Spherical Features Research Articles

FELC-SLAM: feature extraction and loop closure optimized lidar SLAM system

Abstract Simultaneous Localization and Mapping (SLAM) is one of the key technologies in robot navigation and autonomous driving, playing an important role in robot navigation. Due to the sparsity of LiDAR data and the singularity of point cloud features, accuracy loss of LiDAR SLAM can occur during point cloud matching and localization. In response to these issues, this paper proposes a LiDAR Measurement SLAM algorithm that integrates multi type geometric feature extraction and optimized point cloud registration algorithms. This article first adopts advanced ground segmentation methods and feature segmentation strategies, including ground features, edge features, planar features, and spherical features, to improve matching accuracy. In addition, this article improves the previous method for extracting edge and planar features, extracting clearer and more robust line and surface features to address the degradation of geometric features. Finally, by introducing a robust decoupling global registration method for loop closure detection in the backend of the system, the sparsity problem of distant point clouds and the degradation problem caused by the reduction of inner layers in point cloud registration were effectively solved. In the evaluation of the KITTI dataset, our algorithm reduced absolute trajectory error values by 60%, 29%, and 71% compared to LeGO-LOAM in multi loop and feature constrained scenarios (such as sequences 00, 01, and 02), respectively. The evaluation of the M2DGR and Botanic Garden datasets also indicates that the positioning accuracy of our algorithm is superior to other advanced LiDAR SLAM algorithms.

Metrics for Domain Shift Characterization: Comparisons and New Directions

Domain adaptation is an important area of research, as it aims to remedy the effects of the domain shift due to differences in the distribution between the source domain used for training and the target domain where prediction takes place. However, methods for characterizing the domain shift across datasets are lacking. In this work, we propose a domain shift metric called SpOT, which stands for spherical optimal transport, by operating on the spherical manifold. We realize our approach with a spherical network, used to obtain features, and an orthogonal projection loss, used to impose orthogonality in the feature space. The resulting spherical features have better inter-class separation and lower intra-class variation compared to features in Euclidean space. This type of feature clustering makes each domain representation more compact and more suitable for further analysis. The domain shift between the datasets is calculated using the optimal transport on the spherical features, which has a sound theoretical basis. Our results are further supported by experiments that show the correlation of SpOT with a new gain of transfer measure across domain adaptation datasets.

Research on Intelligent Navigation System Based on Aerospace Big Data Traffic System

This paper studies the navigation technology of the On-Orbit Servicing Spacecraft (OSS) and proposes an overall solution for the OSS navigation system. The composition of the OSS satellite navigation simulation system and simulation supporting environment are studied. Then a new SSUKF navigation filter is proposed based on the hyper spherical distributed feature sampling point transform algorithm (SSUT) and the non-scanning Kalman filter (UKF). The numerical simulation of the OSS system is studied based on MATLAB/RTW. Finally, the SSUKF algorithm and the conventional UKF algorithm are simulated digitally. The effectiveness and advanced nature of the hybrid Kalman filter applied to spacecraft autonomous navigation are verified.

Preparation of nanodiamonds modified hard carbon with uniform spherical feature for improving sodium-ion storage performances

Sodium-ion batteries (SIBs) have received remarkable attention due to their abundant sodium (Na) content and low resources cost. However, the absence of high-performance anode materials make carbon-based SIBs still a challenge. Herein, nano-diamonds (NDs) modified gleditsia japonica shell carbon to form a uniform carbon microsphere, which improves the graphitization degree and Na ion adsorption, NDs also act as a strong scaffold to maintain its stability. This spherical carbon-based material exhibits superior performances including the enhanced capacity (270 mA h g−1 at 0.2C after 100 cycles) and long-cycle stability (155 mA h g−1 at 2C after 1000 cycles) when incorporated into SIBs. This work provides a green and simple synthesis strategy for fabricating high performance porous spherical carbon used for SIBs anode.

