Safe and Secure Wireless Power Transfer Networks: Challenges and Opportunities in RF-Based Systems

RF-based wireless power transfer networks (WPTNs) are deployed to transfer power to embedded devices over the air via RF waves. Up until now, a considerable amount of effort has been devoted by researchers to design WPTNs that maximize several objectives such as harvested power, energy outage and charging delay. However, inherent security and safety issues are generally overlooked and these need to be solved if WPTNs are to be become widespread. This article focuses on safety and security problems related WPTNs and highlight their cruciality in terms of efficient and dependable operation of RF-based WPTNs. We provide a overview of new research opportunities in this emerging domain.Comment: Removed some references, added new references, corrected typos, revised some sections (mostly I-B and III-C

Thinking of becoming an equity analyst? Get relevant industry experience first

Analysts coming from the industry they now cover are 3.6% more accurate in their earnings forecasts, write Daniel Bradley, Sinan Gokkaya and Xi Li

Mesoscale simulation of stress relaxation in thin polymer films and the connection to nanocomposites

Key insight into interphase formation and confinement effects in nanocomposites has recently come from studies on polymer thin films supported on solid substrates. In these thin films, both the free surface and the solid supporting layer cause complex changes in the behavior of the polymer. The range and magnitude of these effects have been singled out by systematically varying the boundary conditions (free standing film, supported thin film, and polymer layer confined between two surfaces) and surface/polymer chemistry. Most importantly, the Schadler group and the Torkelson group have shown a quantitative equivalence between nanocomposites and thin films with regards to glass-transition temperature (Tg) via the calculation of an equivalent metric of confinement within the nanocomposite from the distribution of filler surface-to-surface distances. This finding is important because it allows for direct prediction of the Tg of the nanocomposite directly from thin film measurements and microstructural statistics, leveraging current capabilities in accurate computational/experimental characterization of film properties. However, it is currently unknown whether the thin-film analogy can be extended into the constitutive behavior of polymer nanocomposites, most importantly the stress relaxation behavior of the matrix that governs viscoelastic behavior. With an ultimate aim to address this issue, we have begun examining the stress-relaxation in doubly supported polymer thin films through coarse grained simulation using the FENE model. The current study elucidates the connection among film thickness, interfacial energy, and stress relaxation dynamics. In order to characterize the dynamic relaxation behavior of the films at constant temperature, we calculate via an extended, tensorial Green–Kubo relation the linear shear-relaxation modulus from equilibrium coarse-grained simulations of the bulk and of films of varying thickness. We then compare the simulated relaxation moduli to both the Rouse model and the theory of Likhtman and McLeish (originally based on the based on the tube model), with the additional changes proposed by Hou, Svaneborg, Everaers, and Grest. Applications to the continuum mechanics of both thin films and nanocomposites will be discussed

Precipitation behavior of dispersoids and elevated-temperature properties in Al–Si–Mg foundry alloy with Mo addition

In the present work, Mo was added to an Al-Si-Mg foundry alloy to study its influence on the evolution of dispersoids during various heat treatments. The microhardness as well as the elevated-temperature tensile properties and creep resistance was measured to evaluate the contribution of dispersoids. Results showed that the addition of Mo greatly promoted the formation of α-dispersoids. During solution treatment, the formation of α-dispersoids started after 8 hours at 500 °C. At high temperature (540 °C), the coarsening of dispersoids with increasing time became predominant. The optimum condition of dispersoids can be reached by 520°C/12h or 500°C/4h + 540°C/2h, leading to the highest differences in microhardness between the Mo-containing alloy and base alloy. The tensile strengths were improved at both room temperature and elevated temperatures, while the elongation at elevated temperature was greatly increased. The creep resistance at elevated temperature is further enhanced due to the Mo addition

Coarse-grained simulation of recovery in thermally activated shape-memory polymers

