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At least 379 records · Page 21

Green synthesis of reduced Ti 3 C 2 T x MXene nanosheets with enhanced conductivity, oxidation stability, and SERS activity

Transition metal carbides (MXenes) are an emerging family of highly conductive two-dimensional materials with additional functional properties introduced by surface terminations. Further modification of the surface terminations makes MXenes even more appealing for practical applications. Herein, we report a facile and environmentally benign synthesis of reduced Ti 3 C 2 T x MXene (r-Ti 3 C 2 T x ) via a simple treatment with L-ascorbic acid at room temperature. r-Ti 3 C 2 T x shows a six-fold increase in electrical conductivity, from 471 ± 49 for regular Ti 3 C 2 T x to 2819 ± 306 S m -1 for the reduced version. Additionally, we show an enhanced oxidation stability of r-Ti 3 C 2 T x as compared to regular Ti 3 C 2 T x . An examination of the surface-enhanced Raman scattering (SERS) activity reveals that the SERS enhancement factor of r-Ti 3 C 2 T x is an order of magnitude higher than that of regular Ti 3 C 2 T x . The improved SERS activity of r-Ti 3 C 2 T x is attributed to the charge transfer interaction between the MXene surface and probe molecules, re-enforced by an increased electronic density of states (DOS) at the Fermi level of r-Ti 3 C 2 T x . The findings of this study suggest that reduced MXene could be a superior choice over regular MXene, especially for the applications that employ high electronic conductivity, such as electrode materials for batteries and supercapacitors, photodetectors, and SERS-based sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic, magnetic, and structural properties of CoVMnSb: Ab initio study

We present computational results on electronic, magnetic, and structural properties of CoVMnSb, a quaternary Heusler alloy. Our calculations indicate that this material may crystallize in two energetically close structural phases: inverted and regular cubic. The inverted cubic phase is the ground state, with ferrimagnetic alignment, and around 80% spin polarization. Despite having a relatively large bandgap in the minority-spin channel close to the Fermi level, this phase does not undergo a half-metallic transition under pressure. This is explained by the “pinning” of the Fermi level at the minority-spin states at the Γ point. At the same time, the regular cubic phase is half-metallic and retains its perfect spin polarization under a wide range of mechanical strain. Transition to a regular cubic phase may be attained by applying uniform pressure (but not biaxial strain). In practice, this pressure may be realized by an atomic substitution of non-magnetic atoms (Sb) with another non-magnetic atom (Si) of a smaller radius. Our calculations indicate that 25% substitution of Sb with Si results in a half-metallic regular cubic phase being the ground state. In addition, CoVMnSb0.5Si0.5 retains its half-metallic properties under a considerable range of mechanical pressure, as well as exhibits thermodynamic stability, thus making this alloy attractive for potential spintronic applications. We hope that the presented results will stimulate experimental efforts to synthesize this compound.

Physics↗

Repartitioning the Hamiltonian in many-body second-order Brillouin–Wigner perturbation theory: Uncovering new size-consistent models

Second-order Møller-Plesset perturbation theory is well-known as a computationally inexpensive approach to the electron correlation problem that is size-consistent with a size-consistent reference but fails to be regular. On the other hand, the less well-known many-body version of Brillouin-Wigner perturbation theory has the reverse properties: it is regular but fails to be size-consistent when used with the standard MP partitioning. Consequently, its widespread use remains limited. In this work, we analyze the ways in which it is possible to use alternative non-MP partitions of the Hamiltonian to yield variants of BW2 that are size-consistent as well as regular. We show that there is a vast space of such BW2 theories and also show that it is possible to define a repartitioned BW2 theory from the ground state density alone, which regenerates the exact correlation energy. We also provide a general recipe for deriving regular, size-consistent, and size-extensive partitions from physically meaningful components, and we apply the result to small model systems. The scope of these results appears to further set the stage for a revival of BW2 in quantum chemistry.

Ab initio perturbation↗

Hybrid perturbation/Bubnov-Galerkin technique for nonlinear thermal analysis

A two step hybrid analysis technique to predict the nonlinear steady state temperature distribution in structures and solids is presented. The technique is based on the regular perturbation expansion and the classical Bubnov-Galerkin approximation. The functions are obtained by using the regular perturbation method. These functions are selected as coordinate functions and the classical Bubnov-Galerkin technique is used to compute their amplitudes. The potential of the proposed hybrid technique for the solution of nonlinear thermal problems is discussed. The effectiveness of this technique is demonstrated by the effects of conduction, convection, and radiation modes of heat transfer. It is indicated that the hybrid technique overcomes the two major drawbacks of the classical techniques: (1) the requirement of using a small parameter in the regular perturbation method; and (2) the arbitrariness in the choice of the coordinate functions in the Bubnov-Galerkin technique. The proposed technique extends the range of applicability of the regular perturbation method and enhances the effectiveness of the Bubnov-Galerkin technique.