Abstract 3199: Nano gelasomes: Novel lamellar metal-protein suprastructures for nucleic acid delivery

Abstract There is considerable interest in the development of self-assembled charged nanocarriers that form organized, predictable structures to enhance stable packaging and delivery of nucleic acid materials in vivo. However, the synthesis of stably-charged, organized nanostructures is highly challenging, requiring a controlled balance of nanomaterial components, stabilizers, and hydrophobic forces. Herein, we report a significant step forward in the controlled lamellar assembly of a charged complex between ultra-small 2 nm gold nanoparticles and a lipidoid within an organic matrix to form Gelasomes. These spherical suprastructures feature an intricate 3D concentric arrangement with a constant interlayer distance (4nm). The cationic lipidoid within this arrangement aids in the highly efficient packaging of nucleic acid materials in the nanoparticle. To demonstrate the potential biomedical applications of Gelasomes, we have loaded siRNA (AXL or YAP), mRNA (EGFP), or CRISPR components (Cas9 mRNA and guide RNA) and validated their functionality by in vitro or in vivo studies. Gelasomes with AXL siRNA (~20 bp) demonstrated rapid uptake (<2 hrs), successful endosomal escape, remarkable transfection efficiency (99.87 ± 0.04 %), gene downregulation (97 ± 2.8 %), and disassembly within the cell (<24 hrs). In vivo downregulation studies in Lung Cancer PDX (Gelasomes with AXL siRNA) and CDX (Gelasomes with YAP siRNA) models confirm the gene-silencing capability (91% or 38 % respectively) of Gelasomes underscoring their potential in advancing nanomedicine. Similarly, Gelasome loaded with EGFP mRNA (1 kb) showed 47 ± 8.54 % expression efficiency within 48 h of treatment in vitro. We also show the packaging of larger nucleic acids such as CRISPR Cas9 mRNA (5 kb) along with the guide RNA (100 bp) in vitro for generating knockouts, that achieved an editing efficiency of ~6%. Together, the results from this study pave the way for the development of adaptable, biodegradable, and functionally versatile supraparticles for medical applications. Citation Format: Agasthya Suresh Babu, Dhananjay Suresh, Zhaohui Li, Anandhi Upendran, Raghuraman Kannan. Nano gelasomes: Novel lamellar metal-protein suprastructures for nucleic acid delivery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3199.

Unsupervised and Semi-Supervised Robust Spherical Space Domain Adaptation.

Adversarial domain adaptation has been an effective approach for learning domain-invariant features by adversarial training. In this paper, we propose a novel adversarial domain adaptation approach defined in the spherical feature space, in which we define spherical classifier for label prediction and spherical domain discriminator for discriminating domain labels. In the spherical feature space, we develop a spherical robust pseudo-label loss to utilize pseudo-labels robustly, which weights the importance of the estimated labels of target domain data by the posterior probability of correct labeling, modeled by the Gaussian-uniform mixture model in the spherical space. Our proposed approach can be generally applied to both unsupervised and semi-supervised domain adaptation settings. In particular, to tackle the semi-supervised domain adaptation setting where a few labeled target domain data are available for training, we propose a novel reweighted adversarial training strategy for effectively reducing the intra-domain discrepancy within the target domain. We also present theoretical analysis for the proposed method based on the domain adaptation theory. Extensive experiments are conducted on multiple benchmarks for object recognition, digit recognition, and face recognition. The results show that our method either surpasses or is competitive compared with the recent methods for both unsupervised and semi-supervised domain adaptation. Ablation studies also confirm the effectiveness of the spherical classifier, spherical discriminator, spherical robust pseudo-label loss, and reweighted adversarial training strategy.

Intelligent Navigation System based on Big Data Traffic System

This paper studies the navigation technology of the On-Orbit Servicing Spacecraft (OSS) and proposes an overall solution for the OSS navigation system. The composition of the OSS satellite navigation simulation system and simulation supporting environment are studied. Then a new SSUKF navigation filter is proposed based on the hyper spherical distributed feature sampling point transform algorithm (SSUT) and the non-scanning Kalman filter (UKF). The numerical simulation of the OSS system is studied based on MATLAB/RTW. Finally, the SSUKF algorithm and the conventional UKF algorithm are simulated digitally. The effectiveness and advanced nature of the hybrid Kalman filter applied to spacecraft autonomous navigation are verified.

Multifunctional B/N/O-co-doped porous spherical carbons to achieve superior capacitive performance with OER activity

B, N and O-co-doped carbon with a spherical morphology obtained from the carbonization of a polymer of 1,4-phenylenediamine/formaldehyde/phloroglucinol and boric acid shows remarkable energy storage properties along with the ability to split water.

