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Although Li metal batteries (LMBs) with high flexibility are attractive energy storage systems for wearable devices due to their high energy density, there exist critical challenges such as limited loading density, poor dimensional stability, and thus mechanical instability under repeated mechanical deformations including bending, twisting, and folding. In this work, extremely flexible nano/microfiber composite electrodes are developed for LMBs. The highly flexible and mechanically durable electrode is composed of oxidized polyethylene terephthalate (O‐PET) microfiber (MF) substrates covered by single‐walled carbon nanotube (CNT) nanofibers (NF), prepared by mass‐producible O2 plasma treatment and spray‐coating. CNT nanofibers provided an electrical intertangled network to integrate the active materials (i.e., either NCM or passivated Li powder (PLP)) and anchored to a flexible O‐PET MF substrate, which permits high mass loading of active materials, improved electrochemical performance while maintaining mechanical durability. Resultantly, the flexible LMBs based on nano/micro fibrous electrodes have excellent energy density (300.1 Wh kg−1 electrode; nominal voltage of 3.7 V) and stable capacity retention (97.1%) without mechanical failure over 500 folding cycles. [ABSTRACT FROM AUTHOR]

In the implementation of full waveform inversion (FWI) to identify subsurface velocity distributions with land seismic data, which are often acquired in regions with irregular topography, wave equation-based modelling requires caution. In particular, when using the finite difference method (FDM), unwanted scattered waves are generated because irregular surfaces crossing a rectangular grid are discretized via a staircase approximation; hence, if the problems caused by this staircase approximation are disregarded, FDM-based FWI may fail due to the presence of undesirable wavefields. To resolve this problem, this study develops a 2D frequency-domain acoustic FWI technique using a 9-point FDM-based modelling scheme that includes an embedded boundary method (EBM). This study suggests a workflow for the whole EBM-based FWI process from the calculation of coefficients for the EBM-based 9-point FDM modelling to applying it to FWI for proper velocity updates. In numerical examples, using velocity models with a tilted surface and an arbitrarily fluctuating surface, we synthesize seismic data and verify the accuracy of EBM-based 9-point FDM modelling and its superiority over the conventional FDM by comparing it with wavefields derived from the spectral element method. Then, we show that our EBM-based FWI is able to estimate subsurface velocity distributions even though the model has irregular topography, which spoils the result of the conventional FWI. [ABSTRACT FROM AUTHOR]

Full waveform inversion (FWI) is a highly non-linear optimization problem that aims to reconstruct high-resolution subsurface structures. The success of FWI in reflection seismology relies on appropriate updates of low-wavenumber background velocity structures, which are generally driven by the diving waves in conventional FWI. On the other hand, the reflected waves mainly contribute to updating high-wavenumber components rather than low-wavenumber components. To extract low-wavenumber information from the reflected waves in addition to the diving waves, we propose a two-step FWI strategy that separates a given model into the reflectivity and background velocity models and then alternately update them using the scale-separation technique based on diffraction-angle filtering (DAF; which was proposed to effectively control wavenumber components of the FWI gradient). Our strategy first inverts the high-wavenumber reflectivity model by suppressing energy at large diffraction angles, which are necessary to compute the reflection wave paths (i.e. the rabbit-ears-shaped kernels) for low-wavenumber updates in the subsequent stage. Then, we extract low-wavenumber components due to the diving (banana-shaped kernels) and reflected waves (rabbit-ears-shaped kernels) from the gradient by suppressing energy at small diffraction angles. Our strategy is similar to reflection waveform inversion (RWI) in that it separates a given model into high- and low-wavenumber components and uses the rabbit-ears-shaped kernels for low-wavenumber updates. The main difference between our strategy and RWI is that our strategy adopts the DAF-based scale-separation technique in the space domain, which makes our algorithm of using both the banana-shaped and rabbit-ears-shaped kernels computationally attractive. By applying our two-step inversion strategy to the synthetic data for the Marmousi-II model and the real ocean-bottom cable data from the North sea, we demonstrate that our method properly reconstructs low-wavenumber structures even if initial models deviate from the true models. [ABSTRACT FROM AUTHOR]