Noor, A. K.↗

Asymptotic theory of steady axisymmetrical needlelike crystal growth

The present paper is concerned with the stationary needle crystal growth with arbitrary undercooling. Two classes of asymptotic solutions are discussed: (1) the regular-tip solutions, and (2) the smooth-root solutions. When the surface tension is nonzero, the regular-tip solutions may not have smooth roots. Among the regular-tip solutions, however, one can identify a 'principal regular-tip solution', which has the best behavior in the far field and is physically acceptable.

Xu, Jian-Jun↗

Optimal guidance law development for an advanced launch system

The objective of this research effort was to develop a real-time guidance approach for launch vehicles ascent to orbit injection. Various analytical approaches combined with a variety of model order and model complexity reduction have been investigated. Singular perturbation methods were first attempted and found to be unsatisfactory. The second approach based on regular perturbation analysis was subsequently investigated. It also fails because the aerodynamic effects (ignored in the zero order solution) are too large to be treated as perturbations. Therefore, the study demonstrates that perturbation methods alone (both regular and singular perturbations) are inadequate for use in developing a guidance algorithm for the atmospheric flight phase of a launch vehicle. During a second phase of the research effort, a hybrid analytic/numerical approach was developed and evaluated. The approach combines the numerical methods of collocation and the analytical method of regular perturbations. The concept of choosing intelligent interpolating functions is also introduced. Regular perturbation analysis allows the use of a crude representation for the collocation solution, and intelligent interpolating functions further reduce the number of elements without sacrificing the approximation accuracy. As a result, the combined method forms a powerful tool for solving real-time optimal control problems. Details of the approach are illustrated in a fourth order nonlinear example. The hybrid approach is then applied to the launch vehicle problem. The collocation solution is derived from a bilinear tangent steering law, and results in a guidance solution for the entire flight regime that includes both atmospheric and exoatmospheric flight phases.

Calise, Anthony J.↗

Echo mapping of active galactic nuclei broad-line regions: Fundamental algorithms

We formulate and test a series of algorithms for echo mapping the emission-line regions near active galactic nuclei from measurements of correlated variability in their line and continuum light curves. The linear regularization method (LRM) employs a direct inversion of evenly spaced light-curve data, with a regularization parameter that can be used to control the trade-off between noise and resolution. Matrix formulas express the formal solution as well as its variance and covariance in terms of uncertainties in the measurements. Unlike the maximum-entropy method (MEM), LRM applies to kernels with both positive and negative values, but the results are somewhat limited by ringing effects. A positivity constraint proves effective in controlling the ringing. MEM combines regularization and positivity in a natural way, but similar results are also found using positivity constraints with nonentropic regularization functions. Direct inversions of unevenly sampled light curves require interpolating the noisy data. In this case better results are found by solving for both the continuum light curve and kernel function in a simultaneous fit to the data. Our conclusion is that while echo mapping currently gives ambiguous results, the algorithms are not the limiting factor. Progress depends on efforts to increase the accuracy and completeness of sampling of the observed light curves.

Vio, Roberto↗

Some Operational Aspects of the International Two-Way Satellite Time and Frequency Transfer (TWSTFT) Experiment Using INTELSAT Satellites at 307 Degrees East

Eight laboratories are participating in an international two-way satellite time and frequency transfer (TWSTFT) experiment. Regular time and frequency transfers have been performed over a period of almost two years, including both European and transatlantic time transfers. The performance of the regular TWSTFT sessions over an extended period has demonstrated conclusively the usefulness of the TWSTFT method for routine international time and frequency comparisons. Regular measurements are performed three times per week resulting in a regular but unevenly spaced data set. A method is presented that allows an estimate of the values of delta (sub y)(gamma) to be formed from these data. In order to maximize efficient use of paid satellite time an investigation to determine the optimal length of a single TWSTFT session is presented. The optimal experiment length is determined by evaluating how long white phase modulation (PM) instabilities are the dominant noise source during the typical 300-second sampling times currently used. A detailed investigation of the frequency transfers realized via the transatlantic TWSTFT links UTC(USNO)-UTC(NPL), UTC(USNO)-UTC(PTB), and UTC(PTB)-UTC(NPL) is presented. The investigation focuses on the frequency instabilities realized, a three cornered hat resolution of the delta (sub y) (gamma) values, and a comparison of the transatlantic and inter-European determination of UTC(PTB)-UTC(NPL). Future directions of this TWSTFT experiment are outlined.