Ag(Sn9-Sn9)]5- and [(η4-Sn9)Ag(η1-Sn9)]7-, as aggregates of spherical aromatic building blocks. Persistence of aromaticity upon cluster gathering.

Formation of cluster-based materials requires a fundamental understanding of the resulting cluster aggregation processes. The Sn94- Zintl-ion structure can be viewed as a building block featuring a spherical aromatic species, leading to a cluster gathering upon oxidative coupling and/or mediated by transition metals. Here, we evaluate the spherical aromatic properties of [Sn9-Sn9]6-, [Ag(Sn9-Sn9)]5- and [(η4-Sn9)Ag(η1-Sn9)]7-, as aggregates of two Sn9 building units held together via oxidative coupling and mediated by a Ag(I) transition metal center. Our results from magnetic criteria of aromaticity show that the inherent spherical aromatic characteristics of the parent Sn94- cluster are persistent in the overall aggregate where the enabled shielding cones ascribed to each Sn9 unit are able to interplay between them, leading to an overlap of the shielding regions. Hence, the two approaches for bringing cluster units together are able to retain the inherent spherical aromatic features for each Sn9 unit, leading to a cluster-based dimer where the parent properties remain. Thus, further cluster-based materials can be envisaged from aggregation upon oxidative coupling and/or mediated by transition metals, where the constituent building blocks retain their initial features, useful to guide the formation of more complex cluster-based aggregates.

Dual stimuli-responsive polymeric nanoparticles combining soluplus and chitosan for enhanced breast cancer targeting.

A dual stimuli-responsive nanocarrier was developed from smart biocompatible chitosan and soluplus graft copolymers. The copolymerization was investigated by differential scanning calorimetry (DSC), thermo-gravimetric analysis (TGA), and Fourier transform infrared (FTIR). The optimized chitosan-soluplus nanoparticles (CS-SP NPs) were further used for the encapsulation of a poorly water-soluble anticancer drug. Tamoxifen citrate (TC) was used as the model drug and it was loaded in CS-SP NPs. TC CS-SP NPs were characterized in terms of particle size, zeta potential, polydispersity, morphology, encapsulation efficiency, and physical stability. The nanoparticles showed homogenous spherical features with a size around 94 nm, a slightly positive zeta potential, and an encapsulation efficiency around 96.66%. Dynamic light scattering (DLS), in vitro drug release, and cytotoxicity confirmed that the created nano-system is smart and exhibits pH and temperature-responsive behavior. In vitro cellular uptake was evaluated by flow cytometry and confocal microscopy. The nanoparticles revealed a triggered increase in size upon reaching the lower critical solution temperature of SP, with 70% of drug release at acidic pH and 40 °C within the first hour and a 3.5-fold increase in cytotoxicity against MCF7 cells incubated at 40 °C. The cellular uptake study manifested that the prepared nanoparticles succeeded in delivering drug molecules to MCF7 and MDA-MB-231 cells. In summary, the distinctive characteristics provided by these novel CS-SP NPs result in a promising nano-platform for effective drug delivery in cancer treatment.

Bright photoluminescence from CdSe quantum dots conjugated with metal phthalocyanines

Engineering organic/inorganic nanohybrids is one of the emerging tracks in material science to search for new nanomaterials with tailored and/or enhanced properties. In this work, we report the synthesis of CdSe quantum dots (QDs) conjugated with selected metal phthalocyanine (MPc), e.g., ZnPc and CuPc, utilizing the hot-injection organometallic method. The prepared pristine and conjugated QD systems exhibit practically identical particle size and spherical morphology and feature the characteristic CdSe excitonic peaks in their optical absorption spectra. The successful incorporation of ZnPc or CuPc molecules is ensured by the appearance of their sharp Q-band peaks in the optical absorption and the Zn2p or Cu2p core levels in the X-ray photoemission spectroscopy (XPS) measurements. The pure CdSe QDs sample of selected size (∼4.0 nm) exhibits well-defined photoluminescence (PL) peak at the limit of the green range, which is remarkably enhanced for the conjugated QD systems, reaching ∼250 % for the CuPc/CdSe QDs. Such prominent PL enhancement is attributed to Förster resonance energy transfer stimulated by deep B-band emissions from CuPc molecules combined with charge transfer from MPc molecules to CdSe QDs. Furthermore, the emission is greatly amplified upon prolonged exposure to laser beam, exceeding 400 % of the initial CuPc/CdSe emission after only 40 min of exposure time, yet without significant changes in their emission color. Thus, these MPc/CdSe conjugated QD systems are promising nanomaterials for intense white light sources.

