Solvent expulsion away from an intervening region between two approaching particles plays important roles in particle aggregation yet remains poorly understood. In this work, we use metadynamics molecular simulations to study the free energy landscape of removing water molecules from gibbsite and pyrophyllite slit pores representing the confined spaces between two approaching particles. For gibbsite, removing water from the intervening region is both entropically and enthalpically unfavorable. The closer the particles approach each other, the harder it is to expel water molecules. For pyrophyllite, water expulsion is spontaneous, which is different from the gibbsite system. A smaller pore makes the water removal more favorable. When water is being drained from the intervening region, single chains of water molecules are observed in gibbsite pore, while in pyrophyllite pore water cluster is usually observed. Water-gibbsite hydrogen bonds help stabilize water chains, while water forms clusters in pyrophyllite pore to maximize the number of hydrogen bonds among themselves. This work provides the first assessment into the energetics and structure of water being drained from the intervening region between two approaching particles during oriented attachment and aggregation.
Renteria, Emma J.; Heileman, Grant D.; Neely, Jordan P.; Addamane, Sadhvikas J.; Rotter, Thomas J.; Balakrishnan, Ganesh; Christodoulou, Christos G.; Cavallo, Francesca
Here, it is demonstrated that single-crystalline and highly doped GaAs membranes are excellent candidates for realizing infrared-transparent shields of electromagnetic interference at millimeter frequencies. Measured optical transmittance spectra for the semiconductor membranes show resonant features between 750 and 2500 nm, with a 100% maximum transmittance. The shielding effectiveness of the membranes is extracted from measured scattering parameters between 65 and 85 GHz. Selected GaAs membranes and membranes/polyamide films exhibit shielding effectiveness ranging from 22 to 40 dB, which are suitable values to ensure the safe operation of infrared devices for commercial applications. Theoretical calculations based on a plane wave model show that the interplay of primary reflection and multiple internal reflections of the radio-frequency waves results in broadband shielding capabilities of the membrane between 10 and 300 GHz.
Helium-4-based scintillation detector technology is emerging as a strong alternative to pulse-shape discrimination-capable organic scintillators for fast neutron detection and spectroscopy, particularly in extreme gamma-ray environments. The 4He detector is intrinsically insensitive to gamma radiation, as it has a relatively low cross-section for gamma-ray interactions, and the stopping power of electrons in the 4He medium is low compared to that of 4He recoil nuclei. Consequently, gamma rays can be discriminated by simple energy deposition thresholding instead of the more complex pulse shape analysis. The energy resolution of 4He scintillation detectors has not yet been well-characterized over a broad range of energy depositions, which limits the ability to deconvolve the source spectra. In this work, an experiment was performed to characterize the response of an Arktis S670 4He detector to nuclear recoils up to 9 MeV. The 4He detector was positioned in the center of a semicircular array of organic scintillation detectors operated in coincidence. Deuterium–deuterium and deuterium–tritium neutron generators provided monoenergetic neutrons, yielding geometrically constrained nuclear recoils ranging from 0.0925 to 8.87 MeV. The detector response provides evidence for scintillation linearity beyond the previously reported energy range. Finally, the measured response was used to develop an energy resolution function applicable to this energy range for use in high-fidelity detector simulations needed by future applications.
Sun, Xifu; Jakeman, Anthony J.; Croke, Barry F.W.; Roberts, Stephen G.; Jakeman, John D.
In global sensitivity analysis (GSA) of a model, a proper convergence analysis of metrics is essential for ensuring a level of confidence or trustworthiness in sensitivity results obtained, yet is somewhat deficient in practice. The level of confidence in sensitivity measures, particularly in relation to their influence and support for decisions from scientific, social and policy perspectives, is heavily reliant on the convergence of GSA. We review the literature and summarize the available methods for monitoring and assessing convergence of sensitivity measures based on application purposes. The aim is to expose the various choices for convergence assessment and encourage further testing of available methods to clarify their level of robustness. Furthermore, the review identifies a pressing need for comparative studies on convergence assessment methods to establish a clear hierarchy of effectiveness and encourages the adoption of systematic approaches for enhanced robustness in sensitivity analysis.
Individual lanthanide elements have physical/electronic/magnetic properties that make each useful for specific applications. Several of the lanthanides cations (Ln3+) naturally occur together in the same ores. They are notoriously difficult to separate from each other due to their chemical similarity. Predicting the Ln3+ differential binding energies (ΔΔE) or free energies (ΔΔG) at different binding sites, which are key figures of merit for separation applications, will help design of materials with lanthanide selectivity. We apply ab initio molecular dynamics (AIMD) simulations and density functional theory (DFT) to calculate ΔΔG for Ln3+ coordinated to ligands in water and embedded in metal-organic frameworks (MOFs), and ΔΔE for Ln3+ bonded to functionalized silica surfaces, thus circumventing the need for the computational costly absolute binding (free) energies ΔG and ΔE. Perturbative AIMD simulations of water-inundated simulation cells are applied to examine the selectivity of ligands towards adjacent Ln3+ in the periodic table. Static DFT calculations with a full Ln3+ first coordination shell, while less rigorous, show that all ligands examined with net negative charges are more selective towards the heavier lanthanides than a charge-neutral coordination shell made up of water molecules. Amine groups are predicted to be poor ligands for lanthanide-binding. We also address cooperative ion binding, i.e., using different ligands in concert to enhance lanthanide selectivity.
