Parameter-free Framework Research Articles

A Green's Function Approach for Determining Surface Induced Broadening and Shifting of Molecular Energy Levels.

Upon adsorption of a molecule onto a surface, the molecular energy levels (MELs) broaden and change their alignment. This phenomenon directly affects electron transfer across the interface and is, therefore, a fundamental observable that influences electrochemical device performance. Here, we propose a rigorous parameter-free framework, built upon the theoretical construct of Green's functions, for studying the interface between a molecule and a bulk surface and its effect on MELs. The method extends beyond the usual wide-band limit approximation, and its generality allows its use with any level of electronic structure theory. We demonstrate its ability to predict the broadening and shifting of MELs as a function of intramolecular coupling, molecule/surface coupling, and the surface density of states for a molecule with two MELs adsorbed on a one-dimensional model metal surface. The new approach could help provide guidelines for the design and experimental characterization of electrochemical devices with optimal electron transport.

Intermediate polaronic charge transport in organic crystals from a many-body first-principles approach

Charge transport in organic molecular crystals (OMCs) is conventionally categorized into two limiting regimes − band transport, characterized by weak electron-phonon (e-ph) interactions, and charge hopping due to localized polarons formed by strong e-ph interactions. However, between these two limiting cases there is a less well understood intermediate regime where polarons are present but transport does not occur via hopping. Here we show a many-body first-principles approach that can accurately predict the carrier mobility in this intermediate regime and shed light on its microscopic origin. Our approach combines a finite-temperature cumulant method to describe strong e-ph interactions with Green-Kubo transport calculations. We apply this parameter-free framework to naphthalene crystal, demonstrating electron mobility predictions within a factor of 1.5−2 of experiment between 100 and 300 K. Our analysis reveals the formation of a broad polaron satellite peak in the electron spectral function and the failure of the Boltzmann equation in the intermediate regime.

An optimum thermoelectric figure of merit using Ge2Se2 monolayer: An ab-initio approach

It is found that many two-dimensional chalcogenides are exhibiting a superlative thermoelectric behavior because of their versatile characters in terms of stability, conductivity, bandgap tunability, etc. In this paper, the thermoelectric properties of monolayer Ge2Se2 have been calculated using first-principles calculations with all involved electrical and thermal transport properties in the parameter-free framework. It has been found that the Ge2Se2 offers a bandgap of 1.13 eV with a sufficiently high thermoelectric coefficient. The thermoelectric transport parameters have been calculated by solving the linearized Boltzmann Transport Equation and found optimum to qualify for good thermoelectric materials. The investigated material exhibit outstanding thermoelectric performance in terms of an ultra low lattice thermal conductivity of the order of 0.5 Wm−1K−1 and TE Figure of merit around two (2) at 1000 K. For better accuracy in results, we employed hybrid exchange–correlation (HSE06) throughout the calculations and, instead of approximating the relaxation time, computed the accurate relaxation time using the deformation potential approach. The research findings prove its excellent behavior and worthy guideline for the experimentalists looking for materials with high FoM to design thermoelectric devices.

A parameter-free framework for calibration enhancement of near-infrared spectroscopy based on correlation constraint

A new parameter-free framework for calibration enhancement (PFCE) was proposed for dealing with the near-infrared (NIR) spectral inconsistency and maintaining the prediction ability of the calibration model under different conditions. The calibration issues encountered in the maintenance with or without using standards, and even the enhancement between instruments have been thoroughly addressed. The general calibration maintenance/enhancement cases were formulated into non-supervised PFCE (NS-PFCE), semi-supervised PFCE (SS-PFCE), and full-supervised PFCE (FS-PFCE). The NS-PFCE made use of both the provided master and slave spectra of standard samples to construct a maintained calibration slave model by implementing a correlation constraint on the regression coefficients. The SS-PFCE and FS-PFCE methods integrated the slave spectra and reference information of standard samples at the same time into the slave spectral calibration, and thus a maintenance or enhancement model could be achieved for the slave spectra, in particular measured on different instruments. The use of dataset1 comprised of 655 pharmaceutical tablets measured on two NIR spectrometers and datset2 containing 117 plant leaf samples in two mesh sizes has demonstrated that the PFCE framework had a significant effect on enhancing the predictions of the slave spectra in the models. The root mean square errors of prediction (RMSEPs) of either active pharmaceutical ingredient (API) amount in tablets or reducing sugar content in plant leaf samples from the slave spectra approached to or were lower than those values predicted from the master spectra in the master models established with the partial least-squares (PLS) regression method. The advantage of PFCE was parameter-free and efficient. First, the method could be flexibly employed in scientific or applicative environment with no regard to the parameter specification. Second, the performance of NS-PFCE was comparable to the classical calibration maintenance methods, yet the SS-PFCE and FS-PFCE could enhance the prediction ability to a level widely considered as the upper boundary of classical calibration maintenance methods reached.The source code of the method is available at https://github.com/JinZhangLab/PFCE.