SPDET: Edge-Aware Self-Supervised Panoramic Depth Estimation Transformer With Spherical Geometry.

Panoramic depth estimation has become a hot topic in 3D reconstruction techniques with its omnidirectional spatial field of view. However, panoramic RGB-D datasets are difficult to obtain due to the lack of panoramic RGB-D cameras, thus limiting the practicality of supervised panoramic depth estimation. Self-supervised learning based on RGB stereo image pairs has the potential to overcome this limitation due to its low dependence on datasets. In this work, we propose the SPDET, an edge-aware self-supervised panoramic depth estimation network that combines the transformer with a spherical geometry feature. Specifically, we first introduce the panoramic geometry feature to construct our panoramic transformer and reconstruct high-quality depth maps. Furthermore, we introduce the pre-filtered depth-image-based rendering method to synthesize the novel view image for self-supervision. Meanwhile, we design an edge-aware loss function to improve the self-supervised depth estimation for panorama images. Finally, we demonstrate the effectiveness of our SPDET with a series of comparison and ablation experiments while achieving the state-of-the-art self-supervised monocular panoramic depth estimation. Our code and models are available at https://github.com/zcq15/SPDET.

Preparation of ultrafine (W,Mo)B, (W,Mo)B2.5 and (Mo,W)AlB solid solution composite powders

In this study, ultrafine borides powders including (W,Mo)B, (W,Mo)B2.5 and (Mo,W)AlB were successfully fabricated via boronizing ultrafine W-Mo solid solution composite powder with B4C as the boron source under the assistance of Ca melt or Al melt. Ultrafine W-Mo solid solution powder was obtained by using a two-stage reduction route to reduce the precursor powder synthesized by spray drying. Meanwhile, the effects of Mo/W ratio on the phase composition, morphological characteristics and particle size distribution of boride solid solution composite powder were thoroughly investigated. The shift of diffraction peak in the XRD spectrum, the linear change of lattice constant and the homogeneous distributions of W, Mo, B and Al in the EDS energy spectrum comprehensively confirmed that the boride solid solution with different Mo/W ratios could be prepared. Due to the essentially insolubilities of W and Mo in Ca melt, the (W, Mo)B grains grew following a template growth mechanism, and inherited the nearly spherical morphology feature of ultrafine W-Mo solid solution composite powder with a particle size of approximately 200 nm. Nonetheless, as a result of the high solubilities of W, Mo, and B in Al melt, the process of dissolution-precipitation led to the formations of flaky (W, Mo)B2.5 and short rod-shaped (Mo, W)AlB.

Perception-Aware Image-Based Visual Servoing of Aggressive Quadrotor UAVs

The maintenance of visual features within the sensor field of view poses a significant challenge for underactuated aerial vehicles such as quadrotors, especially during aggressive maneuvers. However, the existing image-based visual servo (IBVS) control methods rely on strict target visibility assumptions or impose excessive constraints on the quadrotor's agility to meet this requirement. Furthermore, the effectiveness of the visibility constraint defined in prior works remains unverified in aggressive flight tests. To address these issues, we present a robust IBVS scheme for quadrotors to perform aggressive maneuvers while ensuring target visibility. Based on the nonlinear model-predictive control framework, we propose a novel underactuation compensation scheme to eliminate the need for a virtual camera frame, which enables us to formulate the true target visibility constraint. We then introduce a quaternion-based representation of spherical visual features to handle the nonsmooth vector field problem on the 2-sphere and derive its corresponding image kinematics. We validate our method through three challenging visual servo tasks where agile maneuvers are desired: fast landing, aggressive long-distance flight, and dynamic object tracking. Extensive simulation and experiment show that our method consistently achieves a target-visible rate of 100% in all the image frames, even under a maximum pitch of 21.04 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> . The results validate the effectiveness of our visibility constraint under large robot rotations and underscore its importance in enabling robust and aggressive flights.

Densest-known packings and phase behavior of hard spherical capsids.

