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Abstract A dual oxidative approach using O 2 plasma followed by treatment with H 2 O 2 to impart oxygen functional groups onto the surface of a graphite felt electrode. When used as electrodes for an all‐vanadium redox flow battery (VRB) system, the energy efficiency of the cell is enhanced by 8.2 % at a current density of 150 mA cm −2 compared with one oxidized by thermal treatment in air. More importantly, by varying the oxidative techniques, the amount and type of oxygen groups was tailored and their effects were elucidated. It was found that O−C=O groups improve the cells performance whereas the C−O and C=O groups degrade it. The reason for the increased performance was found to be a reduction in the cell overpotential after functionalization of the graphite felt electrode. This work reveals a route for functionalizing carbon electrodes to improve the performance of VRB cells. This approach can lower the cost of VRB cells and pave the way for more commercially viable stationary energy storage systems that can be used for intermittent renewable energy storage.
We present a Fourier neural network (FNN) that can be mapped directly to the Fourier decomposition. The choice of activation and loss function yields results that replicate a Fourier series expansion closely while preserving a straightforward architecture with a single hidden layer. The simplicity of this network architecture facilitates the integration with any other higher-complexity networks, at a data pre- or postprocessing stage. We validate this FNN on naturally periodic smooth functions and on piecewise continuous periodic functions. We showcase the use of this FNN for modeling or solving partial differential equations with periodic boundary conditions. The main advantages of the current approach are the validity of the solution outside the training region, interpretability of the trained model, and simplicity of use.
Metal-organic frameworks (MOFs) have recently gained wide interest as candidate materials for nuclear waste immobilization. While the fundamental thermodynamic properties, such as the substitution energies determine the favorability of radionuclide sequestration by utilization of a MOF matrix, the studies of MOF electronic structure reveal the role of d-, and/or f-electrons on changes in physical properties of actinide-containing materials. We use density functional theory (DFT) calculations to investigate the electronic structures of Zr-, Th-, and U-MOFs, including their electronic band structures and, where appropriate, their magnetic properties. We employ various DFT methods including DFT+U, collinear spin-polarization, spin-orbit coupling, and different flavors of exchange-correlation functionals to assess the robustness to the specific exchange-correlation functional. Unlike the Zr-, and Th-MOFs, the U-MOF is found to be sensitive to electron localization and spin; hence we explore the magnetic structure of the U-MOF in further detail.
Surface coating has been identified as an effective approach for enhancing the capacity retention of layered structure cathode. However, the underlying operating mechanism of such a thin coating layer, in terms of surface chemical functionality and capacity retention, remains unclear. In this work, we use aberration-corrected scanning transmission electron microscopy and high-efficiency spectroscopy to probe the delicate functioning mechanism of an Al2O3 coating layer on a Li1.2Ni0.2Mn0.6O2 cathode. We discovered that in terms of surface chemical function, the Al2O3 coating suppresses the side reaction between the cathode and the electrolyte during battery cycling. At the same time, the Al2O3 coating layer also eliminates the chemical reduction of Mn from the cathode particle surface, therefore preventing the dissolution of the reduced Mn into the electrolyte. In terms of structural stability, we found that the Al2O3 coating layer can mitigate the layer to spinel phase transformation, which otherwise will be initiated from the particle surface and propagate toward the interior of the particle with the progression of battery cycling. The atomic to nanoscale effects of the coating layer observed here provide insight into the optimized design of a coating layer on a cathode to enhance the battery properties.