Thermally actuated shape-memory polymers (SMPs) are capable of being programmed into a temporary shape and then recovering their permanent reference shape upon exposure to heat, which facilitates a phase transition that allows dramatic increase in molecular mobility. Experimental, analytical, and computational studies have established empirical relations of the thermomechanical behavior of SMPs that have been instrumental in device design. However, the underlying mechanisms of the recovery behavior and dependence on polymer microstructure remain to be fully understood for copolymer systems. This presents an opportunity for bottom–up studies through molecular modeling; however, the limited time-scales of atomistic simulations prohibit the study of key performance metrics pertaining to recovery. In order to elucidate the effects of phase fraction, recovery temperature, and deformation temperature on shape recovery, here we investigate the shape-memory behavior in a copolymer model with coarse-grained potentials using a two-phase molecular model that reproduces physical crosslinking. Our simulation protocol allows observation of upwards of 90% strain recovery in some cases, at timescales that are on the order of the timescale of the relevant relaxation mechanism (stress relaxation in the unentangled soft phase). Partial disintegration of the glassy phase during mechanical deformation is found to contribute to irrecoverable strain. Temperature dependence of the recovery indicates nearly full elastic recovery above the trigger temperature, which is near the glass-transition temperature of the rubbery switching matrix. We find that the trigger temperature is also directly correlated with the deformation temperature, indicating that deformation temperature influences the recovery temperatures required to obtain a given amount of shape recovery, until the plateau regions overlap above the transition region. Increasing the fraction of glassy phase results in higher strain recovery at low to intermediate temperatures, a widening of the transition region, and an eventual crossover at high temperatures. Our results corroborate experimental findings on shape-memory behavior and provide new insight into factors governing deformation recovery that can be leveraged in biomaterials design. The established computational methodology can be extended in straightforward ways to investigate the effects of monomer -chemistry, low--molecular-weight solvents, physical and chemical crosslinking, different phase--separation morphologies, and more complicated mechanical deformation toward predictive modeling capabilities for stimuli-responsive -polymers

Assessing global-scale organic matter reactivity patterns in marine sediments using a lognormal reactive continuum model

Organic matter (OM) degradation in marine sediments is largely controlled by its reactivity and profoundly affects the global carbon cycle. Yet, there is currently no general framework that can constrain OM reactivity on a global scale. In this study, we propose a reactive continuum model based on a lognormal distribution (l-RCM), where OM reactivity is fully described by parameters μ (the mean reactivity of the initial OM bulk mixture) and σ (the variance of OM components around the mean reactivity). We use the l-RCM to inversely determine μ and σ at 123 sites across the global ocean. The results show that the apparent OM reactivity (〈k〉=μ⋅exp⁡(σ2/2)) decreases with decreasing sedimentation rate (ω) and that OM reactivity is more than 3 orders of magnitude higher in shelf than in abyssal regions. Despite the general global trends, higher than expected OM reactivity is observed in certain ocean regions characterized by great water depth or pronounced oxygen minimum zones, such as the eastern–western coastal equatorial Pacific and the Arabian Sea, emphasizing the complex control of the depositional environment (e.g., OM flux, oxygen content in the water column) on benthic OM reactivity. Notably, the l-RCM can also highlight the variability in OM reactivity in these regions. Based on inverse modeling results in our dataset, we establish the significant statistical relationships between 〈k〉 and ω and further map the global OM reactivity distribution. The novelty of this study lies in its unifying view but also in contributing a new framework that allows predicting OM reactivity in data-poor areas based on readily available (or more easily obtainable) information. Such a framework is currently lacking and limits our abilities to constrain OM reactivity in global biogeochemical or Earth system models

The role of anaerobic methane oxidation on the carbonate authigenesis in sediments of the subtropical Beibu Gulf, South China Sea: A reactive–transport modelling approach

