A lightweight cell switching and traffic offloading scheme for energy optimization in ultra-dense heterogeneous networks

One of the major capacity boosters for 5G networks is the deployment of ultra-dense heterogeneous networks (UDHNs). However, this deployment results in a tremendous increase in the energy consumption of the network due to the large number of base stations (BSs) involved. In addition to enhanced capacity, 5G networks must also be energy efficient for it to be economically viable and environmentally friendly. Dynamic cell switching is a very common way of reducing the total energy consumption of the network, but most of the proposed methods are computationally demanding, which makes them unsuitable for application in ultra-dense network deployment with massive number of BSs. To tackle this problem, we propose a lightweight cell switching scheme also known as Threshold-based Hybrid cEll swItching Scheme (THESIS) for energy optimization in UDHNs. The developed approach combines the benefits of clustering and exhaustive search (ES) algorithm to produce a solution whose optimality is close to that of the ES (which is guaranteed to be optimal), but is computationally more efficient than ES and as such can be applied for cell switching in real networks even when their dimension is large. The performance evaluation shows that THESIS significantly reduces the energy consumption of the UDHN and can reduce the complexity of finding a near-optimal solution from exponential to polynomial complexity.     

Analysis of a new multispecies tumor growth model coupling 3D phase-fields with a 1D vascular network

In this work, we present and analyze a mathematical model for tumor growth incorporating ECM erosion, interstitial flow, and the effect of vascular flow and nutrient transport. The model is of phase-field or diffused-interface type in which multiple phases of cell species and other constituents are separated by smooth evolving interfaces. The model involves a mesoscale version of Darcy’s law to capture the flow mechanism in the tissue matrix. Modeling flow and transport processes in the vasculature supplying the healthy and cancerous tissue, one-dimensional (1D) equations are considered. Since the models governing the transport and flow processes are defined together with cell species models on a three-dimensional (3D) domain, we obtain a 3D–1D coupled model.     

Nanostructured BaTi1-xSnxO3 ferroelectric materials for electrocaloric applications and energy performance

Nanostructured BaTi_1-xSn_xO₃ (x = 0, 0.05 & 0.075) were successfully synthesized using the modified Pechini processing method. The phase purity and symmetry were examined by X-ray diffraction and Raman spectroscopy. Tetragonal symmetry was obtained for BaTiO₃ (BT) while orthorhombic symmetry for Sn doped BT. BT exhibits an up-shift of the Curie temperature towards high temperatures (T_C = 139 °C). In contrast, a down-shift was recorded for Sn doped BT. Then, indirect electrocaloric (EC) adiabatic temperature change ΔT and the energy storage performances were determined based on ferroelectric hysteresis loops. Interestingly, large EC responsivity of ΔT/ΔE = 0.81 × 10⁻⁶ K m/V was obtained for the BT accompanied with a moderate stored energy of 23 mJ/cm³ but with a high energy efficiency of 67%. The incorporation of Sn in BT was found to broaden the EC responsivity and to improve the energy efficiency up to 90%, recorded for the 5% Sn doped BT.     

Solution combustion synthesis,energy and environment: Best parameters for better materials

Solution combustion synthesis (SCS) is a worldwide used methodology for the preparation of inorganic ceramic and composite materials with controlled properties for a wide number of applications, from catalysis to photocatalysis and electrocatalysis, from heavy metal removal to sensoristics and electronics. The high versatility and efficiency of this technique have led to the introduction of many variants, which allowed important optimization to the prepared materials. Moreover, its ecofriendly nature encouraged further studies about the use of sustainable precursors for the preparation of nanomaterials for energy and environment, according to the concept of circular economy. On the other hand, the large variety of expressions to define SCS and the often-contradictory definitions of the SCS parameters witnessed a scarce consciousness of the potentiality of this methodology. In this review article, the most important findings about SCS and the selection criteria for its main parameters are critically reviewed, in order to give useful guidelines to those scientists who want to use this methodology for preparing materials with improved or new functional properties. This review aims as well (i) to bring more clarity in the SCS terminology (ii) to increase the awareness of the SCS as a convenient tool for the synthesis of materials and (iii) to propose a new perspective in the SCS, with special attention to the use of ecofriendly procedures. Part of the review is also dedicated to precautions and limitations of this powerful methodology.     