The kinetics of biogeochemical processes in natural and engineered environmental systems are typically described using Monod-type or modified Monod-type models. These models rely on biomass as surrogates for functional enzymes in microbial community that catalyze biogeochemical reactions. A major challenge to apply such models is the difficulty to quantitatively measure functional biomass for constraining and validating the models. On the other hand, omics-based approaches have been increasingly used to characterize microbial community structure, functions, and metabolites. Here we proposed an enzyme-based model that can incorporate omics-data to link microbial community functions with biogeochemical process kinetics. The model treats enzymes as time-variable catalysts for biogeochemical reactions and applies biogeochemical reaction network to incorporate intermediate metabolites. The sequences of genes and proteins from metagenomes, as well as those from the UniProt database, were used for targeted enzyme quantification and to provide insights into the dynamic linkage among functional genes, enzymes, and metabolites that are necessary to be incorporated in the model. The application of the model was demonstrated using denitrification as an example by comparing model-simulated with measured functional enzymes, genes, denitrification substrates and intermediates
Accurately predicting the spin splitting energy of chemical species is important for understanding their reactivity and magnetic properties, but it is very challenging, especially for molecules containing transition metals. One impediment to progress is the scarcity of accurate benchmark data. Here we report a set of calculations designed to yield reliable benchmarks for simple transition-metal complexes that can be used to test density functional methods that are affordable for large systems of more practical interest. Various wave function methods are tested against experiment for Fe 2+ , Fe 3+ , and Co 3+ , including CASSCF, CASPT2, CASPT3, MRCISD, MRCISD+Q, ACPF, AQCC, CCSD(T), and CASPT2/CCSD(T) and also a new method called CASPT2.5, which is performed by taking the average of the CASPT2 and CASPT3 energies. Furthermore, we find that MRCISD+Q, ACPF, and AQCC require smaller active spaces for good accuracy than are required by CASPT2 and CASPT3, and this aspect may be important for calculations on larger molecules; here we find that CASPT2.5 extrapolated to a complete basis set is the most suitable method—in terms of computational cost and in terms of accuracy on monatomic systems—and therefore we chose this method for molecular benchmarks. Then Kohn–Sham density functional calculations with 60 exchange-correlation functionals are tested for FeF 2 , FeCl 2 , and CoF 2 . We find that MN15-L, M06-SX, and revM06 have very good agreement with CASPT2.5 benchmarks in terms of both the spin splitting energy and the optimized geometry for each spin state. In addition, we recommend def2-TZVP as the most suitable basis set to perform density functional calculations for molecular spin splitting energies; extra polarization functions in the basis set do not help to increase the accuracy of the spin splitting energy in KS calculations.
The Green’s function coupled cluster (GFCC) method, originally proposed in the early 1990s, is a powerful many-body tool for computing and analyzing the electronic structures of molecular structures and periodic systems, especially when electrons are strongly correlated. However, in order for the GFCC method to become an approach that can be routinely used in the electronic structure calculations, more robust linear algebraic techniques and approximations need to be employed to reduce its extremely high computational overhead. In our recent studies, we showed that the GFCC equation can be numerically solved by seeking solutions of multiple linear systems in the frequency regime of interest, which can be easily distributed in a massively parallel environment, and broaden the avenue for more state-of-the-art numerical linear algebraic tools associated with multiple linear systems to be kicked in to this field. In the present pursuit of this practice, we show a successful application of model order reduction (MOR) techniques in the GFCC framework. Briefly speaking, for a frequency regime of interest that requires a high resolution of spectral function, instead of solving GFCC linear equation in the original dimension for every single frequency point, an easily-solvable linear system model with reduced dimension can be built upon projecting the original GFCC linear system into a subspace, from which the interpolation and extrapolation can give a reasonable approximation to the results of the original GFCC linear equations. Here, we show that the subspace can be properly constructed in an iterative manner from the auxiliary vectors of the GFCC linear equations at some select frequencies inside the frequency regime. During the iterations, the quality of the subspace, as well as the linear system model, can be systematically improved. The approach is tested in this work in terms of the efficiency and accuracy of computing spectral functions for some typical molecular systems including carbon monoxide, 1,3-butadiene, benzene, and adenine molecules. As a byproduct, the high quality linear system model is also found to be able to provide high quality initial guess for the existing linear solver to improve the convergence performance.
The way to improve Kohn–Sham density functional theory is to improve the exchange–correlation functionals, and functionals have been successively improved by adding new ingredients, especially local spin density gradients, nonlocal Hartree–Fock exchange, and local meta terms based on kinetic energy density. Here, we present a new kind of functional obtained by adding rung-3.5 terms to a functional including local gradients, local meta terms, and range-separated Hartree–Fock exchange. A rung-3.5 term has short-range nonlocality designed to account for nondynamic correlation; we add two kinds of rung-3.5 terms, one kind modeled on position-dependent Hartree–Fock exchange and another modeled on the spin density at a point interacting with the opposite-spin exchange hole at the same point. Here, optimization of the functional yields broad accuracy for both ground states and excited states with especially significant improvement for systems with strong correlation.
