Cooperative Interactions between Surface Terminations Explain Photocatalytic Water Splitting Activity on Sr Ti O 3
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71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
SEARCH · Engineering Papers
Results for “generalized functions”
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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Regularization prescription for the mixing between nonlocal gluon and quark operators
It is well known that in the study of mixing between nonlocal gluon and quark bilinear operators there exists an ambiguity when relating coordinate space and momentum space results. In this work, we show that this ambiguity is due to the lack of a proper regularization prescription of the singularity that arises when the separation between the gluon/quark fields approaches zero. We then demonstrate that dimensional regularization resolves this issue and yields consistent results in both coordinate and momentum space. This prescription is also compatible with lattice extractions of parton distributions from nonlocal operators.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Measurement of the $c$-jet mistagging efficiency in $t\bar{t}$ events using $pp$ collision data at $\sqrt{s}=13$ $\text {TeV}$ collected with the ATLAS detector
A technique is presented to measure the efficiency with which c-jets are mistagged as b-jets (mistagging efficiency) using tt¯ events, where one of the W bosons decays into an electron or muon and a neutrino and the other decays into a quark–antiquark pair. The measurement utilises the relatively large and known W → cs branching ratio, which allows a measurement to be made in an inclusive c-jet sample. The data sample used was collected by the ATLAS detector at √s = 13 TeV and corresponds to an integrated luminosity of 139 fb –1 . Events are reconstructed using a kinematic likelihood technique which selects the mapping between jets and tt¯ decay products that yields the highest likelihood value. The distribution of the b-tagging discriminant for jets from the hadronic W decays in data is compared with that in simulation to extract the mistagging efficiency as a function of jet transverse momentum. The total uncertainties are in the range 3–17%. The measurements generally agree with those in simulation but there are some differences in the region corresponding to the most stringent b-jet tagging requirement.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Sensor Recommendations for Long Term Monitoring of the F-Area Seepage Basins
In mid-2018, a new paradigm for long-term monitoring was developed after of decade of applied research projects funded by the Department of Energy’s office of Environmental Management Technology Development program. The program at SRNL was focused on transitioning complex environmental waste sites from active to passive remediations strategies. A key result of these studies was that the use of enhanced attenuation approaches at radiologically contaminated sites will result in the creation of secondary source areas in the subsurface that will require monitoring for decades. Alternative monitoring approaches are being developed and tested at the Savannah River Site’s F-Area Hazardous Waste Management Facility, the new paradigm provides innovative solutions that will significantly lower costs of monitoring through the coupling of data collection, machine learning and deterministic groundwater modeling. The foundation of this approach is a well-optimized network of sensors for measuring hydrogeochemical master variables that control, and therefore act as indicators of groundwater contaminant transport. By monitoring changes in the controlling master variables over time arising from geological and environmental shifts, predictive modelling can assist with identifying new strategies for ensuring regulatory requirements are met if trends toward conditions for potential remobilization of attenuated contaminants are detected. In this report, we evaluated commercially available single parameter sensor platforms (e.g., temperature/depth) and configurable multi-parameter sensor platforms (e.g., pH, oxidation-reduction potential, temperature, depth, dissolved oxygen, and conductivity). Each was scored using an optimization function based on how well the system supports the proposed long-term monitoring paradigm, in general, and the site-specific conditions at F-Area, in particular. Several viable sensor systems were identified. Of these, a combined platform including the In-Situ Aqua TROLL 500 multi-parameter sensor platform and the In-Situ temperature/depth sensor had the highest rating and was identified as the most suitable candidate for installation and monitoring of the master variables and potentiometric surface that control groundwater contaminant plumes emanating from the F-Area Seepage Basins. The discussion of recommended potential deployment locations builds upon recommendations made by Denham et al (2019).
