3D Architecture Research Articles

Isosteric 3D Bicyclo[1.1.1]Pentane (BCP) Core-Based Lipids for mRNA Delivery and CRISPR/Cas Gene Editing.

Lipid nanoparticles (LNPs) are an essential component of messenger RNA (mRNA) vaccines and genome editing therapeutics. Ionizable amino lipids, which play the most crucial role in enabling mRNA to overcome delivery barriers, have, to date, been restricted to two-dimensional (2D) architectures. Inspired by improved physicochemical properties resulting from the incorporation of three-dimensionality (3D) into small-molecule drugs, we report the creation of 3D ionizable lipid designs through the introduction of bicyclo[1.1.1]pentane (BCP) core motifs. BCP-based lipids enabled efficient in vivo mRNA delivery to the liver and spleen with significantly greater performance over 2D benzene- and cyclohexane-based analogues. Notably, lead BCP-NC2-C12 LNPs mediated ∼90% reduction in the PCSK9 serum protein level via CRISPR/Cas9 gene knockout, outperforming 2D controls and clinically used DLin-MC3-DMA LNPs at the same dose. Here, we introduce BCP-based designs with superior in vivo activity, thereby expanding the chemical scope of ionizable amino lipids from 2D to 3D and offering a promising avenue to improve mRNA and gene editing efficiency for the continued development of genetic medicines.

Extension Doping with Low‐Resistance Contacts for P‐Type Monolayer WSe2 Field‐Effect Transistors

AbstractSource/Drain extension doping is crucial for minimizing the series resistance of the ungated channel and reducing the contact resistance of field‐effect transistors (FETs) in complementary metal–oxide–semiconductor (CMOS) technology. 2D semiconductors, such as MoS2 and WSe2, are promising channel materials for beyond‐silicon CMOS. A key challenge is to achieve extension doping for 2D monolayer FETs without damaging the atomically thin material. This work demonstrates extension doping with low‐resistance contacts for monolayer WSe2 p‐FETs. Self‐limiting oxidation transforms a bilayer WSe2 into a hetero‐bilayer of a high‐work‐function WOxSey on a monolayer WSe2. Then, damage‐free nanolithography defines an undoped nano‐channel, preserving the high on‐current of WOxSey‐doped FETs while significantly improving their on/off ratio. The insertion of an amorphous WOxSey interlayer under the contacts achieves record‐low contact resistances for monolayer WSe2 over a hole density range of 1012 to 1013 cm−2 (1.2 ± 0.3 kΩ µm at 1013 cm−2). The WOxSey‐doped extension exhibits a sheet resistance as low as 10 ± 1 kΩ □−1. Monolayer WSe2 p‐FETs with sub‐50 nm channel lengths reach a maximum drain current of 154 µA µm−1 with an on/off ratio of 107–108. These results define strategies for nanometer‐scale selective‐area doping in 2D FETs and other 2D architectures.

Advancing yeast cell analysis: A cryomethod for serial block-face scanning electron microscopy imaging in mitochondrial morphology studies.

Conventional Transmission Electron Microscopy analysis of biological samples often provides limited insights due to its inherent two-dimensional (2D) nature. This limitation hampers a comprehensive understanding of the three-dimensional (3D) complexity of cellular structures, occasionally leading to misinterpretations. Serial block-face scanning electron microscopy emerges as a powerful method for acquiring high-resolution 3D images of cellular volumes. By iteratively removing ultrathin sample sections and capturing images of each newly exposed surface, Serial block-face scanning electron microscopy allows for the meticulous reconstruction of a comprehensive 3D volume. In this study, we investigate the 3D architecture of altered mitochondrial morphologies in Saccharomyces cerevisiae using Serial block-face scanning electron microscopy imaging. We have developed a novel cryomethod based on plunge freezing and a dedicated freeze-substitution protocol. This protocol enhances ultrastructural preservation enabling a more accurate understanding of mitochondrial defects observed in 2D electron microscopy. Our findings underscore the utility of Serial block-face scanning electron microscopy coupled with optimized sample preparation techniques in elucidating complex cellular structures in 3D.

Ultrasmall Bismuth Nanoparticles Supported Over Nitrogen-Rich Porous Triazine-Piperazine Polymer for Efficient Catalytic Reduction.

The development of inexpensive and reusable nanocatalysts to convert the hazardous pollutant 4-nitrophenol (4-NP) into a valuable platform chemical 4-aminophenol (4-AP) is quite demanding due to environmental and public health concerns. Herein, we report a facile strategy for the preparation of supported Bi nanoparticles (NPs) over the surfaces of nitrogen-rich porous covalent triazine-piperazine-3D nanoflowers (BiNPs@3D-NCTP). SEM and TEM image analysis suggested 3D-flower-like morphology of the materials. The powder X-ray diffraction (PXRD) analysis also confirmed the loading of Bi NPs. N2 sorption analysis suggested BET surface areas of 663 and 364 m2g-1 for the 3D-NCTP and BiNPs@3D-NCTP materials, respectively. The large surface area, bimodal pores and 3D nanoflower architecture enable uniform loading of Bi nanoparticles, while its nitrogen-rich functionality stabilizes and acts as a capping agent restricting further nanoparticle expansion. BiNPs@3D-NCTP showed a 99.85% conversion for the 4-NP to 4-AP within four minutes. The normalized rate constant of 38.3 min-1 mg-1 of BiNPs@3D-NCTP catalyst for reducing of 4-NP suggested its superior catalytic efficiency. Nitrogen-rich functionality activates the catalytic site to accelerate the reaction, while bimodal pores can promote diffusion of reactant molecules. After five catalytic cycles, the nanocatalyst showed high chemical stability and negligible activity loss.