By mostly using Monte Carlo numerical simulation, this work investigates the densest-known packings and phase behavior of hard spherical capsids, i.e., hard infinitesimally thin spherical caps with a subtended angle larger than the straight angle. The infinitely degenerate densest-known packings are all characterized by hard spherical capsids that interlock and can be subdivided into three families. The first family includes crystalline packings that are constructed by suitably rotating and stacking layers of hexagonally arranged and suitably tilted hard spherical capsids; depending on the successive rotations, the crystalline packings of this family can become the face-centered cubic crystal, the hexagonal close-packed crystal, and their infinitely degenerate variants in the hard-sphere limit. The second family includes crystalline packings that are characterized by rhombic motifs; they all become the face-centered cubic crystal in the hard-sphere limit. The third family includes crystalline packings that are constructed by suitably shifting and stacking layers in which hard spherical capsids are arranged in tightly packed, straight or zigzag, columns; depending on the successive shifts, the crystalline packings of this family can become the face-centered cubic crystal, the hexagonal close-packed crystal, and their infinitely degenerate variants in the hard-sphere limit. In the plane number density vs subtended angle, the phase diagram of hard spherical capsids features a hexagonal columnar liquid-crystalline phase, toward the hard-hemispherical-cap limit, and a plastic-crystalline phase, toward the hard-sphere limit, in addition to the isotropic fluid phase and crystalline phases. On departing from the hard-sphere limit, the increasing propensity of hard spherical capsids to interlock progressively disfavors the plastic-crystalline phase while favoring auto-assemblage into mostly dimeric interlocks in the denser isotropic fluid phase so that a purely entropic isotropic-fluid-plastic-crystal-isotropic-fluid re-entrant sequence of phase transitions is observed in systems of hard spherical capsids with a subtended angle intermediate between the straight angle and the complete angle.

T-distributed Spherical Feature Representation for Imbalanced Classification

T-distributed Spherical Feature Representation for Imbalanced Classification

Solar-driven photodegradation of synthetic dyes by ternary of titanium oxide-copper oxide-chitosan catalyst

The ternary titanium oxide (TiO2), copper oxide (CuO), and chitosan (TiO2/CuO/Chitosan) photocatalyst (composites) for the photodegradation of synthetic methyl orange (MO) were developed by entrapping copper ions and nanosized TiO2 into chitosan thin films at room temperature. TiO2 Degussa P25 was incorporated with CuO and Chitosan (CS) solution using an ex-situ synthesis method before being immobilized onto glass plates via a dip-coating technique. This study is the first time approach for a combination of a composite comprising two metal oxides to suppress the electron-hole recombination, thus enhancing their catalytic and adsorptive properties. The morphology and surface interactions of the TiO2/CuO/Chitosan composite were determined using techniques such as XRD, FTIR, RAMAN, and SEM-EDX, respectively. The results show the anatase phase and homogenous spherical features of TiO2. The TiO2/CuO/Chitosan composites (0.5 gL-1) exhibited excellent activity for the photodegradation of MO under solar irradiation (λ > 400 nm) at different pH. The decolorization efficiency increased according to pH 9 < pH 7 < pH 6 < pH 3 with the highest degradation efficiency of 85.29% at 1 ppm MO solution, reaching two times greater than the pristine TiO2 nanoparticles (56.55%). Complete degradation of MO was attained at 240 min of solar irradiation with pH 3 using the optimum TiO2/CuO/Chitosan composites of 1:4:1 composition (5 cycles of dip coating) and the photodegradation rate constant is 0.0073 min−1. The physic-chemical study has established the structure, crystalline phase, surface contact, and stability of the catalyst. The photocatalytic improvement under visible irradiation is attributed to band-gap reduction and suspension of electron-hole recombination of the ternary catalyst system. The results of this study offer guidelines for the design of a new synthetic strategy.for the preparation of an efficient photocatalyst for the selective oxidation of synthetic azo dyes compounds.

3D Morphology Measurement for Blastocyst Evaluation From "All Angles".

