Search

While computational screening with density functional theory (DFT) is frequently employed for the screening of metal–organic frameworks (MOFs) for gas separation and storage, commonly applied generalized gradient approximations (GGAs) exhibit self-interaction errors, which hinder the predictions of adsorption energies. We investigate the Hubbard U parameter to augment DFT calculations for full periodic MOFs, targeting a more precise modeling of gas molecule–MOF interactions, specifically for N2, CO2, and O2. We introduce a calibration scheme for the U parameter, which is tailored for each MOF, by leveraging higher-level calculations on the secondary building unit (SBU) of the MOF. When applied to the full periodic MOF, the U parameter calibrated against hybrid HSE06 calculations of SBUs successfully reproduces hybrid-quality calculations of the adsorption energy of the periodic MOF. The mean absolute deviation of adsorption energies reduces from 0.13 eV for a standard GGA treatment to 0.06 eV with the calibrated U, demonstrating the utility of the calibration procedure when applied to the full MOF structure. Furthermore, attempting to use coupled cluster singles and doubles with perturbative triples calculations of isolated SBUs for this calibration procedure shows varying degrees of success in predicting the experimental heat of adsorption. It improves accuracy for N2 adsorption for cases of overbinding, whereas its impact on CO2 is minimal, and ambiguities in spin state assignment hinder consistent improvements of O2 adsorption. Our findings emphasize the limitations of cluster models and advocate the use of full periodic MOF systems with a calibrated U parameter, providing a more comprehensive understanding of gas adsorption in MOFs. [ABSTRACT FROM AUTHOR]

The field of multifunctional energetics encompasses a range of materials including propellants, explosives, and pyrotechnics that possess the ability to be manipulated through various characteristics that can be switched between go and no-go, or those that have controllable energy release levels or have additional functions beyond energetic output. The development of multifunctional energetics harnessing electromechanical or piezoelectric properties of polymeric materials or binder systems has garnered increasing interest in recent years. Among polymers, fluoropolymers such as poly(vinylidene fluoride) (PVDF) and copolymers such as poly(vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)], which are used as the binder and oxidizer in the energetic formulations, have demonstrated the highest piezoelectric coefficients. In this study, we fabricated piezo-energetic composite films using aluminum nanopowders (10 wt. % active content) as fuel and P(VDF-TrFE) (70/30) as an oxidizer and investigated the piezoelectric response using a small-scale drop weight setup. Additionally, we employed a shaker setup to investigate the response of the films to vibrations. Our findings demonstrate that these piezo-energetic films can replicate the behavior of a commercial PVDF gauge at relatively low-pressure impacts, indicating their potential use as shock or pressure sensors in various fields, as well as an accelerometer gauge. Additionally, aging studies of up to one year indicated minimal loss in the energetic content of the created films, enabling the use of energetic gauges for an extended period. Our findings support the effectiveness of piezo-energetic composite films as pressure sensors or accelerometers and highlight their potential for energetic applications. [ABSTRACT FROM AUTHOR]

Despite more than seven decades of active research and development in thermoelectricity, the accurate measurement of the thermoelectric (TE) properties of bulk materials has remained a challenge, mainly because of the strong interrelation between thermal and electrical phenomena. This work highlights practical advancements in methods and instrumentation dedicated to the simultaneous measurements of TE properties such as the Seebeck coefficient (S), the thermal (κ), and electrical (σ) conductivities and the dimensionless TE figure of merit ZT = S2σT/κ. The accuracy of a Harman based approach, as implemented by the ZT-Scanner (TEMTE Inc.), applicable to the simultaneous measurement of the above TE properties, has been made possible by a self-contained calibration procedure, which is based on the availability of two samples of the same homogeneous material having different shape factors. It is of practical importance that this approach provides a simple procedure to obtain the calibration for the figure of merit ZT and the thermal conductivity in the temperature interval from 300 to 720 K. In addition, we show that a simplified Harman setup with no thermocouples attached to the sample can also be used for self-contained calibrated ZT measurements. It is concluded that the implemented steady-state approach decreases the relative error down to 1%–2% for ZT measurements and can be recommended for most applications not involving dynamical behavior. In particular, it is proposed that self-generated calibration samples can critically increase the quality and ease of comparison of TE measurements if they are adopted by the TE community. [ABSTRACT FROM AUTHOR]

