effects, offering critical advantages for catalytic applications. Notably, the reverse exchange from ACN to DMF proceeds more slowly and does not reverse the structural changes, but a new phase is formed with preserved AA stacking. By isotope labeling of linker molecules in combination with two complementary theoretical vibrational simulation methods, the precise assignment of Raman bands and the vibrational modes associated with the ligand exchange process could be achieved. These pioneering insights into the dynamic behavior of 2D MOFs, coupled with ligand exchange, establish a highly promising and transformative approach to achieving enhanced tunability and responsiveness in future catalytic applications.
Combining different observational probes, such as galaxy clustering and weak lensing, is a promising technique for unveiling the physics of the Universe with upcoming dark energy experiments. The galaxy redshift sample from the Dark Energy Spectroscopic Instrument (DESI) will have a significant overlap with major ongoing imaging surveys specifically designed for weak lensing measurements: the Kilo-Degree Survey (KiDS), the Dark Energy Survey (DES), and the Hyper Suprime-Cam (HSC) survey. In this work, we analyse simulated redshift and lensing catalogues to establish a new strategy for combining high-quality cosmological imaging and spectroscopic data, in view of the first-year data assembly analysis of DESI. In a test case fitting for a reduced parameter set, we employ an optimal data compression scheme able to identify those aspects of the data that are most sensitive to cosmological information and amplify them with respect to other aspects of the data. We find this optimal compression approach is able to preserve all the information related to the growth of structures.
Dynamic strain sensing is relevant in numerous applications involving structural health monitoring, condition-based maintenance, operation efficiency preservation, and work environment safety. These sensors are particularly critical for high-temperature (HT) harsh-environment (HE) industries such as aerospace, automotive, power plants, and advanced manufacturing. In HT/HE, sensor implementation and measurement present challenges such as maintaining sensor stability, accounting for temperature cross-sensitivity, providing HT attachment, and packaging of the sensors and system. Surface acoustic wave resonator (SAWR) sensors can address these needs and offer additional benefits such as compact size and wireless interrogation capability. The SAWR sensitivity to dynamic strain is temperature dependent, making it necessary to measure the sensor temperature in order to use the correct dynamic strain calibration curve. In this work, a method for determining the temperature, dynamic strain magnitude, and dynamic strain spectral components using a single SAWR sensor is presented. Here, the established technique for determining operational temperature and dynamic strain magnitude/spectral components using only one SAWR simplifies the sensor measurement system, thus being very attractive for HT /HE applications.
Nickel-rich single-crystal (SC) layered oxides are promising cathode candidates for next-generation lithium-ion batteries (LIBs) owing to their high energy density and structural robustness against intergranular cracking. However, their intrinsic surface reactivity with liquid electrolytes accelerates parasitic reactions at the cathode–electrolyte interphase (CEI), leading to transition-metal dissolution, gas generation, and impedance buildup. In this work, we synthesized SC-Li x Ni 0.9 Mn 0.05 Co 0.05 O 2 (NMC9055, 1 ≤ x ≤ 1.2) using a eutectic-assisted method and investigated interface stabilization strategies. A nickel-deficient Li x Ni 0.6 Mn 0.2 Co 0.2 O 2 (NMC622, 1 ≤ x ≤ 1.2) coating was applied via evaporation-based deposition to suppress CEI degradation pathways. Structural and compositional analyses confirmed uniform shell formation and preserved particle integrity. Half-cell electrochemical testing against lithium metal revealed ∼10% higher capacity retention and improved reversibility compared with pristine SC NMC9055, particularly under high-voltage operation. In conclusion, these results highlight the critical role of controlled surface chemistry in mitigating CEI instability in nickel-rich SC cathodes, offering a pathway toward enabling durable high-energy LIBs.
The discrete ordinates discontinuous Galerkin (SN-DG) method is a well-established and practical approach for solving the radiative transport equation. In this paper, we study a low-memory variation of the upwind SN-DG method. The proposed method uses a smaller finite element space that is constructed by coupling spatial unknowns across collocation angles, thereby yielding an approximation with fewer degrees of freedom than the standard method. Like the original SN-DG method, the low-memory variation still preserves the asymptotic diffusion limit and maintains the characteristic structure needed for mesh sweeping algorithms. While we observe second-order convergence in the scattering dominated, diffusive regime, the low-memory method is in general only first-order accurate. To address this issue, we use upwind reconstruction to recover second-order accuracy. Finally, for both methods, numerical procedures based on upwind sweeps are proposed to reduce the system dimension in the underlying Krylov solver strategy.