Green Function Research Articles

Spin polarization in a collinear antiferromagnetic molecular wire predicted by first-principles calculations

A collinear antiferromagnetic molecular wire with zero total magnetic moments based on 1,3-diphenylpropynylidene radicals was sandwiched between two nonmagnetic Al leads. The transport characteristics with spin-polarization for this molecular junction were performed using an first-principles method based on density functional theory combined with non-equilibrium Green's functions. Reversible and high spin polarization was obtained in this collinear antiferromagnetic molecular wire, which was originated from that the bias voltage broke the symmetry of spin sublattices. Especially, the sign of spin polarization could be adjusted by changing the bias. Our calculations greatly contribute for developing novel antiferromagnetic spintronics devices with single molecular scale.

A semi-analytical approach for site-city interaction under oblique incident SH waves

In this paper, a semi-analytical approach was proposed for investigating the site-city interactions (SCI). The site was modelled as a horizontal layered half-space, while the building was represented as a collection of shear wall structures fixed on the surface of half-space. The total wave field was considered as a combination of free field and scattering wave field generated by buildings, simulated by direct stiffness method and Green's function, respectively. The coupling between the site and the city is achieved through the displacement continuity conditions at the bottom of the building. Finally, the impact and some influencing factors of SCI effect on site and buildings were studied. It is found that the SCI effect has a significant impact on surface displacement and building response. The SCI effect typically reduces surface displacement near cities and the amplitude of relative displacement of buildings, while increases the seismic duration of buildings. However, this influence will be affected by the incident angle, building layout, building height, and building spacing, so these factors should be comprehensively considered when analyzing the SCI effect. Through the case studies, it is demonstrated that this method can quickly calculate SCI models with complex factors without being limited by the number and thickness of soil layers, incidence angles, and different sizes and spacing of buildings.

The Effect of Corporate Social Responsibility on Environmental Performance in China’s Manufacturing Industry: The Mediating Role of Environmental Strategy and Green Innovation

Within the ever-changing manufacturing landscape of China, corporate social responsibility (CSR) is a key factor influencing environmental performance. Knowing the relationship between corporate social responsibility (CSR) efforts and environmental results is crucial as environmental concerns throughout the world grow more pressing. This research explores the complex relationship between CSR practices and environmental performance, focusing on how green innovation and environmental strategy function as mediating factors. The urgent need to prevent industrial environmental consequences in the face of fast economic expansion highlights the need for this investigation. China, a major force in world manufacturing, must balance environmental sustainability with economic expansion. In addition to improving a company’s reputation, effective CSR initiatives are essential for promoting sustainable development. Through an analysis of the mediating functions of green innovation, which propels technological developments, and environmental strategy, which comprises policies and practices, we clarify how proactive CSR methods can ignite revolutionary shifts towards more environmentally friendly manufacturing processes. In order to create a harmonious balance between industrial growth and ecological stewardship, this research aims to provide theoretical insights as well as practical implications for industry leaders and policymakers. It achieves this by promoting strategic alignment between CSR goals and environmental imperatives.

A simple and fast method to calculate the coil currents and the external poloidal flux and magnetic field for fixed boundary equilibria

Abstract A simple and fast method to calculate the coil currents and the exter-
nal poloidal flux and magnetic field consistent with a given internal MHD
equilibrium and coil geometry is presented. The constrained optimization
technique employed allows to fix the exact position of the X-points. The ex-
ternal poloidal flux and fi eld are calculated using Green's functions expressed
in terms of elliptic integrals that are calculated using a fast and accurate rou-
tine. The calculation can be limited to the region between the plasma and
the device wall. An example for a double null con guration is presented.