In this work, a calibration of ruby, samarium-doped strontium tetraborate (Sm2+: SrB4O7), and samarium-doped yttrium aluminum garnet (Sm3+: YAG) using Raman and fluorescence spectra was conducted within the temperature range of 296–850 K and pressure range of 0–55 GPa. The obtained calibration can be applied independently for high-temperature or high-pressure conditions and described as the unit form of P = (A′/B′) × [(λ/λT)B′ − 1] with A′ = A (296 K) + A1 × (T − 296) + A2 × (T − 296)2, B′ = B(296 K) + B1 × (T – 296), and λT = λT (296 K) + ΔλT, where the specific parameters are provided in the main text. It was observed that for the λ1 line (5D0 → 7F0 transition, about 685.2 nm under ambient conditions, also known as the 0-0 line) of Sm2+: SrB4O7, the neglect of the temperature effect on the pressure coefficient may lead to an underestimation of pressure above 35–40 GPa, with a maximum deviation of approximately 2.5 GPa within the range of 55 GPa and 850 K. For Sm3+: YAG, it may introduce significant errors under the whole high temperature and high pressure range if the effect of temperature is ignored, that is, about 3.9 GPa for Y1 line (4G5/2 → 6H7/2 transition, about 617.8 nm under ambient conditions) and 4.6 GPa for Y2 line (4G5/2 → 6H7/2 transition, about 616.0 nm under ambient conditions) at 850 K. Comparing the three fluorescence pressure sensors, the ruby has the strongest signal intensity and highest temperature sensitivity, and the Sm2+: SrB4O7 and the Sm3+: YAG possess lower temperature sensibility, wider used temperature range, and better spectral quality under high temperature and high pressure (HTHP), especially Sm2+: SrB4O7, which has a sharp high-intensity single peak λ1, perhaps the most promising sensor for high P–T experiments. Therefore, in view of the potential deflections of fluorescence peaks of each pressure sensor under HTHP, we recommend utilizing the HTHP-corrected relationships for pressure calibration. [ABSTRACT FROM AUTHOR]

Optical second harmonic generation (SHG) can be employed to characterize the passivation quality of semiconducting material interfaces. The interface electric field (EDC) related to the existing charges at and near the interface, including the fixed oxide charges Qox, gives rise to the electric field induced second harmonic phenomenon. In this paper, we calibrate the SHG response for EDC measurement, using Al2O3/SiO2/Si(100) samples with different Qox. To perform this calibration, SHG and capacitance-voltage measurements (to access the electrical field of the samples) were made. The experimental results match well the simulated calibration curve, proving the potential of the SHG as stand-alone characterization technique for dielectric stacks on Si. [ABSTRACT FROM AUTHOR]

Colloidal probes are often used in force microscopy when the geometry of the tip–sample interaction should be well controlled. Their calibration requires an understanding of their mechanical response, which is very sensitive to the details of the force sensor consisting of a cantilever and the attached colloid. We present some analytical models to describe the dynamics of the cantilever and its load positioned anywhere along its length. The thermal noise calibration of such probes is then studied from a practical point of view, leading to correction coefficients that can be applied in standard force microscope calibration routines. Experimental measurements of resonance frequencies and thermal noise profiles of raw and loaded cantilevers demonstrate the validity of the approach. [ABSTRACT FROM AUTHOR]

Dynamic shockless compression experiments provide the ability to explore material behavior at extreme pressures but relatively low temperatures. Typically, the data from these types of experiments are interpreted through an analytic method called Lagrangian analysis. In this work, alternative analysis methods are explored using modern statistical methods. Specifically, Bayesian model calibration is applied to a new set of platinum data shocklessly compressed to 570 GPa. Several platinum equation-of-state models are evaluated, including traditional parametric forms as well as a novel non-parametric model concept. The results are compared to those in Paper I obtained by inverse Lagrangian analysis. The comparisons suggest that Bayesian calibration is not only a viable framework for precise quantification of the compression path, but also reveals insights pertaining to trade-offs surrounding model form selection, sensitivities of the relevant experimental uncertainties, and assumptions and limitations within Lagrangian analysis. The non-parametric model method, in particular, is found to give precise unbiased results and is expected to be useful over a wide range of applications. The calibration results in estimates of the platinum principal isentrope over the full range of experimental pressures to a standard error of 1.6%, which extends the results from Paper I while maintaining the high precision required for the platinum pressure standard. [ABSTRACT FROM AUTHOR]

Gaussian process surrogates are a popular alternative to directly using computationally expensive simulation models. When the simulation output consists of many responses, dimension-reduction techniques are often employed to construct these surrogates. However, surrogate methods with dimension reduction generally rely on complete output training data. This article proposes a new Gaussian process surrogate method that permits the use of partially observed output while remaining computationally efficient. The new method involves the imputation of missing values and the adjustment of the covariance matrix used for Gaussian process inference. The resulting surrogate represents the available responses, disregards the missing responses, and provides meaningful uncertainty quantification. The proposed approach is shown to offer sharper inference than alternatives in a simulation study and a case study where an energy density functional model that frequently returns incomplete output is calibrated.