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Development of an Assessment Methodology That Enables the Nuclear Industry to Evaluate Adoption of Advanced Automation
Nuclear power has a crucial role in providing safe, reliable, and economical carbon-free electricity for today and the future. For continued operation, many of the existing United States nuclear power plants will begin the subsequent license renewal process for extending their operating license periods. As plants extend their expected operating lifetimes, there is a significant opportunity to modernize. These plants have a much stronger business case with these extended mission periods to modernize and significantly enhance their economic viability in current and future energy markets by implementing digital technologies that support innovation, efficiency gains, and business-model transformation. Ensuring continued safety and reliability is crucial. Transformative digital technologies—including automation—that fundamentally change the concept of operation for the nuclear power plant operating model requires a critical focus on the human and technology integration element. Further, the nuclear industry has historically been reluctant to modernize due to having a risk adverse culture and lack of clarity for a transformative new state vision (Joe & Remer, 2019; Thomas et al., 2020). Common barriers include (1) the perceived value and return on investment (ROI) of digital technology, (2) the perceived risk associated with licensing, regulatory, and cybersecurity, and (3) insufficient guidance for performing digital modifications to power generation systems. This work presents a methodology to address these barriers and support the industry in adopting advanced automation and digital technology through developing a transformative vision and implementation strategy that will address the human and technology integration element. This research leverages previous LWRS Program and industry results. It draws specifically on previous LWRS Program research in the areas of advanced alarm systems, computer-based procedures, model informed decision support, and advanced human-system interface displays (e.g., overviews and task-based). The modernization methodology can be used to guide transformative thinking when integrating a set of vendor-specific capabilities to support a new concept of operations and a utility’s end-state vision. The results of this research are organized into six major sections: - Section 1 introduces the need for supporting large-scale digital modifications that will renew the technology base for extended operating life beyond 60 years - Section 2 describes the challenges that the nuclear industry is enduring with modernizing. - Section 3 summarizes the primary standards and guidance. - Section 4 presents earlier work from the LWRS Program regarding the development of a transformative conceptual design for an advanced control room of a hybrid plants. - Section 5 presents a methodology that is designed at addressing the challenges in the industry today in achieving a transformative new state vision and concept of operations. - Conclusions and next steps of this research are provided in Section 6.
99 GENERAL AND MISCELLANEOUS↗
Adsorption and Growth of Organic Materials on Metal Surfaces
This work investigated extensively the role of van der Waals (vdWs) interactions, when incorporated self-consistently into density functional theory (DFT). The investigations follow two avenues: 1) screening of several vdWs schemes at the generalized gradient approximation (GGA), using adsorption of small and large organic molecules on a variety of metal surfaces; and 2) simulating the adsorption of 2D materials such as silicene and phosphorene on metal surfaces. This second avenue is done in connection were subject of experimental investigations. These investigations led us to the conclusion that, if the inclusion of the vdWs interactions improved the nature of the adsorption and brought some excellent agreements with the experimental observations of the adsorption geometries, there is still a lot to do when it comes to the changes to the electronic structure upon adsorption.
2D materials.↗
Digital Twins for Materials
Digital twins are emerging as powerful tools for supporting innovation as well as optimizing the in-service performance of a broad range of complex physical machines, devices, and components. A digital twin is generally designed to provide accurate in-silico representation of the form (i.e., appearance) and the functional response of a specified (unique) physical twin. This paper offers a new perspective on how the emerging concept of digital twins could be applied to accelerate materials innovation efforts. Specifically, it is argued that the material itself can be considered as a highly complex multiscale physical system whose form (i.e., details of the material structure over a hierarchy of material length) and function (i.e., response to external stimuli typically characterized through suitably defined material properties) can be captured suitably in a digital twin. Accordingly, the digital twin can represent the evolution of structure, process, and performance of the material over time, with regard to both process history and in-service environment. This paper establishes the foundational concepts and frameworks needed to formulate and continuously update both the form and function of the digital twin of a selected material physical twin. The form of the proposed material digital twin can be captured effectively using the broadly applicable framework of n-point spatial correlations, while its function at the different length scales can be captured using homogenization and localization process-structure-property surrogate models calibrated to collections of available experimental and physics-based simulation data.
36 MATERIALS SCIENCE↗
A pedagogical derivation of dynamical susceptibilities
Dynamical two-particle susceptibilites are important for a wide range of different experiments in condensed-matter physics and beyond. Nevertheless, most textbooks avoid describing how to derive such response functions, perhaps because they are viewed as too complex. In the literature, most derivations work with generalized susceptibilities, which are more general, but require an even higher layer of complexity. In this work, we show a more direct derivation in the context of model Hamiltonians which can be mapped directly onto an impurity model. We also present an alternative derivation for the irreducible vertex in the context of the Falicov-Kimball model.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Entanglement Requirements for Coherent Enhancement in Detectors
Coherent enhancement is a powerful mechanism for improving the sensitivity of a wide range of detectors, but its practical use is often limited by the difficulty of preparing the required quantum states. We show that this difficulty has a fundamental origin: coherent enhancement of a signal interacting with a detector is quantitatively constrained by entanglement. We prove general bounds on how the strength of coherent effects can scale with system size, as a function of the single-mode entanglement entropy of the detector. These bounds smoothly interpolate between the incoherent and fully coherent regimes, and apply both to parameter-estimation problems and to scattering processes. We discuss these results from two complementary perspectives: First, they appear as bounds on the quantum Fisher information of many-body states, which translate directly into limits on parameter sensitivity via the quantum Cramér-Rao bound. Second, they can be interpreted as limits on a class of scattering cross sections, leading to predictions for how minimum detectable interaction strengths scale with target size. Together, these results provide a unified view of coherent enhancement in metrology and scattering experiments, and motivate the development of new techniques for generating entangled detector states.