First-principles calculations of cubic boron arsenide surfaces

The properties of cubic boron arsenide (c-BAs) (100), (110), and (111) surfaces are investigated by performing first-principles calculations using the slab and Green's function surface models with different terminals. The (111) surface with As-termination is found to be the most stable structure among the studied surfaces, with its lowest surface energy (1.70–1.92 J m−2) and largest surface density (20.24 nm−2). The electronic affinity of these surfaces lie in the range 4.62–6.17 eV, which is higher than that of common semiconductor materials, such as silicon (4.05 eV) and germanium (4.13 eV), implying that the electrons at the bottom of the conduction band require more energy to escape. The surface states of the structures with As-termination in the surface band structures are generally more numerous and extended than those with B-termination. The absorption peak of the bulk c-BAs is located in the ultraviolet region, and the light absorption ranges of the surfaces are significantly extended compared with the bulk c-BAs, due to the surface states inside the bandgap.

Giant tunneling resistance and robust switching behavior in ferroelectric tunnel junctions of WS2/Ga2O3 heterostructures: The influence of metal–semiconductor contacts

The ferroelectric tunneling junctions (FTJs) are widely recognized as one of the non-volatile memories with significant potential. Ferroelectricity usually fades away as materials are thinned down below a critical value, and this problem is particularly acute in the case of shrinking device sizes, thus attracting attention to two-dimensional ferroelectric materials (2DFEMs). In this work, we designed 2D ferroelectric Ga2O3-based FTJs with out-of-plane polarization, and the influence of metal–semiconductor contact in the electrode region on the system is considered. Here, using density functional theory combined with the non-equilibrium Green's function approach to quantum transport calculations, we demonstrate robust ferroelectric polarization-controlled switching behavior between metallic and semiconducting states in Ga2O3/WS2 ferroelectric heterostructures. The potential barrier of the metal–semiconductor contact in the electrode region is lower than that of the intrinsic material, thereby resulting in an increased probability of electron tunneling. Our results reveal the crucial role of 2DFEMs in the construction of FTJs and highlight the significant impact of electrode contact types on performance. This provides a promising approach for developing high-density ferroelectric memories based on 2D ferroelectric semiconductor heterostructures.

Edge state regulation and interfacial design on spin transport properties of VC2-based nanoscale devices

Edge state and interfacial design are efficient strategies to regulate the spin-transport properties of nanoscale devices. Spin-polarized transport properties of VC2 nanoribbon device and poly-(terphenylene-butadiynylene) PTB molecular junctions are studied by using density functional theory (DFT) and non-equilibrium Green function. Results show good self-selected filtering properties for spin-up current are highly suppressed, where there is only spin-down current that can propagate through the scattering region of such a nanoribbon device. What needs to be pointed out is that spin-down current exhibits an obvious negative differential resistance effect. Current and transmission spectrum peaks are significantly weakened, and the negative differential resistance effect disappears after a PTB molecule is embedded between two semi-infinite VC2 nanoribbon electrodes. This work provides a basis for improving the design and method of spintronic devices.

Retarded and advanced Green functions for first-order differential equations

Retarded and advanced Green functions are examined through the lens of linear first-order ordinary differential equations. They are constructed for a finite interval with emphasis on the imposition of homogeneous Dirichlet boundary conditions at the interval ends. It is shown that both types of Green functions exhibit the property of facilitating solutions.

The pentatricopeptide repeat protein DG1 promotes the transition to bilateral symmetry during Arabidopsis embryogenesis through GUN1-mediated plastid signals.

During Arabidopsis embryogenesis, the transition of the embryo's symmetry from radial to bilateral between the globular and heart stage is a crucial event, involving the formation of cotyledon primordia and concurrently the establishment of a shoot apical meristem (SAM). However, a coherent framework of how this transition is achieved remains to be elucidated. In this study, we investigated the function of DELAYED GREENING 1 (DG1) in Arabidopsis embryogenesis using a newly identified dg1-3 mutant. The absence of chloroplast-localized DG1 in the mutants led to embryos being arrested at the globular or heart stage, accompanied by an expansion of WUSCHEL (WUS) and SHOOT MERISTEMLESS (STM) expression. This finding pinpoints the essential role of DG1 in regulating the transition to bilateral symmetry. Furthermore, we showed that this regulation of DG1 may not depend on its role in plastid RNA editing. Nevertheless, we demonstrated that the DG1 function in establishing bilateral symmetry is genetically mediated by GENOMES UNCOUPLED 1 (GUN1), which represses the transition process in dg1-3 embryos. Collectively, our results reveal that DG1 functionally antagonizes GUN1 to promote the transition of the Arabidopsis embryo's symmetry from radial to bilateral and highlight the role of plastid signals in regulating pattern formation during plant embryogenesis.