Measuring the 3D morphology of spherical cell aggregates is required in both biology and medicine. Traditional methods either use fluorescent labeling, which cause cell toxicity and are unsuitable for clinical treatment, or use 2D images to roughly estimate 3D morphology. To overcome these limitations, this paper presents a quantitative label-free 3D morphology measurement technique using multi-view images. This technique, for the first time, enables the morphological evaluation of a blastocyst (Day 5 embryo) from "all angles" for IVF treatment. In this technique, a spherical rotation scale invariant feature transform (SR-SIFT) is proposed to address feature distortions for the rotation matrix calculation of the multi-view images. U-Net with generalized Dice loss is used to segment individual trophectoderm (TE) cells and the inner cell mass (ICM) of the blastocyst. Based on the rotation matrices and the segmentation results, the 3D morphological parameters of the entire blastocyst were quantified. Experimental results showed that the error of rotation angle was less than 1 °, the Dice was 95.6% for TE segmentation and 92.3% for ICM segmentation, and the overall measurement error of clinically defined blastocyst parameters was less than 6.7%.

CD44 targeted delivery of oncolytic Newcastle disease virus encapsulated in thiolated chitosan for sustained release in cervical cancer: a targeted immunotherapy approach.

Cervical cancer accounts for one of most common cancers among women of reproductive age. Oncolytic virotherapy has emerged as a promising immunotherapy modality but it comes with several drawbacks that include rapid clearance of virus from body due to immune-neutralization of virus in host. To overcome this, we encapsulated oncolytic Newcastle disease virus (NDV) in polymeric thiolated chitosan nanoparticles. For active targeting of virus loaded nanoformulation against CD44 (cluster of differentiation 44) receptors which are overly expressed on cancer cells, these nanoparticles were surface functionalized with hyaluronic acid (HA). Using half dose of NDV (TCID50 (50% tissue culture infective dose) single dose 3 × 105), virus loaded nanoparticles were prepared by green synthesis approach through ionotropic gelation method. Zeta analysis was performed to analyse size and charge on nanoparticles. Nanoparticles (NPs) shape and size were analysed by SEM (scanning electron microscope) and TEM (transmission electron microscope) while functional group identification was done by FTIR (fourier transform infrared) and XRD (X-ray diffraction). Viral quantification was done by TCID50 and Multiplicity of infection (MOI) determination while oncolytic potential of NPs encapsulated virus was analysed by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) assay and cell morphology analysis. Zeta analysis showed that average size of NDV loaded thiolated chitosan nanoparticles surface functionalized with HA (HA-ThCs-NDV) was 290.4nm with zeta potential of 22.3 mV and 0.265 PDI (polydispersity index). SEM and TEM analysis showed smooth surface and spherical features of nanoparticles. FTIR and XRD confirmed the presence of characteristic functional groups and successful encapsulation of the virus. In vitro release showed continuous but sustained release of NDV for up to 48 hours. TCID50 for HA-ThCs-NDV nanoparticles was 2.63x 106/mL titter and the nanoformulation exhibited high oncolytic potential in cell morphology analysis and MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) assay as compared to naked virus, in dose dependent manner. These findings suggest that virus encapsulation in thiolated chitosan nanoparticles and surface functionalization with HA is not only helpful in achieving active targeting while masking virus from immune system but, it also gives sustained release of virus in tumor microenvironment for longer period of time that increases bioavailability of virus.

Design and manufacturing of aspherical GaAs-SILs for a versatile optical semiconductor failure analysis system

In this study, we have developed an aspherical solid immersion lens (SIL) made of gallium arsenide (GaAs) for semiconductor failure analysis. A SIL is an optical component to dramatically increase the numerical aperture and the spatial resolution of a microscopy system by attaching it to the backside of the device-under-test. To further enhance the spatial resolution of the optical microscopy system, a shorter wavelength light source has also been introduced. In the past, we have developed a spherical SIL made of silicon (Si), which is the same material as the device under test. However, Si is not transparent for wavelengths shorter than around 1100 nm. To enable the use of a SIL at shorter wavelengths, we chose GaAs as SIL material, which is transparent at shorter wavelengths than Si and has a refractive index very close to that of Si. However, a spherical GaAs SIL features a more pronounced spherical aberration due to the difference in refractive index between the device-under-test (Si) and that of the SIL (GaAs) deteriorating the optical resolution of the microscopy system. We have therefore designed an aspherical GaAs-SIL which makes it possible to correct spherical aberration. We applied diamond tooling as a technique for manufacturing the SIL shape with a required surface irregularity below 100 nm peak-to-valley, resulting in a diffraction limited performance of the optical system for semiconductor failure analysis with a performance at around 0.18 μm cutoff.