HexPlane: A Fast Representation for Dynamic Scenes

Modeling and re-rendering dynamic 3D scenes is a challenging task in 3D vision. Prior approaches build on NeRF and rely on implicit representations. This is slow since it requires many MLP evaluations, constraining real-world applications. We show that dynamic 3D scenes can be explicitly represented by six planes of learned features, leading to an elegant solution we call HexPlane. A HexPlane computes features for points in spacetime by fusing vectors extracted from each plane, which is highly efficient. Pairing a HexPlane with a tiny MLP to regress output colors and training via volume rendering gives impressive results for novel view synthesis on dynamic scenes, matching the image quality of prior work but reducing training time by more than $100\times$. Extensive ablations confirm our HexPlane design and show that it is robust to different feature fusion mechanisms, coordinate systems, and decoding mechanisms. HexPlanes are a simple and effective solution for representing 4D volumes, and we hope they can broadly contribute to modeling spacetime for dynamic 3D scenes.Comment: Project page: https://caoang327.github.io/HexPlan

A Simple and Efficient Approach to Cellulose/Silica Composite Aerogel with High Silica Utilization Efficiency

Cellulose aerogel is a fascinating material with high porosity, low density and biocompatibility. However, cellulose aerogel lacks sufficient thermal stability. Recombination between cellulose aerogel with silica is efficacious for enhance the cellulose aerogel's thermal stability. This work described a simple and efficient approach to the cellulose/silica composite aerogel via a dropwise manner, using tetraethoxysilane as silicon source and NaOH solution as cellulose solvent. The result showed that the thermal stability of cellulose aerogel was enhanced by introducing silica. And by this manner, the utilization efficiency of silica was up to 95%. The composite aerogel had a low density and a high porosity, which promised the material a good heat insulation performance, and the thermal conductivity of the composite aerogel was low to 0.0161W/(m·K). Moreover, by adjusting cellulose concentration and tetraethoxysilane amount, the density, porosity and thermal conductivity of the composite aerogel could be controlled. This work contributed to improving the utilization efficiency of silica for the composite aerogel with better performances

Nonlinear optical conductivity of two-dimensional semiconductors with Rashba spin-orbit coupling in terahertz regime

We reveal that two-dimensional semiconductors with Rashba spin-orbit interaction (R2DG) exhibit exceptionally strong nonlinear optical response (NOR) in the terahertz frequency regime. The spin-split of the parabolic energy band in R2DG allows strong multiple-photon process to occur via inter-subband mechanism. We show sharp multiple photon edges in the nonlinear conductivity. The edges correspond to the cut-off effect produced by the multiple-photon process. For Rashba coupling parameter of λ R ≈ 10−10 eV m, electric field strength in the order of only 102 V/cm is required for the NOR to dominate over the linear response. Furthermore, the roles of the parabolic ‘free electron’ term H 0 and the linear Rashba term H R on NOR of R2DG are also investigated. Although the NOR is made possible due to the presence of a finite H R , H 0 does play an important role on the NOR especially in high temperature regime. H 0 has rendered R2DG a strong optical nonlinearity at elevated temperature which is not found in a purely linear system such as graphene. The results suggest the possibilities of Rashba spintronic system in the application of nonlinear terahertz devices

Relation Between Gravitational Mass and Baryonic Mass for Non-Rotating and Rapidly Rotating Neutron Stars