DeYoung, J. A.↗

Psychoacoustic Testing of Modulated Blade Spacing for Main Rotors

Psychoacoustic testing of simulated helicopter main rotor noise is described, and the subjective results are presented. The objective of these tests was to evaluate the potential acoustic benefits of main rotors with modulated (uneven) blade spacing. Sound simulations were prepared for six main rotor configurations. A baseline 4-blade main rotor with regular blade spacing was based on the Bell Model 427 helicopter. A 5-blade main rotor with regular spacing was designed to approximate the performance of the 427, but at reduced tipspeed. Four modulated rotors - one with "optimum" spacing and three alternate configurations - were derived from the 5 bladed regular spacing rotor. The sounds were played to 2 subjects at a time, with care being taken in the speaker selection and placement to ensure that the sounds were identical for each subject. A total of 40 subjects participated. For each rotor configuration, the listeners were asked to evaluate the sounds in terms of noisiness. The test results indicate little to no "annoyance" benefit for the modulated blade spacing. In general, the subjects preferred the sound of the 5-blade regular spaced rotor over any of the modulated ones. A conclusion is that modulated blade spacing is not a promising design feature to reduce the annoyance for helicopter main rotors.

Edwards, Bryan↗

Making Carbon-Nanotube Arrays Using Block Copolymers: Part 2

Some changes have been incorporated into a proposed method of manufacturing regular arrays of precisely sized, shaped, positioned, and oriented carbon nanotubes. Such arrays could be useful as mechanical resonators for signal filters and oscillators, and as electrophoretic filters for use in biochemical assays. A prior version of the method was described in Block Copolymers as Templates for Arrays of Carbon Nanotubes, (NPO-30240), NASA Tech Briefs, Vol. 27, No. 4 (April 2003), page 56. To recapitulate from that article: As in other previously reported methods, carbon nanotubes would be formed by decomposition of carbon-containing gases over nanometer-sized catalytic metal particles that had been deposited on suitable substrates. Unlike in other previously reported methods, the catalytic metal particles would not be so randomly and densely distributed as to give rise to thick, irregular mats of nanotubes with a variety of lengths, diameters, and orientations. Instead, in order to obtain regular arrays of spaced-apart carbon nanotubes as nearly identical as possible, the catalytic metal particles would be formed in predetermined regular patterns with precise spacings. The regularity of the arrays would be ensured by the use of nanostructured templates made of block copolymers.

Bronikowski, Michael↗

Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers

Backdoor data poisoning attacks have recently been demonstrated in computer vision research as a potential safety risk for machine learning (ML) systems. Traditional data poisoning attacks manipulate training data to induce unreliability of an ML model, whereas backdoor data poisoning attacks maintain system performance unless the MLmodel is presented with an input containing an embedded“trigger” that provides a predetermined response advantageous to the adversary. Our work builds upon prior back-door data-poisoning research for ML image classifiers and systematically assesses different experimental conditions including types of trigger patterns, persistence of trigger patterns during retraining, poisoning strategies, architectures (ResNet-50, NasNet, NasNet-Mobile), datasets (Flowers, CIFAR-10), and potential defensive regularization techniques (Contrastive Loss, Logit Squeezing, Manifold Mixup,Soft-Nearest-Neighbors Loss). Experiments yield four key findings. First, the success rate of backdoor poisoning at-tacks varies widely, depending on several factors, including model architecture, trigger pattern and regularization technique. Second, we find that poisoned models are hard to detect through performance inspection alone. Third, regularization typically reduces backdoor success rate, although it can have no effect or even slightly increase it, depending on the form of regularization. Finally, backdoors inserted through data poisoning can be rendered ineffective after just a few epochs of additional training on a small set of clean data without affecting the model’s performance.