Oxide–water interfaces are ubiquitous, with many applications in industry and the environment, yet there is a great deal of controversy over their properties and microscopic structure. This controversy stems, in part, from the unique H-bond networks formed at different surface terminations and mineral compositions. Density functional theory simulations of these interfaces require an accurate description of both the oxide mineral and water in diverse H-bond environments. Thus, herein we simulate the Al 2 O 3 (001)–H 2 O interface using the PBE, PBE-TS, RPBE, SCAN, and HSE06-TS functionals to determine how calculated interfacial properties depend on the choice of functional. We find that the structure of the first few layers of water at the surface is determined by electron correlation in a way that cannot be approximated using semiemipirical van der Waals corrections. Of the functionals investigated, we find that SCAN yields the most accurate interfacial structure, dynamics, and sum frequency generation spectrum. Furthermore, SCAN leads to a reduction in the order of the 2D H-bond network of water at the alumina surface predicted by GGA functionals, leading to a significant decrease in the anisotropy of the diffusion coefficient at the surface. We emphasize the importance of using a functional which accurately describes electron correlation for more complex oxides, such as transition-metal oxides, where electron correlation may play an even greater role in determining the structure and dynamics of the oxide–water interface.
Cell type-resolved proteome analyses of the brain, heart and liver have been reported, however a similar effort on the lipidome is currently lacking. Here we applied liquid chromatography-tandem mass spectrometry to characterize the lipidome of major lung cell types isolated from human donors, representing the first lipidome map of any organ. We coupled this with cell type-resolved proteomics of the same samples (available at Lungmap.net). Complementary proteomics analyses substantiated the functional identity of the isolated cells. Lipidomics analyses showed significant variations in the lipidome across major human lung cell types, with differences most evident at the subclass and intra-subclass (i.e. total carbon length of the fatty acid chains) level. Further, lipidomic signatures revealed an overarching posture of high cellular cooperation within the human lung to support critical functions. Our complementary cell type-resolved lipid and protein datasets serve as a rich resource for analyses of human lung function.
This article presents a perspective on Kohn-Sham density functional theory (KS-DFT) for electronic structure calculations in chemical physics. This theory is in widespread use for applications to both molecules and solids. We pay special attention to several aspects where there are both concerns and progress toward solutions. These include: The treatment of open-shell and inherently multiconfigurational systems (the latter are often called multireference systems and are variously classified as having strong correlation, near-degeneracy correlation, or high static correlation; KS-DFT must treat these systems with broken-symmetry determinants). The treatment of noncovalent interactions. The choice between developing new functionals by parametrization, by theoretical constraints, or by a combination. The ingredients of the exchange-correlation functionals used by KS-DFT, including spin densities, the magnitudes of their gradients, spin-specific kinetic energy densities, nonlocal exchange (Hartree-Fock exchange), nonlocal correlation, and subshell-dependent corrections (DFT+U). The quest for a universal functional, where we summarize some of the success of the latest Minnesota functionals, namely MN15-L and MN15, which were obtained by optimization against diverse databases. Time-dependent density functional theory, which is an extension of DFT to treat time-dependent problems and excited states. Furthermore, the review is a snapshot of a rapidly moving field, and—like Marcel Duchamp—we hope to convey progress in a stimulating way.
Abstract This paper presents stellar mass functions and i-band luminosity functions for Sloan Digital Sky Survey (SDSS) galaxies with i < 21 using clustering redshifts. From these measurements, we also compute targeting completeness measurements for the Baryon Oscillation Spectroscopic Survey (BOSS). Clustering redshifts is a method of obtaining the redshift distribution of a sample of galaxies with only photometric information by measuring the angular cross-correlation with a spectroscopic sample in different redshift bins. We construct a spectroscopic sample containing data from the BOSS + eBOSS surveys, allowing us to recover redshift distributions from photometric data out to z ≃ 2.5. We produce k-corrected i-band luminosity functions and stellar mass functions by applying clustering redshifts to SDSS DR8 galaxies in small bins of colour and magnitude. There is little evolution in the mass function between 0.2 < z < 0.8, implying that the most massive galaxies form most of their mass before z = 0.8. These mass functions are used to produce stellar mass completeness estimates for the BOSS, giving a stellar mass completeness of $80{{\ \rm per\ cent}}$ above M⋆ > 1011.4 between 0.2 < z < 0.7, with completeness falling significantly at redshifts higher than 0.7, and at lower masses. Large photometric data sets will be available in the near future (DECaLS, DES, Euclid), so this and similar techniques will become increasingly useful in order to fully utilize these data.