The formation and burial of authigenic carbonate in marine sediment significantly affect the sedimentary carbon cycle and its isotopic mass balance in geological history. Anaerobic oxidation of methane (AOM) is the primary driver of authigenic carbonate precipitation within the sulfate-methane transition zone (SMTZ). Quantitative estimations of the role of AOM on the authigenic carbonate precipitation and its carbon isotope under non-steady-state processes (e.g., changes in methane fluxes at the bottom sediment, sedimentation rates or organic fluxes in the surface sediment), however, are still limited. In this study, we use geochemical data from porewater (e.g., the concentration of sulfate, calcium, magnesium, strontium, dissolved inorganic carbon, total alkalinity) and solid sediment (e.g., organic matter content, and carbonate content) in different depositional environments of the subtropical Beibu Gulf, South China Sea, combined with a diagenetic reactive-transport modelling approach, to estimate the mineralogy of authigenic carbonate, the relationship between AOM and authigenic carbonate precipitation, and the impact of AOM rate on carbon isotope of sediment carbonate (δ13CCar). The results show that high-Mg carbonates (high-Mg calcite and dolomite) are the main type of authigenic carbonate (∼80%) formed in the methane-bearing sediments, leading to higher porewater Sr2+/Ca2+ (>0.02) and Mg2+/Ca2+ (>20) within the SMTZ. Our modelling analysis highlights that the non-steady-state induced by increased methane flux from the underlying sediments can significantly accelerate the authigenic carbonates formation within the SMTZ. Using parametric sensitivity analysis, we observed that even a 1% increase in the authigenic carbonate fraction of sediment carbonates results in significant changes in δ13CCar within the SMTZ (from −1‰ to −2‰), mainly due to lighter carbon isotopes produced by more intensive AOM processes. Noteworthily, the terrestrial-to-marine transition was identified by the sediment and porewater geochemical profiles at site SO-8. Although lower authigenic carbonate precipitation occurs in terrestrial sedimentary environments, the proportion of authigenic carbonate in terrestrial environments (11%) is much higher than that in marine environments (1%), resulting in carbon isotopes of carbonate in terrestrial sediments becoming more negative (−5‰)

New Insight into the Anti-liver Fibrosis Effect of Multitargeted Tyrosine Kinase Inhibitors: From Molecular Target to Clinical Trials

Tyrosine kinases (TKs) is a family of tyrosine protein kinases with important functions in the regulation of a broad variety of physiological cell processes. Overactivity of TK disturbs cellular homeostasis and has been linked to the development of certain diseases, including various fibrotic diseases. In regard to liver fibrosis, several TKs, such as vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), fibroblast growth factor receptor (FGFR) and epidermal growth factor receptor (EGFR) kinases, have been identified as central mediators in collagen production and potential targets for anti-liver fibrosis therapies. Given the essential role of TKs during liver fibrogenesis, multitargeted inhibitors of aberrant TK activity, including sorafenib, erlotinib, imatinib, sunitinib, nilotinib, brivanib and vatalanib, have been shown to have potential for treating liver fibrosis. Beneficial effects are observed by researchers of this field using these multitargeted TK inhibitors in preclinical animal models and in patients with liver fibrosis. The present review will briefly summarize the anti-liver fibrosis effects of multitargeted TK inhibitors and molecular mechanisms

Mixed Neural Voxels for Fast Multi-view Video Synthesis

Synthesizing high-fidelity videos from real-world multi-view input is challenging because of the complexities of real-world environments and highly dynamic motions. Previous works based on neural radiance fields have demonstrated high-quality reconstructions of dynamic scenes. However, training such models on real-world scenes is time-consuming, usually taking days or weeks. In this paper, we present a novel method named MixVoxels to better represent the dynamic scenes with fast training speed and competitive rendering qualities. The proposed MixVoxels represents the 4D dynamic scenes as a mixture of static and dynamic voxels and processes them with different networks. In this way, the computation of the required modalities for static voxels can be processed by a lightweight model, which essentially reduces the amount of computation, especially for many daily dynamic scenes dominated by the static background. To separate the two kinds of voxels, we propose a novel variation field to estimate the temporal variance of each voxel. For the dynamic voxels, we design an inner-product time query method to efficiently query multiple time steps, which is essential to recover the high-dynamic motions. As a result, with 15 minutes of training for dynamic scenes with inputs of 300-frame videos, MixVoxels achieves better PSNR than previous methods. Codes and trained models are available at https://github.com/fengres/mixvoxelsComment: ICCV 2023 (Oral