Energy band modulation of GaAs/Al0.26Ga0.74As quantum well in 3D self-assembled nanomembranes

In this study, we investigate the modulation of energy band in 3D self-assembled nanomembranes containing GaAs/Al_0.26Ga_0.74As quantum wells (QWs). Photoluminescence (PL) characterizations demonstrate that the self-assembled structures have different optical transition properties and the modulation of the energy band is thus realized. Detailed spectral analyses disclose that the small strain change in structures with different curvatures cannot cause remarkable change in energy bands in Al_0.26Ga_0.74As layer. On the other hand, the optical transitions of GaAs QW layer is influenced by the strain evolution in term of light emission intensity. We also find the first order Stark effect in rolled-up nanomembrane with diameter of 150 μm, which is closely connected with the coupling effect between the deformation potential and the piezoelectric potential. Our work may pave a way for the fabrication of high performance rolled-QW infrared photo-detectors.     

Growth and characterization of two-dimensional crystals for communication and energy applications

This review article covers the growth and characterization of two-dimensional (2D) crystals of transition metal chalcogenides, h-BN, graphene, etc. The chemical vapor transport method for bulk single crystal growth is discussed in detail. Top-down methods like mechanical and liquid exfoliation and bottom-up methods like chemical vapor deposition and molecular beam epitaxy for mono/few-layer growth are described. The optimal characterization techniques such as optical, atomic force, scanning electron, and Raman spectroscopy for identification of mono/few-layer(s) of the 2D crystals are discussed. In addition, a survey was done for the application of 2D crystals for both creation and deterministic transfer of single-photon sources and photovoltaic systems. Finally, the application of plasmonic nanoantenna was proposed for enhanced solar-to-electrical energy conversion and faster/brighter quantum communication devices.     

Ab initio simulations of liquid electrolytes for energy conversion and storage

Understanding physicochemical properties of liquid electrolytes is essential for predicting and optimizing device performance for a wide variety of emerging energy technologies, including photoelectrochemical water splitting, supercapacitors, and batteries. In this work, we review recent progress and open challenges in predicting structural, dynamical, and electronic properties of the liquids using first-principles approaches. We briefly summarize the basic concepts of first-principles molecular dynamics (FPMD), and we discuss how FPMD methods have enriched our understanding of a number of liquids, including aqueous solutions, organic electrolytes and ionic liquids. We also discuss technical challenges in extending FPMD simulations to the study of liquid electrolytes in more complex environments, including the interface between electrolytes and electrodes, which is a key component in many energy storage and conversion systems.     

Exploring the latest Pantheon SN Ia dataset by using three kinds of statistics techniques

In this work, we explore the cosmological consequences of the latest Type Ia supernova (SN Ia)dataset, Pantheon, by adopting the wCDM model. The Pantheon dataset currently contains the largest number of SN Ia samples, which contains 1048 supernovae on the redshift range0 z 2.3. Here we take into account three kinds of SN Ia statistics techniques, including:(1) magnitude statistics (MS), which is the traditional SN Ia statistics technique;(2) flux statistics(FS), which is based on the flux-averaging (FA) method; and (3) improved flux statistics (IFS),which combines the advantages of MS and FS. It should be mentioned that the IFS technique needs to scan the (zcut,Δz) parameters plane, where zcutandΔz are redshift cut-off and redshift interval of FA, respectively. The results are as follows.(1) Using the SN dataset only, the best FA recipe for IFS is (zcut,Δz)=(0.1, 0.08);(2) comparing to the old SN dataset, JLA, adopting the Pantheon dataset can reduce the 2σerror bars of equation of state w by 38%, 47%and 53%for MS, FS and IFS, respectively;(3) FS gives closer results to other observations, such as Baryon acoustic oscillations and cosmic microwave background;(4) compared with FS and IFS,MS more favors a Universe that will end in a ‘big rip’.