Truong, Loc T.↗

An adaptive and stability-promoting layerwise training approach for sparse deep neural network architecture

This work presents a two-stage adaptive framework for progressively developing deep neural network (DNN) architectures that generalize well for a given training data set. In the first stage, a layerwise training approach is adopted where a new layer is added each time and trained independently by freezing parameters in the previous layers. We impose desirable structures on the DNN by employing manifold regularization, sparsity regularization, and physics-informed terms. We introduce a ε – δ – stability-promoting concept as a desirable property for a learning algorithm and show that employing manifold regularization yields a ε – δ stability-promoting algorithm. Further, we also derive the necessary conditions for the trainability of a newly added layer and investigate the training saturation problem. In the second stage of the algorithm (post-processing), a sequence of shallow networks is employed to extract information from the residual produced in the first stage, thereby improving the prediction accuracy. Numerical investigations on prototype regression and classification problems demonstrate that the proposed approach can outperform fully connected DNNs of the same size. Moreover, by equipping the physics-informed neural network (PINN) with the proposed adaptive architecture strategy to solve partial differential equations, we numerically show that adaptive PINNs not only are superior to standard PINNs but also produce interpretable hidden layers with provable stability. As a result, we also apply our architecture design strategy to solve inverse problems governed by elliptic partial differential equations.

42 ENGINEERING↗

The approximate second order coupled-cluster method based on a size-consistent Brillouin–Wigner partitioning

We present a variant of the approximate second order coupled-cluster method (CC2) with a two-parameter size-consistent Brillouin–Wigner (BW-s) partitioning instead of a Møller–Plesset (MP) partitioning for the unperturbed Hamiltonian, which we refer to as BWs-CC2. The computational complexity of this model scales identically to CC2 with molecular size. Conventional CC2 and its regularized BWs-CC2 variants, as well as conventional MP2 and two of its regularized BW-s2 variants, were assessed on a 535 element database spanning thermochemistry, non-covalent interactions, barrier heights, and isomerization energies. To ensure a well-defined model chemistry, the assessment was performed using internally stable spin-polarized Hartree–Fock (HF) orbitals in the finite aug-cc-pVQZ basis without counterpoise corrections. As a result of using stable orbitals, contrary to conventional wisdom, we find that CC2 substantially outperforms MP2 on molecules with significantly spin contaminated reference orbitals without a significant increase in error on systems with a spin-pure reference, showing the value of its single substitutions. While no single choice of regularization parameters can be optimal for all datasets, we find that BWs-CC2 generally outperforms both CC2 and BW-s2 with a single judicious parameter choice. Additional tests on dipole moments and bond lengths of diatomics provide further support for the utility of this choice. Furthermore, the main outliers and poorest performing cases are associated with large amounts of spin-contamination in the HF reference, which is indicative of systems with either strong correlation or extensive artificial symmetry breaking. Overall, these findings argue that the perception of the quality of the CC2 ground state should be reevaluated and that it can be further improved upon by the soundly based BWs-CC2 variant with the recommended parameter choice.

Correlation energy↗

Improved Guarantees for Optimal Nash Equilibrium Seeking and Bilevel Variational Inequalities

We consider a class of hierarchical variational inequality (VI) problems that subsumes VI-constrained optimization and several other problem classes, including the optimal solution selection problem and the optimal Nash equilibrium (NE) seeking problem. Our main contribution is threefold. (i) We consider bilevel VIs with monotone and Lipschitz continuous mappings and devise a single-timescale iteratively regularized extragradient method, named IR-EG 𝚖,𝚖 . We improve the existing iteration complexity results for addressing both bilevel VI and VI-constrained convex optimization problems. (ii) Under the strong monotonicity of the outer-level mapping, we develop a method named IR-EG 𝚜,𝚖 and derive faster guarantees than those in (i). We also study the iteration complexity of this method under a constant regularization parameter. These results appear to be new for both bilevel VIs and VI-constrained optimization. (iii) To our knowledge, complexity guarantees for computing the optimal NE in nonconvex settings do not exist. Motivated by this lacuna, we consider VI-constrained nonconvex optimization problems and devise an inexactly projected gradient method, named IPR-EG, where the projection onto the unknown set of equilibria is performed using IR-EG 𝚜,𝚖 with a prescribed termination criterion and an adaptive regularization parameter. We obtain new complexity guarantees in terms of a residual map and an infeasibility metric for computing a stationary point. Here, we validate the theoretical findings using preliminary numerical experiments for computing the best and the worst NEs.

bilevel optimization↗

Hierarchical ensemble Kalman methods with sparsity-promoting generalized gamma hyperpriors

This paper introduces a computational framework to incorporate flexible regularization techniques in ensemble Kalman methods, generalizing the iterative alternating scheme to nonlinear inverse problems. The proposed methodology approximates the maximum a posteriori (MAP) estimate of a hierarchical Bayesian model characterized by a conditionally Gaussian prior and generalized gamma hyperpriors. Suitable choices of hyperparameters yield sparsity-promoting regularization. We propose an iterative algorithm for MAP estimation, which alternates between updating the unknown with an ensemble Kalman method and updating the hyperparameters in the regularization to promote sparsity. Here, the effectiveness of our methodology is demonstrated in several computed examples, including compressed sensing and subsurface flow inverse problems.