Materials simulations based on direct numerical solvers are accurate but computationally expensive for predicting materials evolution across length- and time-scales, due to the complexity of the underlying evolution equations, the nature of multiscale spatiotemporal interactions, and the need to reach long-time integration. We develop a method that blends direct numerical solvers with neural operators to accelerate such simulations. This methodology is based on the integration of a community numerical solver with a U-Net neural operator, enhanced by a temporal-conditioning mechanism to enable accurate extrapolation and efficient time-to-solution predictions of the dynamics. We demonstrate the effectiveness of this hybrid framework on simulations of microstructure evolution via the phase-field method. Such simulations exhibit high spatial gradients and the co-evolution of different material phases with simultaneous slow and fast materials dynamics. We establish accurate extrapolation of the coupled solver with large speed-up compared to DNS depending on the hybrid strategy utilized. This methodology is generalizable to a broad range of materials simulations, from solid mechanics to fluid dynamics, geophysics, climate, and more.
Boron nitride nanotubes (BNNTs) are high-strength, high-modulus nanotubes with high thermal and oxidative stabilities. Two hybrid composites were prepared with satin weave carbon fiber (CF) and resole-type phenolic resin: one with surface layers of BNNTs and one with alternating interlayers of BNNTs. The samples were subjected to hot jet tests that simulate realistic high-pressure-temperature conditions to understand the behavior of BNNTs under high-pressure erosion. Adding BNNTs to CF/phenolic laminates enhanced the ablation resistance by reinforcing the char material and mitigated localized thermal damage. Hybrid laminates exhibited up to 14% lower weight loss, 55% increase in flexural modulus, higher thermal diffusivity, and improved char yield and microstructure compared to CF/phenolic samples. The surface layer hybrid had many surviving nanotubes reinforcing the char and crystalline oxide structures that could mitigate further oxygen diffusion. Further, various characterization methods were used to deduce possible mechanisms and their products, indicating that BNNTs could serve as growth templates for direct crystalline boron oxide formation. Overall, hybrid BNNT/CF/phenolic laminates displayed better ablation resistance and favorable microstructure evolution under high-pressure conditions.
Analytical and semi–analytical models for stream depletion with transient stream stage drawdown induced by groundwater pumping are developed to address a deficiency in existing models, namely, the use of a fixed stream stage condition at the stream–aquifer interface. Here field data are presented to demonstrate that stream stage drawdown does indeed occur in response to groundwater pumping near aquifer–connected streams. A model that predicts stream depletion with transient stream drawdown is developed based on stream channel mass conservation and finite stream channel storage. The resulting models are shown to reduce to existing fixed–stage models in the limit as stream channel storage becomes infinitely large, and to the confined aquifer flow with a no–flow boundary at the streambed in the limit as stream storage becomes vanishingly small. The model is applied to field measurements of aquifer and stream drawdown, giving estimates of aquifer hydraulic parameters, streambed conductance, and a measure of stream channel storage. The results of the modeling and data analysis presented herein have implications for sustainable groundwater management.
This dataset is comprised of a library of atomistic structure files and corresponding X-ray diffraction (XRD) profiles and vibrational density of states (VDoS) profiles for bulk single crystal silicon (Si), gold (Au), magnesium (Mg), and iron (Fe) with and without disorder introduced into the atomic structure and with and without mechanical loading. Included with the atomistic structure files are descriptor files that measure the stress state, phase fractions, and dislocation content of the microstructures. All data was generated via molecular dynamics or molecular statics simulations using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code. This dataset can inform the understanding of how local or global changes to a materials microstructure can alter their spectroscopic and diffraction behavior across a variety of initial structure types (cubic diamond, face-centered cubic (FCC), hexagonal close-packed (HCP), and body-centered cubic (BCC) for Si, Au, Mg, and Fe, respectively) and overlapping changes to the microstructure (i.e., both disorder insertion and mechanical loading).