Non-linear radiative response to patterned global warming due to convection aggregation and non-linear tropical dynamics

Abstract Climate responses to global warming exhibit large dependence on the spatial pattern of sea surface temperature (SST) changes. A Green’s function (GF) approach - predicting the global climate response to a complex SST pattern change as the linear superposition of the response to finite-area SST perturbations evaluated in isolation – has been used to systematically evaluate and understand the top of atmosphere (TOA) radiation response to patterned warming. However, in general the linear GF approach fails for TOA radiation reconstruction under future global warming scenarios in coupled models. Here we show that the linear superposition of global mean TOA radiation responses to large SST warming perturbations at multiple patches (the GF approach prediction) overestimates the actual response to simultaneous multi-patch perturbation. This is because the linear superposition overestimates tropical large-scale convection aggregation strengthening upon localized heating that enhances longwave radiative cooling, which is further explained by the overestimation of circulation response and associated horizontal water vapor transport. The non-additivity of TOA radiation response is caused by the non-additivity of convection aggregation, ultimately rooted in non-linear tropical dynamics. We also demonstrate that the prediction error of the GF approach grows with decreasing patch size (equivalently, increasing patch number). We conclude that using the GF approach to predict future climate change could overestimate longwave radiative cooling and underestimate (effective) climate sensitivity. Numerical experiments may be used to identify specific perturbation patterns where the errors are smaller than the signal. Our research also highlights that an increase in the degree of large-scale convection aggregation has a non-linear and negative feedback for mean warming.

Calculation of Green's functions for heat conduction in curved anisotropic media

AbstractSolving the inverse problems of heat conduction often requires performing a very large number of Green's function evaluations. This paper addresses the calculation of Green's functions in anisotropic curved media, such as composite lamina, where the principal axes of thermal conductivity follow the curved surface. We start with established exact series solutions for cylindrical convex and concave shapes. These solutions are extended to accommodate geometries of real‐world composite materials that do not form a closed surface like a cylinder. Unfortunately, the exact solutions have the form of an infinite series of sums or integrals and are computationally infeasible for the inverse problems of interest, especially for large radii of curvature. This motivates a perturbation solution that is accurate and computationally efficient at large radii of curvature. In addition, it motivates a phenomenological approximation that is extremely computationally efficient over a broad range of curvatures, but with some sacrifice in accuracy. These solutions are compared with exact solutions, with each other, and with numerical finite difference calculation. We identify regions in parameter space where the different approaches are preferable and where they lead to the same numerical result.

The starting vortices generated by bodies with sharp and straight edges in a viscous fluid

A two-dimensional body that moves suddenly in a viscous fluid can instantly generate vortices at its sharp edges. Recent work using inviscid flow theory, based on the Birkhoff–Rott equation and the Kutta condition, predicts that the ‘starting vortices’ generated by the sharp and straight edges of a body – i.e. the vortices formed immediately after motion begins – can be one of three distinct self-similar types. We explore the existence of these starting vortices for a flat plate and two symmetric Joukowski aerofoils immersed in a viscous fluid, using high-fidelity direct numerical simulations (DNS) of the Navier–Stokes equations. A lattice Green's function method is employed and simulations are performed for chord Reynolds numbers ranging from 5040 to 45 255. Vortices generated at the leading and trailing edges of the flat plate show agreement with the derived inviscid theory, for which a detailed assessment is reported. Agreement is also observed for the two symmetric Joukowski aerofoils, demonstrating the utility of the inviscid theory for arbitrary bodies. While this inviscid theory predicts an abrupt transition between the starting-vortex types, DNS shows a smooth transition. This behaviour occurs for all Reynolds numbers and is related to finite-time effects – there is a maximal time for which the (self-similar) starting vortices exist. We confirm the inviscid prediction that the leading-edge starting vortex of a flat plate can be suppressed dynamically. This has implications for the performance of low-speed aircraft such as model aeroplanes, micro air vehicles and unmanned air vehicles.