Bogorad, Zachary [Fermilab] (ORCID:000000019913647↗
Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems
Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.
Preconditioner, Nonlinear, Porous media, Multiphas↗
Adjoint DSMC for nonlinear spatially-homogeneous Boltzmann equation with a general collision model
We derive an adjoint method for the Direct Simulation Monte Carlo (DSMC) method for the spatially homogeneous Boltzmann equation with a general collision law. This generalizes our previous results in Caflisch et al., which was restricted to the case of Maxwell molecules, for which the collision rate is constant. The main difficulty in generalizing the previous results is that a rejection sampling step is required in the DSMC algorithm in order to handle the variable collision rate. We find a new term corresponding to the so-called score function in the adjoint equation and a new adjoint Jacobian matrix capturing the dependence of the collision parameter on the velocities. The new formula works for a much more general class of collision models.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Anion Association Strength as a Unifying Descriptor for the Reversibility of Divalent Metal Deposition in Nonaqueous Electrolytes
Developing next-generation battery chemistries that move beyond traditional Li-ion systems is critical to enabling transformative advances in electrified transportation and grid-level energy storage. Here, we provide the first evidence for common descriptors for improved reversibility of metal plating/stripping in nonaqueous electrolytes for multivalent ion batteries. Focusing first on the specific role of chloride (Cl – ) in promoting electrochemical reversibility in multivalent systems, rotating disk (RDE) and ring-disk electrode (RRDE) investigations were performed utilizing a variety of divalent cations (Mg 2+ , Zn 2+ , and Cu 2+ ) and the bis-(trifluoromethane sulfonyl) imide (TFSI – ) anion. By introducing varying concentrations of Cl – , a cooperative effect is observed between TFSI – and Cl – that yields the more reversible behavior of mixed electrolytes relative to electrolytes containing only TFSI – . This effect is shown to be general for Mg, Zn, and Cu electrodeposition, and mechanistic understanding of the role of Cl – in improving reversibility of TFSI-based electrolytes is obtained through the combination of R(R)DE experimental results and density functional theory (DFT) evaluation of the redox activity and thermodynamic stability of various TFSI- and Cl-based solution complexes of metal ions. The cooperative anion effect is further generalized to other mixed-anion systems, where systematic variations in anion association strength predicted from DFT (i.e., Cl – > OTf – ≈ TFSI – > BF 4 – > PF 6 – ) yield corresponding trends in redox potentials and improvements of ≥200 mV in the reversibility of metal deposition/dissolution. These results identify anion association strength as a common descriptor for the reversibility of divalent metal anodes and suggest a set of general design principles for developing new electrolytes with improved activity and stability.
25 ENERGY STORAGE↗
A generalized 3D elastic model for nanoscale, self-assembled oxide-metal thin films with pillar-in-matrix configurations
In recent years, functional oxide-metal based vertically aligned nanocomposite (VAN) thin films have gained interest due to their intriguing physical properties and multifunctionalities stemming from the complex interactions between the two phases in the film and the substrate. In this work, we develop a model for studying the energetics of these thin film systems, including the effects of both lattice mismatch and capillary forces due to interface curvature. Each phase is incorporated into the model using a phase indicator function, and we introduce the capillary forces as body forces using a vector density representation of the interface. The model is implemented using the finite element method to study the deformation of the thin film which is composed of Au nanopillars embedded in a La 0.7 Sr 0.3 MnO 3 (LSMO) matrix on an SrTiO 3 (STO) substrate. Further, the results suggest that the total energy is lowest for random configurations of pillars compared to ordered square and hexagonal lattice configurations, consistent with the random distribution of pillars found in experiments. Furthermore, we find that the interfacial energy dominates the total energy of each configuration, suggesting that interfacial energy in the system is an important design parameter for nanocomposite growth, along with the lattice mismatch.