We present a study of the τ polarization in charged-current quasielastic (anti)neutrino-nucleus scattering. The spectral function formalism is used to compute the differential cross section and the polarization components for several kinematical setups, relevant for neutrino-oscillation experiments. The effects of the nuclear corrections in these observables are investigated by comparing the results obtained using two different realistic spectral functions, with those deduced from the relativistic global Fermi gas model, where only statistical correlations are accounted for. We show that the spectral functions, although they play an important role when predicting the differential cross sections, produce much less visible effects on the polarization components of the outgoing τ.
Here, we present calculations of the 40 Ca transverse response function obtained from coupled-cluster theory used in conjunction with the Lorentz integral transform method. We employ nuclear forces derived at next-to-next-to leading order in chiral effective field theory with and without Δ degrees of freedom. We first benchmark this approach on the 4 He nucleus and compare both the transverse sum rule and the response function to earlier calculations based on different methods. As expected from the power counting of the chiral expansion of electromagnetic currents and from previous studies, our results retaining only one-body term underestimate the experimental data for 4 He by about 20%. However, when the method is applied to 40 Ca at the same order of the expansion, response functions do not lack strength and agree well with the world electron scattering data. We discuss various sources of theoretical uncertainties and comment on the comparison of our results with the available experiments.
Unveiling both the presence and nature of point defects is one of the biggest challenges in condensed matter physics and materials science. Particularly in complex oxides, even a minute amount of unavoidable point defects could generate novel physical phenomena and functions, such as visible light emission and ferroelectricity, yet it remains elusive to clearly identify such point defects. Here, taking SrTiO3 as a model system, we show that iterative feedback among atomic-layer- and stoichiometry-controlled thin-film epitaxy, hybrid density functional theory, and high-resolution cathodoluminescence spectroscopy allows for the identification of a functional cationic defect, the Ti antisite (TiSr) defect. Our cathodoluminescence measurements reveal sub-band-gap luminescence, whose spectral fine structures show excellent quantitative agreement, as well as a one-to-one correspondence, with the theoretically predicted optical transitions from intrinsic point defects such as TiSr. Guided by the theory and spectroscopic results, we also control a cation stoichiometry, and it in turn results in good systematics in cathodoluminescence spectra. Not limited to the identification of TiSr, this approach allows for more reliable, self-consistent defect study, and provides critical insight into a microscopic picture of point defects in complex oxides.
Purpose: Functional lung avoidance radiotherapy promises optimized therapy planning by minimizing dose to well-functioning lung and maximizing dose to the rest of the lung. Patients with NSCLC commonly present with co-morbid COPD and heterogeneously distributed ventilation abnormalities stemming from emphysema, airways disease, and tumour burden. We hypothesized that pulmonary functional imaging methods may be used to optimize radiotherapy plans to avoid regions of well-functioning lung and significantly improve outcomes like quality-of-life and survival. To ascertain the utility of functional lung avoidance therapy in clinical practice, we measured COPD phenotypes in NSCLC patients enrolled in a randomized-controlled-clinical-trial prior to curative intent therapy. Methods: Thirty stage IIIA/IIIB NSCLC patients provided written informed consent to a randomized-controlled-clinical-trial ( http://clinicaltrials.gov/ct2/show/NCT02002052 ) comparing outcomes in patients randomized to standard or image-guided radiotherapy. Hyperpolarized noble gas MRI ventilation-defect-percent (VDP) (Kirby et al, Acad Radiol, 2012) as well as CT-emphysema measurements were determined. Patients were stratified based on quantitative imaging evidence of ventilation-defects and emphysema into two subgroups: 1) tumour-specific ventilation defects only (TSD), and, 2) tumour-specific and other ventilation defects with and without emphysema (TSD{sub VE}). Receiver-operating-characteristic (ROC) curves were used to characterize the performance of clinical measures as predictors of the presence of non-tumour specific ventilation defects. Results: Twenty-one out of thirty subjects (70%) had non-tumour specific ventilation defects (TSD{sub VE}) and nine subjects had ONLY tumour-specific defects (TSD). Subjects in the TSD{sub VE} group had significantly greater smoking-history (p=.006) and airflow obstruction (FEV{sub 1}/FVC) (p=.001). ROC analysis demonstrated an 87% classification rate for smoking pack-years, 90% for FEV{sub 1}/FVC, and 56% for tumour RECIST measurements for identifying patients with non-tumour and tumour-specific ventilation abnormalities. Conclusion: 70% of NSCLC patients had ventilation abnormalities stemming from emphysema, airways disease and tumour burden. Smoking-history and airflow obstruction, but not RECIST, identified NSCLC patients with ventilation abnormalities appropriate for functional lung avoidance therapy.