A systematic study of switching, optoelectronics, and gas‐sensitive properties of PCF‐graphene‐based nanodevices: Insights from DFT study

AbstractTwo‐dimensional materials exhibit significant potential and wide‐ranging application prospects owing to their remarkable tunability, pronounced quantum confinement effects, and notable surface sensitivity. The switching, optoelectronics, and gas‐sensitive properties of the new carbon material poly‐cyclooctatetraene framework (PCF)‐graphene were systematically studied using density functional theory combined with the nonequilibrium Green's function method. First, the diode device based on PCF‐graphene monolayer exhibited an impressive switching ratio of 106, demonstrating excellent diode characteristics. Moreover, in the investigation of the pin junction utilizing monolayer PCF‐graphene, it is noteworthy that significant photocurrent responses were observed in both the zigzag and armchair directions, specifically within the visible and ultraviolet regions. Finally, gas sensors employing monolayer and bilayer PCF‐graphene demonstrate significant chemical adsorption capabilities for NO and NO2. Notably, the maximum gas sensitivity for NO is achieved in monolayer PCF‐graphene, reaching 322% at a bias voltage of 1.0 V. Meanwhile, for bilayer PCF‐graphene‐based gas sensor, the maximum gas sensitivity reaches 52% at a bias voltage of 0.4 V. In addition, the study also examined the influence of various environmental conditions, specifically H2O, O, and OH, on the system under investigation. The obtained results emphasize the multifunctional properties of PCF‐graphene, exhibiting significant potential for various applications, including switching devices, optoelectronic devices, and gas sensors.

GPU-Enabled Exascale Quantum Transport Modeling of Carbon Nanotube Devices

The work will describe our efforts to develop an exascale electrostatic-quantum transport framework, Quantum-eXstatic (https://github.com/AMReX-Microelectronics/eXstatic), currently supporting the modeling of carbon nanotube field-effect transistors (CNTFETs). The framework is capable of modeling realistic three-dimensional structures, efficiently, using CPU/GPU heterogeneous architectures of state-of-the-art supercomputers. It is built on top of the AMReX library, which is a GPU-enabled software library containing functionality for writing particle-mesh applications on structured grids. The Quantum-eXstatic framework comprises three major components: the electrostatic module, the quantum transport module, and the part that self-consistently couples the two modules. The electrostatic module using a finite-volume multigrid solver to compute the electrostatic potential induced by charges on the surface of carbon nanotubes, as well as by source, drain, and gate terminals, which can be modeled using an embedded boundary approach to allow for intricate shapes. The quantum transport module uses the Nonequilibrium Green's Function (NEGF) method to model induced charge. Currently, it supports coherent (ballistic) transport, mode-space approximation for subbands of nanotube, contacts modeled as semi-infinite leads, and Hamiltonian representation using the tight-binding approximation. Special features are being included for accurate modeling of long nanotubes, such as adaptive refinement of integration contours to resolve van Hove singularities in long channels. Particular attention is paid to overlap computations with communication to optimize GPU performance. The self-consistency between the two modules is achieved using Broyden's modified second algorithm, which is parallelized using CPUs and GPUs. Preliminary scaling studies show that the code exhibits ~77% weak-scaling efficiency on 512 NVIDIA A100 GPUs of Perlmutter supercomputer for modeling gate-all-around CNTFETs with a channel length of 13.5 microns at equilibrium conditions. This case involved computations of electrostatic potential in 14.5 billion computational cells and Green’s function computation for a Hamiltonian of size 131,072 x 131,072. For problems of this large size, the code takes about 5 min to reach self-consistency. Figure 1