Ensemble Kalman methods↗

Virtual element approximations of the time-fractional nonlinear convection-diffusion equation on polygonal meshes

We extend the Virtual Element Method to a two-dimensional unsteady nonlinear convection-diffusion equation characterized by a fractional-order derivative with respect to the time variable. Our methodology is based on three fundamental technical components: a fractional version of the Grunwald-Letnikov approximation, discrete maximal regularity, and the regularity theory associated with non-linearity. We prove the method's well-posedness, i.e., the approximate solution's existence and uniqueness to the time-fractional convection-diffusion equation with a Lipschitz nonlinear source term. The fully discrete scheme inherently maintains stability and consistency by leveraging the discrete maximal regularity and the energy projection operator. The convergence in the L 2 -norm and H 1 -norm to various mesh configurations is validated by numerical results, underlining the practical effectiveness of the proposed method.

97 MATHEMATICS AND COMPUTING↗

A Lithium Metal Anode Surviving Battery Cycling Above 200 °C

Lithium (Li) metal electrode cannot endure elevated temperature (e.g., >200 °C) with the regular battery configuration due to its low melting point (180.5 °C) and high reactivity, which restricts its application in high-temperature Li metal batteries for energy storage and causes safety concerns for regular ambient-temperature Li metal batteries. Herein, this work reports a Li 5 B 4 /Li composite featuring a 3D Li 5 B 4 fibrillar framework filled with metallic Li, which maintains its initial structure at 325 °C in Ar atmosphere without leakage of the liquid Li. The capillary force caused by the porous structure of the Li 4 B 5 fibrillar framework, together with its lithiophilic surface, restricts the leakage of liquid metallic Li and enables good thermal tolerance of the Li 5 B 4 /Li composite. Thus, it can be facilely operated for rechargeable high-temperature Li metal batteries. Li 5 B 4 /Li electrodes are coupled with a garnet-type ceramic electrolyte (Li 6.5 La 3 Zr 0.5 Ta 1.5 O 12 ) to fabricate symmetric cells, which exhibit stable Li stripping/plating behaviors with low overpotential of approximate to 6 mV at 200 °C using a regular sandwich-type cell configuration. This study affords new insights into realizing a stable Li metal anode for high-temperature Li metal batteries with a simple battery configuration and high safety, which is different from traditional molten-salt Li metal batteries using a pristine metallic Li anode.

25 ENERGY STORAGE↗

A Scalable Interior‐Point Gauss–Newton Method for PDE‐Constrained Optimization With Bound Constraints

Here, we present a scalable approach to solve a class of partial differential equation (PDE)‐constrained optimization problems with bound constraints. This approach utilizes a robust full‐space interior‐point (IP)‐Gauss–Newton optimization method. To cope with the poorly‐conditioned IP‐Gauss–Newton saddle‐point linear systems that need to be solved approximately, once per optimization step, we propose two spectrally related preconditioners. These preconditioners leverage the limited informativeness of data in regularized PDE‐constrained optimization problems. A block Gauss–Seidel preconditioner is proposed for the GMRES‐based solution of the IP‐Gauss–Newton linear systems. It is shown, for a large‐class of PDE‐ and bound‐constrained optimization problems, that the spectrum of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix is asymptotically independent of discretization and is not impacted by the ill‐conditioning that notoriously plagues interior‐point methods. We exploit symmetry of the IP‐Gauss–Newton linear systems and propose a regularization and log‐barrier Hessian preconditioner for the preconditioned conjugate gradient (PCG)‐based solution of the equivalent IP‐Gauss–Newton–Schur complement linear systems. The eigenvalues of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix, that are not equal to one, are identical to the eigenvalues of the regularization and log‐barrier Hessian preconditioned Schur complement matrix. The scalability of the approach is demonstrated on two example problems. The numerical solution of these optimization problems is shown to require a discretization independent number of IP‐Gauss–Newton linear solves. Furthermore, the linear systems are solved in a discretization and IP ill‐conditioning independent number of preconditioned Krylov subspace iterations. The parallel scalability of the preconditioner, achieved via algebraic multigrid component solvers when applicable, and the aforementioned algorithmic scalability permits a parallel scalable means to compute solutions of a large class of PDE‐ and bound‐constrained problems.

PDE-constrained optimization↗