In the early stage of acoustic full-waveform inversion (AFWI), it is important to exploit the long-wavelength features of the gradient and suppress its short-wavelength features to update the background velocity. However, due to strong near-offset PP reflections and multiples within the pressure data, conventional AFWI sometimes primarily reconstructs the short-wavelength features of a given model and fails to converge on a reliable subsurface P-wave velocity model. Therefore, this study, we propose the usage of pseudo-horizontal particle acceleration (pseudo-ax) data for AFWI, rather than the original pressure data. Because the amplitudes of PP reflections are implicitly weighted according to the reflection angle in pseudo-ax data, the near-offset PP reflections and multiples of the pseudo-ax data are much weaker than those of the pressure data. As a result, AFWI using pseudo-ax data focuses on reconstructing the longer-wavelength features of a given model in the early iterations, and then gradually reconstructs short-wavelength features as the inversion process continues. Using synthetic and real data examples for the Volve oilfield in the North Sea, we examined the effects and feasibility of this strategy. In the synthetic data example, the proposed strategy rapidly reduced far-offset data misfits related to long-wavelength feature updates and achieved smaller model misfits than the conventional strategy. The real data example showed that the velocity model reconstructed using the proposed strategy flattened some of the reflectors at the angle-domain common-image gathers (ADCIGs) better than the velocity model obtained using the conventional strategy. These findings demonstrate that our strategy converges closer to the real P-wave velocity model than the conventional strategy by building a hierarchical velocity model from long- to short-wavelength structures. [ABSTRACT FROM AUTHOR]

Full-waveform inversion (FWI), which is among the most powerful seismic data processing techniques for imaging subsurface geological structures, has a huge computational cost in proportion to the number of sources. To increase the speed of FWI, we explored the use of common-receiver gathers (CRGs) as an alternative to common-shot gathers (CSGs) as observed data. This approach has the potential to reduce the computational cost of FWI significantly, particularly for ocean-bottom cable (OBC) acquisition. As we match modelled and observed CSGs in CSG-based FWI, we match observed CRGs with modelled CSGs of switched source–receiver geometry in CRG-based FWI. According to the reciprocity principle, CRG FWI based on the steepest descent or Gauss–Newton method yields the same inverted velocity models as CSG FWI for an identical and known source signature applied over whole source positions. However, when the source wavelet is unknown, and changes from one source position to another, each trace of a CRG contains a different source signature, making it difficult to apply conventional source estimation or source-independent methods to CRG FWI. Therefore, in this study, we proposed inversion strategies for CRG FWI in both the time and frequency domains to deal with errors arising from different source wavelets between CRG traces. Then, we used a synthetic example for the Marmousi-II model and a real data example from the North Sea to demonstrate that our strategies for CRG FWI provide very similar inverted velocity models to those obtained from CSG FWI, at a lower computational cost. [ABSTRACT FROM AUTHOR]

To improve the computational efficiency of reverse-time migration (RTM) for vertically transverse isotropic (VTI) media, various acoustic approximations of the elastic wave equations have been presented. Among these, the pseudo-acoustic wave equation, which combines differential and scalar operators, has the advantage that it does not produce shear wave artefacts. In this study, we investigate the feasibility of pseudo-acoustic anisotropic RTM (PA-RTM) for the analysis of synthetic and observed ocean-bottom cable (OBC) datasets of the Volve oil field in the North Sea. To analyse the influence of anisotropic parameters on RTM images and the sensitivity of data components to seismic anisotropy, we perform PA-RTM using synthetic data by incorporating various background models, as well as pressure wavefields and vertical particle acceleration. The synthetic experiments demonstrate that the anisotropic parameter ε plays an important role, whereas δ is negligible in PA-RTM for VTI media, and that vertical particle acceleration is less affected by seismic anisotropy than the pressure wavefields. Our experiments using observed data show that reflectors are better imaged by PA-RTM than by isotropic-RTM, particularly near the reservoir below the strongly anisotropic region, which is supported by angle-domain common image gathers. These results indicate that PA-RTM using only the vertical component is a suitable option for VTI media when insufficient seismic anisotropy data are available. [ABSTRACT FROM AUTHOR]

Molybdenum disulfide (MoS2) is considered a promising material in energy storage systems, and is thus drawing considerable attention. However, the relatively low conductivity of bulk MoS2 has been a threat for practical applications. This study developed a simple and scalable fabrication method of few-layer MoS2 sheets embedded in a nanoporous graphene film (NGF) as a high capacitance active material. Transfer of MoS2/NGF onto a flexible substrate followed by plotter cutting produced a highly efficient micro-supercapacitor with superior flexibility, mechanical stability, and great potential for applications in wearable electronics. Notably, MoS2/NGF-based mSC revealed a high volumetric capacitance of 55 F cm−3 and 82.2% of capacitance retention after 20 000 cycles, which are superior to the reported data for solid-state micro-supercapacitors. With these performances, the flexible MoS2/NGF mSC exhibited an ultrahigh energy density of 7.64 mW h cm−3 and power density of 9.96 W cm−3 in a H3PO4 gel polymer electrolyte. The high volumetric capacitance and energy/power densities of MoS2/NGF as micro-supercapacitor electrodes are due to direct growth of ultra-thin MoS2 onto the interconnected 3D nanoporous graphene film with extended active sites and good conductivity. The MoS2/NGF mSC integrated on the skin efficiently powered a light emitting diode and strain sensors. This work suggests a meaningful way to realize film type MoS2 active materials in flexible micro-supercapacitors for wearable applications. [ABSTRACT FROM AUTHOR]