A Mechanism of Resistance Switching in CNT Based Memory Devices

Carbon nanotubes (CNTs) show promise for high energy efficiency electronic devices due to their high electrical conductivity. One possible application is in the fabrication of resistance-change computer memory, where the application of an external electrical bias can use a CNT layer as the switching element in a RAM cell. Memory cells of this type have been extensively demonstrated, where the electrical resistance of a switching layer of CNTs can be reversibly controlled by the application of external bias [1].To better understand these devices, we have developed a nanoscale model of their electrical switching. Towards this end, first-principles calculations of the electrical conductivity of CNT-CNT junctions were performed using the Density Functional Tight Binding (DFTB) in combination with the Non-Equilibrium Greens functions (NEGF) approach, enabling an improved understanding of the tunnelling of electrons across a range of CNT junctions [2]. These results demonstrate that the conductivity of CNT contacts depends on the overlap area between nanotubes and exponentially on the distances between the carbon atoms of the interacting CNTs. Secondly, we employed coarse-grained molecular dynamics [3,4] to produce nanoscale dense CNT film models like those used in the devices. We devise a set of metrics for characterising the structural properties of CNT films, and apply them to a set of model films designed to mimic those used in microelectronics devices. In order to understand how the geometrical properties of CNTs affect the film structure, we analyse films with different CNT chirality and length distributions. Unlike previous studies that focused on relatively low-density systems below ∼0.4 g/cm3, we also consider films with density of ∼0.6 g/cm3, as employed in experimentally fabricated CNT-based NRAM devices. By adding amorphous carbon to the film models, in varying amounts, we are then able to assess its effects. Finally, these two elements were combined to produce electrical simulations of the conductivity of the CNT films connected to TiN electrodes. These electrodes are shown to be partially oxidized during the device fabrication. The electrical conductivity in a device is characterized by formation of conduction paths formed by CNTs between the electrodes and connected via the CNT junctions. The conductivity is modulated by charging of CNTs and amorphous carbon present in the film.Using these simulations, we propose a resistance switching mechanism in TiN/CNT/TiN devices based on the physical movement of CNTs. During the initial operation of the device, oxygen is released from the oxidized bottom electrode and this readily reacts with individual CNTs to form charge trapping sites. Once these sites have become charged, they enable controllable movement of CNTs at the bottom electrode under the application of electric field. By reversibly connecting and disconnecting such CNTs from the bottom electrode, the electrical conductivity through the CNT film as a whole can be controlled.

Navigating the Fractional Calcium Dynamics of Orai Mechanism in Polar Dimensions.

Calcium plays a crucial role as a second messenger in neuronal signal transduction pathways. The influx of calcium ions through various physicochemical gating channels activates neuronal calcium signaling. The Endoplasmic Reticulum (ER) is a significant intracellular structure that sequesters calcium and controls signaling through SERCA, IPR, and leak channel mechanisms. Disruption of calcium dynamics can trigger intrinsic dyshomeostasis, cell damage, and apoptosis. The present study articulates a Caputo fractional time derivative in the polar coordinate dimensions to investigate the role of nonlocal calcium-free ions in the neuron through the Orai channel, and ER fluxes, incorporating various physiological parameters. The solution was obtained through the hybrid integral transform technique for analytical form. The closed form was generated using Green's function in terms of Mainardi and Wright's functions. Our simulation uncovered the calcium concentration bandwidth of interaction with different neuronal parameters. Parameters and calcium ion synergy show normal and Alzheimer's disease-impacted interaction through different illustrations. Our simulation reveals that S100B and BAPTA have significant calcium-controlling behavior.

A meshless stochastic method for Poisson-Nernst-Planck equations.