There is direct evidence of risks at moderate and high levels of radiation dose for highly radiogenic cancers such as leukaemia and thyroid cancer. For many cancer sites, however, it is necessary to assess risks via extrapolation from groups exposed at moderate and high levels of dose, about which there are substantial uncertainties. Crucial to the resolution of this area of uncertainty is the modelling of the dose-response relationship and the importance of both systematic and random dosimetric errors for analyses in the various exposed groups. It is well recognised that measurement error can alter substantially the shape of this relationship and hence the derived population risk estimates. Particular attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. We propose a modification of the regression calibration method which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. This method can be used in settings where there is a mixture of Berkson and classical error. In fits to synthetic datasets in which there is substantial upward curvature in the true dose response, and varying (and sometimes substantial) amounts of classical and Berkson error, we show that the coverage probabilities of all methods for the linear coefficient [Formula: see text] are near the desired level, irrespective of the magnitudes of assumed Berkson and classical error, whether shared or unshared. However, the coverage probabilities for the quadratic coefficient [Formula: see text] are generally too low for the unadjusted and regression calibration methods, particularly for larger magnitudes of the Berkson error, whether this is shared or unshared. In contrast Monte Carlo maximum likelihood yields coverage probabilities for [Formula: see text] that are uniformly too high. The extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large, although otherwise it performs well, and coverage is generally better than these other three methods. A notable feature is that for all methods apart from extended regression calibration the estimates of the quadratic coefficient [Formula: see text] are substantially upwardly biased.

Equations of state (EOSs) are typically represented as physics-informed models with tunable parameters that are adjusted to replicate calibration data as closely as possible. Uncertainty quantification (UQ) allows for the development of an ensemble of EOS parameters that are consistent with the calibration data instead of a single EOS. In this work, we perform UQ for the reactant and product EOSs for a variety of high explosives (HEs). In doing so, we demonstrate a strategy for dealing with heterogeneous (both experimental and calculated) data. We also use a statistical distance metric to quantify the differences between the various HEs using the UQ results. [ABSTRACT FROM AUTHOR]

Dynamic compression experiments in condensed matter are of interest in part because they provide opportunities to examine material response under extreme conditions; however, the inference of material behavior from dynamic experiments is challenging in the presence of phase transitions exhibiting kinetic processes. Demonstrating an approach to quantitative interpretation of such dynamic experiments, we present a Bayesian model calibration of strength and phase transformation parameters to data drawn from pulsed power and gas gun shot experiments. The posterior predictions of the Bayesian model capture the experimental measurements and account for the various uncertainties in the experimental configurations. This holistic approach to model calibration utilizing multiple types of experimental data identifies important cross correlations among kinetics, strength, and the phase boundary. Improved insight into potential sources of current model form error is provided by comparing the differences between calibrations against different subsets of the experimental data. [ABSTRACT FROM AUTHOR]

Purpose: To compare the linear and angular deviations of sites prepared for implants with the proposed 3D-printed sliding guide vs a 3D-printed conventional sleeveless static guide. Materials and Methods: This study consisted of two groups: a control group of 14 3D-printed conventional sleeveless static guides, and a test group of 37 3D-printed sliding guides. The guides were designed to drill 37 implant sites in each group. Linear and angular deviations were determined after scanning the drilled casts. Linear deviations were measured at the coronal and apical aspects of the drilled implant sites at 5-, 10-, 15-, and 20-mm distances. Results: There were no significant differences between the control and study groups regarding the coronal and 5-mm apical linear deviations. The angular and 10-, 15-, and 20-mm linear deviations of the 3D-printed sliding guide were significantly smaller than the control group. Conclusions: The proposed 3D-printed sliding guide could reduce the angular deviation of drilled implant sites from the planned positions, which is reflected in reducing the linear apical deviation of prepared implant sites longer than 5 mm. [ABSTRACT FROM AUTHOR]