36 MATERIALS SCIENCE↗
Basis light-front quantization approach to photon
We solve for the light-front wave functions (LFWFs) of the physical photon from the eigenvectors of the light-front quantum electrodynamics (QED) Hamiltonian with the aim to determine its bare photon and electron-positron Fock components. We then employ the resulting LFWFs to compute the transverse momentum dependent parton distributions (TMDs) and the generalized parton distributions (GPDs) at zero skewness of the photon. The TMDs are found to be in excellent agreement with the lowest-order perturbative results calculated using the electron-positron quantum fluctuation of the photon. The GPDs are also consistent with the perturbative calculations.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Data-driven reduced-order models for port-Hamiltonian systems with operator inference
Hamiltonian operator inference has been developed in Sharma et al. (2022) to learn structure-preserving reduced-order models (ROMs) for Hamiltonian systems. The method constructs a low-dimensional model using only data and knowledge of the functional form of the Hamiltonian. The resulting ROMs preserve the intrinsic structure of the system, ensuring that the mechanical and physical properties of the system are maintained. In this work, we extend this approach to port-Hamiltonian systems, which generalize Hamiltonian systems by including energy dissipation, external input, and output. Based on snapshots of the system’s state and output, together with the information about the functional form of the Hamiltonian, reduced operators are inferred through optimization and are then used to construct data-driven ROMs. To further alleviate the complexity of evaluating nonlinear terms in the ROMs, a hyper-reduction method via discrete empirical interpolation is applied. Accordingly, we derive error estimates for the ROM approximations of the state and output. Lastly, we demonstrate the structure preservation, as well as the accuracy of the proposed port-Hamiltonian operator inference framework, through numerical experiments on a linear mass–spring-damper problem and a nonlinear Toda lattice problem.
97 MATHEMATICS AND COMPUTING↗
MXenoids: Generalization of MXene-Inspired Covalent Surface Modifications Across Two-Dimensional Materials
The ability to perform versatile covalent surface modifications in two-dimensional (2D) inorganic materials marks a significant advance in the functionalization of this broad family of materials. One particularly successful example of 2D materials with chemically modifiable surfaces are 2D transition metal carbides and nitrides (MXenes). MXenes' strong in-plane metal-carbon bonds and labile surface metal-halide bonds create altogether unprecedented opportunities for versatile postsynthetic modifications and assembling complex materials, including various organic-inorganic hybrids. Here, we demonstrate the general applicability of this surface modification strategy to non-MXene halide-terminated 2D materials, termed MXenoids. These surface modifications enable compositional and electronic structure engineering, introduce chiral hybrid organic-inorganic structures, and photoluminescence ranging from near-IR to blue. This study highlights the avenue of surface chemistry-driven materials design, enhancing the functional capabilities of 2D materials.
Zhou, Chenkun [University of Chicago, IL (United S↗
Role of water model on ion dissociation at ambient conditions
In this work, we study ion pair dissociation in water at ambient conditions using a combination of classical and ab initio approaches. The goal of this study is to disentangle the sources of discrepancy observed in computed potentials of mean force. In particular, we aim to understand why some models favor the stability of solvent-separated ion pairs vs contact ion pairs. We found that some observed differences can be explained by non-converged simulation parameters. However, we also unveil that for some models, small changes in the solution density can have significant effects on modifying the equilibrium balance between the two configurations. We conclude that the thermodynamic stability of contact and solvent-separated ion pairs is very sensitive to the dielectric properties of the underlying simulation model. In general, classical models are very robust in providing a similar estimation of the contact ion pair stability, while this is much more variable in density functional theory-based models. The barrier to transition from the solvent-separated to contact ion pair is fundamentally dependent on the balance between electrostatic potential energy and entropy. This reflects the importance of water intra- and inter-molecular polarizability in obtaining an accurate description of the screened ion–ion interactions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Magnus method for electronic structure calculations at extreme conditions
We present the application of Magnus based methods to the solution of first order coupled ordinary differential equations in High Energy Density (HED) physics applications. Our focus is on the application to quantum mechanical methods, specifically on the solution of the radial Dirac equation for real and complex energies. HED applications require accurate solutions across a wide range of spatial and energy domains, including regimes where the solutions exhibit pronounced oscillatory behavior. Such cases pose significant computational challenges. We demonstrate that Magnus-based integrators can efficiently and accurately address these challenges. We discuss the implementation of the Magnus method for the solution of the radial Dirac equation, including practical considerations such as the evaluation of matrix exponentials, numerical integration, error estimation, and adaptive step size control. We also discuss the application of these methods to complex energy Green’s function techniques and the efficient approximation of integrals of the solutions relevant to HED electronic structure calculations. Here, we demonstrate the accuracy and robustness of the resulting method in applications to the free-particle case, for which analytic solutions are available for comparison, as well as the challenging case of gold at HED conditions.
general physics↗