With a selected sample of neutron star (NS) equations of state (EOSs) that are consistent with the current observations and have a range of maximum masses, we investigate the relations between NS gravitational mass Mg and baryonic mass Mb, and the relations between the maximum NS mass supported through uniform rotation (Mmax) and that of nonrotating NSs (MTOV). We find that for an EOS-independent quadratic, universal transformation formula (Mb=Mg+A×M2g)(Mb=Mg+A×Mg2), the best-fit A value is 0.080 for non-rotating NSs, 0.064 for maximally rotating NSs, and 0.073 when NSs with arbitrary rotation are considered. The residual error of the transformation is ∼ 0.1M⊙ for non-spin or maximum-spin, but is as large as ∼ 0.2M⊙ for all spins. For different EOSs, we find that the parameter A for non-rotating NSs is proportional to R−11.4R1.4−1 (where R1.4 is NS radius for 1.4M⊙ in units of km). For a particular EOS, if one adopts the best-fit parameters for different spin periods, the residual error of the transformation is smaller, which is of the order of 0.01M⊙ for the quadratic form and less than 0.01M⊙ for the cubic form ((Mb=Mg+A1×M2g+A2×M3g)(Mb=Mg+A1×Mg2+A2×Mg3)). We also find a very tight and general correlation between the normalized mass gain due to spin Δm = (Mmax − MTOV)/MTOV and the spin period normalized to the Keplerian period PP, i.e., log10Δm=(−2.74±0.05)log10P+log10(0.20±0.01)log10Δm=(−2.74±0.05)log10P+log10(0.20±0.01), which is independent of EOS models. These empirical relations are helpful to study NS-NS mergers with a long-lived NS merger product using multi-messenger data. The application of our results to GW170817 is discussed

Lanthanum Oxyhalide Monolayers: An Exceptional Dielectric Companion to Two-Dimensional Semiconductors

Two-dimensional (2D) layered dielectrics offers a compelling route towards the design of next-generation ultimately compact nanoelectronics. Motivated by recent high-throughput computational prediction of LaO$X$ ($X$ = Br, Cl) as an exceptional 2D dielectrics that significantly outperforms HfO$_2$ even in the monolyaer limit, we investigate the interface properties between LaOX and the archetypal 2D semiconductors of monolayer transition metal dichacolgenides (TMDCs) $M$S$_2$ ($M$ = Mo, W) using first-principle density functional theory simulations. We show that LaO$X$ monolayers interacts weakly with $M$S$_2$ via van der Waals forces with negligible hybridization and interfacial charge transfer, thus conveniently preserving the electronic properties of 2D TMDCs upon contact formation. The conduction and valance band offsets of the interfaces exhibit a sizable value ranging from 0.7 to 1.4 eV, suggesting the capability of LaO$X$ as a gate dielectric materials. Based on Murphy-Good electron emission model, we demonstrate that LaOCl/MoS$_2$ is a versatile dielectric/semiconductor combinations that are compatible to both NMOS and PMOS applications with leakage current lower than $10^{-7}$ Acm$^{-2}$, while LaO$X$/WS$_2$ is generally compatible with PMOS application. The presence of an interfacial tunneling potential barrier at the van der Waals gap further provide an additional mechanism to suppress the leakage current. Our findings reveal the role LaO$X$ as an excellent dielectric companion to 2D TMDC and shall provide useful insights for leveraging the dielectric strength of LaO$X$ in the design of high-performance 2D nanodevices.Comment: 10 pages, 4 Figures, 3 Table

Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Models

We present Text2Room, a method for generating room-scale textured 3D meshes from a given text prompt as input. To this end, we leverage pre-trained 2D text-to-image models to synthesize a sequence of images from different poses. In order to lift these outputs into a consistent 3D scene representation, we combine monocular depth estimation with a text-conditioned inpainting model. The core idea of our approach is a tailored viewpoint selection such that the content of each image can be fused into a seamless, textured 3D mesh. More specifically, we propose a continuous alignment strategy that iteratively fuses scene frames with the existing geometry to create a seamless mesh. Unlike existing works that focus on generating single objects or zoom-out trajectories from text, our method generates complete 3D scenes with multiple objects and explicit 3D geometry. We evaluate our approach using qualitative and quantitative metrics, demonstrating it as the first method to generate room-scale 3D geometry with compelling textures from only text as input.Comment: Accepted to ICCV 2023 (Oral) video: https://youtu.be/fjRnFL91EZc project page: https://lukashoel.github.io/text-to-room/ code: https://github.com/lukasHoel/text2roo