A plethora of biological, physical, and chemical phenomena involve transport of charged particles (ions). Its continuum-scale description relies on the Poisson-Nernst-Planck (PNP) system, which encapsulates the conservation of mass and charge. The numerical solution of these coupled partial differential equations is challenging and suffers from both the curse of dimensionality and difficulty in efficiently parallelizing. We present a novel particle-based framework to solve the full PNP system by simulating a drift-diffusion process with time- and space-varying drift. We leverage Green's functions, kernel-independent fast multipole methods, and kernel density estimation to solve the PNP system in a meshless manner, capable of handling discontinuous initial states. The method is embarrassingly parallel, and the computational cost scales linearly with the number of particles and dimension. We use a series of numerical experiments to demonstrate both the method's convergence with respect to the number of particles and computational cost vis-à-vis a traditional partial differential equation solver.

Spatially Resolved Temperature Response Functions to CO2 Emissions

AbstractCarbon dioxide (CO2) emissions affect local temperature; quantifying that local response is important for learning about the earth system, the impacts of mitigation, and adaptation needs. We assume the climate system can be represented as a time‐dependent linear system, diagnosing Green's Functions for the spatial temperature response to CO2 emissions based on CMIP6 earth system models. This allows us to emulate the linear component of the temperature response to CO2. This approach is sufficient to capture the spatial temperature response of CMIP6 experiments within one standard deviation of the multimodel spread across most regions, though accuracy is lower in the Southern Ocean and the Arctic. Our approach reveals where nonlinear feedbacks are important in current CMIP6 models, and where the local system response is well represented by a time‐dependent linear differential operator. It incorporates emissions path dependency and may be useful for evaluating large ensembles of emission scenarios.

Toward an efficient second‐order method for computing the surface gravitational potential on spherical‐polar meshes

AbstractAstrophysical accretion discs that carry a significant mass compared with their central object are subject to the effect of self‐gravity. In the context of circumstellar discs, this can, for instance, cause fragmentation of the disc gas, and—under suitable conditions—lead to the direct formation of gas‐giant planets. If one wants to study these phenomena, the disc's gravitational potential needs to be obtained by solving the Poisson equation. This requires to specify suitable boundary conditions. In the case of a spherical‐polar computational mesh, a standard multipole expansion for obtaining boundary values is not practicable. We hence compare two alternative methods for overcoming this limitation. The first method is based on a known Green's function expansion (termed “CCGF”) of the potential, while the second (termed “James' method”) uses a surface screening mass approach with a suitable discrete Green's function. We demonstrate second‐order convergence for both methods and test the weak scaling behavior when using thousands of computational cores. Overall, James' method is found superior owing to its favorable algorithmic complexity of compared with the scaling of the CCGF method.

Influence of perturbative intertube interactions on ballistic and quasi-ballistic phonon transports in double-walled carbon nanotubes

Assembling single-walled carbon nanotubes (SWCNT) into multiwalled carbon nanotubes (MWCNT) reduces the intrinsically high thermal conductivity of individual SWCNTs. Typically, this reduction can be explained by structural imperfections, e.g., defects, and van der Waals (vdW) intertube interactions between the constituent SWCNTs are considered to have negligible impacts on the reduction. However, intertube interactions should alter the transport characteristics of low-frequency phonons responsible for heat conduction, which implies that intertube interactions may also reduce the thermal conductivity of MWCNTs when low-frequency phonons modulated by intertube interactions participate in the overall heat conduction. In this study, by applying a combination of the atomistic Green's function method and nonequilibrium molecular dynamics simulation to double-walled carbon nanotubes (DWCNT) with different chiral configurations of SWCNTs and various lengths, we investigated the length scale and chiral configuration where perturbative intertube interactions can suppress phonon transports. We found that thermal resistance attributed to intertube interactions manifests in the low-temperature ballistic regime and quasi-ballistic regime for DWCNT lengths greater than 1 μm. Revisiting the influence of the intertube interactions helps comprehend the intrinsic origin of the reduced thermal conductivity of MWCNTs. In addition, the reported findings are beneficial for the thermal engineering of SWCNT-assembled materials, including emerging one-dimensional vdW heterostructures.