Correlated excited states in the narrow band gap semiconductor FeSi and antiferromagnetic screening of local spin moments

The physical properties of the semiconductor FeSi with very narrow band gap, anomalous behavior of the magnetic susceptibility and metal-insulator transition at elevated temperatures attract gross interest due to the still controversial theoretical understanding of their origin. On one side the purely band like mechanism of the gap formation in FeSi at low temperature is well established, on other side a number of experiments and their theoretical interpretation suggest a rich physics of strong correlations at finite temperature. In this work we use an ab-initio scheme based on the Random Phase Approximation and Local Spin Density Approximation (RPA@LSDA) to reveal the role of the electron correlation effects in FeSi extending it by applying a fixed spin moment constraint. In the parameter free framework we show that correlation effects essentially alter the one-electron LSDA results leading to the formation of an additional state with finite magnetic moment on Fe, whose energy is almost degenerate with the non-magnetic ground state. This explains the results of high field experiments, which found a first-order meta-magnetic phase transition into a metallic ferromagnetic state. Our results suggest a strongly correlated nature of the low-energy excitations in FeSi. From our super-cells calculations we reveal that these excitations are local and exhibit a Kondo-like behavior since a strong antiferromagnetic screening is present.

Heterogeneous anomaly detection in social diffusion with discriminative feature discovery

Social diffusion is a dynamic process of information propagation within social networks. In this paper, we study social diffusion from the perspective of discriminative features, a set of features differentiating the behaviors of social network users. We propose a new parameter-free framework based on modeling and interpreting of discriminative features that we have created, named HADISD. It utilizes a probability-distribution-based parameter-free method to identify the maximum vertex set with specified features. Using the maximum vertext set, a probability-distribution-based optimization approach is applied to find the minimum number of vertices in each feature category with the maximum discriminative information. HADISD includes an incremental algorithm to update the discriminative vertex set over time. The proposed model is capable of addressing anomaly detection in social diffusion, and the results can be leveraged for both spammer detection and influence maximization. The findings from our extensive experiments on four real-life datasets show the efficiency and effectiveness of the proposed scheme.

Parameter-free image segmentation with SLIC

Abstract In this paper, we develop a parameter-free image segmentation framework using Simple Linear Iterative Clustering (SLIC) and Extreme Learning Machines (ELM). SLIC requires a single parameter, the number of centroids k. Our framework, called PF-SLIC (Parameter-Free SLIC) uses an ELM to predict the optimal k, generating a parameter-free framework. PF-SLIC and its streaming variant SPF-SLIC (Streaming PF-SLIC) achieve performance comparable to other models on ultra-high-definition (4K) images and streams, with runtimes orders of magnitude lower.

ΔΔ ABC partner in theND̅system

We perform a study of the N ¯ D interaction within a chiral constituent quark model. This model has been completely tight in the description of the NN interaction and the baryon and meson spectra, therefore provides a parameter-free framework from where to address the problem of the charm −1 two hadron systems. We predict the existence of a unique bound state, ¯ D ∗ with (T, S) = (1,5/2), that would appear in the scattering of ¯ D mesons on nucleons as a D wave state. This resonance resembles our findings in the system, that offered a plausible explanation to the cross section of double-pionic fusion reactions through the so-called ABC effect.

Gauge formulation of general relativity using conformal and spin symmetries

The gauge symmetry inherent in Maxwell's electromagnetics has a profound impact on modern physics. Following the successful quantization of electromagnetics and other higher order gauge field theories, the gauge principle has been applied in various forms to quantize gravity. A notable development in this direction is loop quantum gravity based on the spin-gauge treatment. This paper considers a further incorporation of the conformal gauge symmetry in canonical general relativity. This is a new conformal decomposition in that it is applied to simplify recently formulated parameter-free construction of spin-gauge variables for gravity. The resulting framework preserves many main features of the existing canonical framework for loop quantum gravity regarding the spin network representation and Thiemann's regularization. However, the Barbero-Immirzi parameter is converted into the conformal factor as a canonical variable. It behaves like a scalar field but is somehow non-dynamical since the Hamiltonian constraint does not depend on its momentum. The essential steps of the mathematical derivation of this parameter-free framework for the spin-gauge variables of gravity are spelled out. The implications for the loop quantum gravity programme are briefly discussed.

Density dependent relativistic mean field theory in deformed nuclei

We perform density dependent relativistic mean field calculations for deformed nuclei in order to examine the possibility of describing nuclear deformation properties in a parameter-free framework. The results are compared with experimental data and with results from earlier phenomenological relativistic mean field calculations using nonlinear terms in the {sigma} field. {copyright} {ital 1998} {ital The American Physical Society}

A behavioral approach to linear exact modeling

The behavioral approach to system theory provides a parameter-free framework for the study of the general problem of linear exact modeling and recursive modeling. The authors present the solution of the (continuous-time) polynomial-exponential time series modeling problem. Both recursive and nonrecursive solutions are provided and classified according to properties like complexity and controllability. It is shown, in particular, that recursive modeling corresponds to updating by means of a cascade inter-connection of systems. As a special case, the solution of several other problems, such as rational interpolation, realization, and modeling of arbitrary discrete-time time series, is obtained.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>