Efficient carbon capture requires engineered porous systems that selectively capture CO2 and have low energy regeneration pathways. Porous liquids (PLs), solvent-based systems containing permanent porosity through the incorporation of a porous host, increase the CO2 adsorption capacity. A proposed mechanism of PL regeneration is the application of isostatic pressure in which the dissolved nanoporous host is compressed to alter the stability of gases in the internal pore. This regeneration mechanism relies on the flexibility of the porous host, which can be evaluated through molecular simulations. Here, the flexibility of porous organic cages (POCs) as representative porous hosts was evaluated, during which pore windows decreased by 10-40% at 6 GPa. POCs with sterically smaller functional groups, such as the 1,2-ethane in the CC1 POC resulted in greater imine cage flexibility relative to those with sterically larger functional groups, such as the cyclohexane in the CC3 POC that protected the imine cage from the application of pressure. Structural changes in the POC also caused CO2 adsorption to be thermodynamically unfavorable beginning at ∼2.2 GPa in the CC1 POC, ∼1.1 GPa in the CC3 POC, and ∼1.0 GPa in the CC13 POC, indicating that the CO2 would be expelled from the POC at or above these pressures. Energy barriers for CO2 desorption from inside the POC varied based on the geometry of the pore window and all the POCs had at least one pore window with a sufficiently low energy barrier to allow for CO2 desorption under ambient temperatures. The results identified that flexibility of the CC1, CC3, or CC13 POCs under compression can result in the expulsion of captured gas molecules.
Bulk metallic glasses (BMGs) are promising structural materials owing to their high elastic limit and yield strength-to-weight ratio. While BMGs also exhibit attractive tribological properties (e.g., high wear resistance), the scientific basis for this behavior is not yet established. In particular, tribologically-induced changes in surface chemistry upon sliding are still an open topic of research. Here, we evaluated by X-ray photoelectron spectroscopy (XPS) the evolution of the surface chemistry of Vitreloy 105 (a Zr-rich BMG) upon sliding under different contact conditions against a tungsten carbide countersurface. The spectroscopic results indicate that the relative fraction of the metallic elements in the near-surface region is not affected by the sliding speed when the applied contact pressure is lower than 1.37 GPa, while a decrease in metallic zirconium was observed at lower sliding speeds and higher applied contact pressure (i.e., 1.71 GPa). Based on the spectroscopic results, a model is proposed for the effect of mechanical stress on the extent of oxidation of the near-surface region of Zr-based BMGs. The results of this work provide novel insights into the surface phenomena occurring on BMGs upon sliding and add significantly to our understanding of the tribological response of this class of promising structural materials.
High-throughput image segmentation of atomic resolution electron microscopy data poses an ongoing challenge for materials characterization. In this paper, we investigate the application of the polyhedral template matching (PTM) method, a technique widely employed for visualizing three-dimensional (3D) atomistic simulations, to the analysis of two-dimensional (2D) atomic resolution electron microscopy images. This technique is complementary with other atomic resolution data reduction techniques, such as the centrosymmetry parameter, that use the measured atomic peak positions as the starting input. Furthermore, since the template matching process also gives a measure of the local rotation, the method can be used to segment images based on local orientation. We begin by presenting a 2D implementation of the PTM method, suitable for atomic resolution images. We then demonstrate the technique's application to atomic resolution scanning transmission electron microscopy images from close-packed metals, providing examples of the analysis of twins and other grain boundaries in FCC gold and martensite phases in 304 L austenitic stainless steel. Finally, we discuss factors, such as positional errors in the image peak locations, that can affect the accuracy and sensitivity of the structural determinations.
Stereo high-speed video of photovoltaic modules undergoing laboratory hail tests was processed using digital image correlation to determine module surface deformation during and immediately following impact. The purpose of this work was to demonstrate a methodology for characterizing module impact response differences as a function of construction and incident hail parameters. Video capture and digital image analysis were able to capture out-of-plane module deformation to a resolution of ±0.1 mm at 11 kHz on an in-plane grid of 10 × 10 mm over the area of a 1 × 2 m commercial photovoltaic module. With lighting and optical adjustments, the technique was adaptable to arbitrary module designs, including size, backsheet color, and cell interconnection. Impacts were observed to produce an initially localized dimple in the glass surface, with peak deflection proportional to the square root of incident energy. Subsequent deformation propagation and dissipation were also captured, along with behavior for instances when the module glass fractured. Natural frequencies of the module were identifiable by analyzing module oscillations postimpact. Limitations of the measurement technique were that the impacting ice ball obscured the data field immediately surrounding the point of contact, and both ice and glass fracture events occurred within 100 μs, which was not resolvable at the chosen frame rate. Increasing the frame rate and visualizing the back surface of the impact could be applied to avoid these issues. Applications for these data include validating computational models for hail impacts, identifying the natural frequencies of a module, and identifying damage initiation mechanisms.
In order to make design decisions, engineers may seek to identify regions of the design domain that are acceptable in a computationally efficient manner. A design is typically considered acceptable if its reliability with respect to parametric uncertainty exceeds the designer’s desired level of confidence. Despite major advancements in reliability estimation and in design classification via decision boundary estimation, the current literature still lacks a design classification strategy that incorporates parametric uncertainty and desired design confidence. To address this gap, this works offers a novel interpretation of the acceptance region by defining the decision boundary as the hypersurface which isolates the designs that exceed a user-defined level of confidence given parametric uncertainty. This work addresses the construction of this novel decision boundary using computationally efficient algorithms that were developed for reliability analysis and decision boundary estimation. The proposed approach is verified on two physical examples from structural and thermal analysis using Support Vector Machines and Efficient Global Optimization-based contour estimation.