Molecular sociology of virus-induced cellular condensates supporting reovirus assembly and replication

Virus-induced cellular condensates, or viral factories, are poorly understood high-density phases where replication of many viruses occurs. Here, by cryogenic electron tomography (cryoET) of focused ion beam (FIB) milling-produced lamellae of mammalian reovirus (MRV)-infected cells, we visualized the molecular organization and interplay (i.e., “molecular sociology”) of host and virus in 3D at two time points post-infection, enabling a detailed description of these condensates and a mechanistic understanding of MRV replication within them. Expanding over time, the condensate fashions host ribosomes at its periphery, and host microtubules, lipid membranes, and viral molecules in its interior, forming a 3D architecture that supports the dynamic processes of viral genome replication and capsid assembly. A total of six MRV assembly intermediates are identified inside the condensate: star core, empty and genome-containing cores, empty and full virions, and outer shell particle. Except for star core, these intermediates are visualized at atomic resolution by cryogenic electron microscopy (cryoEM) of cellular extracts. The temporal sequence and spatial rearrangement among these viral intermediates choreograph the viral life cycle within the condensates. Together, the molecular sociology of MRV-induced cellular condensate highlights the functional advantage of transient enrichment of molecules at the right location and time for viral replication.

ANALISIS EFEKTIFITAS VISUALISASI PERMODELAN DESAIN ARSITEKTUR BERBASIS KECERDASAN BUATAN (AI)

This research focuses on the iteration of architectural modeling using artificial intelligence (AI) as a solution to generate visualization concepts in the architectural iteration process. It examines the development of AI in architecture and highlights AI's position in current architectural practice. AI has revolutionized the way architectural designs are developed, presented, and interpreted. With its ability to process complex data, AI accelerates the design process, enables the exploration of innovative solutions, and enhances understanding of projects before construction begins. AI is used in various applications, from automating visualizations to generating floor plans, opening new potentials in designing and visualizing architectural projects. However, the use of AI in architecture is still in its early stages, and challenges remain in applying AI to conceptual design stages. This research will analyze the effectiveness of AI in architectural modeling and design visualization, evaluating its impact on efficiency, creativity, and design output quality, and exploring limitations and future recommendations for AI use in architectural practice. Based on platform evaluations, MidJourney and DALL·E show superiority in visual quality and design accuracy, each with the highest scores. MidJourney and DALL·E are the top choices for creative and technical architectural visualization, while Leonardo AI and Bing AI show limitations in creativity and flexibility.

Effect of Lanthanum-Aluminum Co-Doping on Structure of Hafnium Oxide Ferroelectric Crystals.

Hafnium oxide (HfO2)-based devices have been extensively evaluated for high-speed and low-power memory applications. Here, the influence of aluminum (Al) and lanthanum (La) co-doping HfO2 thin films on the ferroelectric characteristics of hafnium-based devices is investigated. Among devices with different La/Al ratios, the Al and La co-doped hafnium oxide (HfAlAO) device with 4.2% Al and 2.17% La exhibited the excellent remanent polarization and thermostability. Meanwhile, first principal analyses verified that hafnium-based thin films with 4.2% Al and 2.17% La promoted the formation of the o-phase against the paraelectric phase, providing theoretical support for supporting experimental results. Furthermore, a vertical ferroelectric HfO2 memory based on 3D macaroni architecture is reported. The devices show excellent ferroelectric characteristics of 22 µCcm-2 under 4.5 MVcm-1 and minimal coercive field of ≈1.6V. In addition, the devices exhibit great memory performance, including the response speed of device can achieve 20ns and endurance characteristic can achieve 1010 cycles.

Capillarity‐Assisted 3D Patterning of Liquid Metal

AbstractFlexible electronics with sophisticated 3D architectures enable multidimensional functionalities and multi‐component integration, thus surpassing their 2D counterparts in soft robotics and wearable sensors. Because of its unique metallic and fluidic characteristics, liquid metal (LM) has proven to be an excellent material for fabricating flexible electronics. However, its low viscosity and high surface tension have primarily restricted LM to the creation of 2D‐patterned films on flat surfaces, significantly limiting the complexity and functionality of the resulting flexible devices. In this work, inspired by the capillary‐driven liquid flow in a hierarchical lattice matrix, a 3D patterning method is proposed for LM and extended to the fabrication of porous materials with flexible conductivity. The feasibility and versatility of the proposed method are showcased by fabricating tunable electromagnetic interference shielding materials, programmable 3D circuits, and customizable wearable sensors, highlighting its potential for promoting the development of integrated circuits and wearable electronics.

Pelophen B is a non-taxoid binding microtubule-stabilizing agent with promising preclinical anticancer properties

Taxanes, such as paclitaxel (PTX), stabilize microtubules and are used as a first-line therapy in multiple cancer types. Disruption of microtubule equilibrium, which plays an essential role in mitosis and cell homeostasis, ultimately results in cell death. Even though PTX is a very potent chemotherapy, its use is associated with major side effects and therapy resistance. Pelophen B (PPH), a synthetic analog of peloruside A, stabilizes microtubules through interaction with a non-taxoid binding site of β-tubulin. We evaluated the anticancer effect of PPH in a variety of tumor types by using established cell lines, early-passage cultures and ex vivo tumor-derived cultures that preserve the 3D architecture of the tumor microenvironment. PPH significantly blocks colony formation capacity, reduces viability and exerts additivity with PTX. Interestingly, PPH overcomes resistance to PTX. Mechanistically, PPH induces a G2/M cell cycle arrest and increases the presence of tubulin polymerization promoting protein (TPPP), inducing lysine 40 acetylation of α-tubulin. Although, results induced by paclitaxel or PPH are concordant, PPH’s unique microtubule binding mechanism enables PTX additivity and ensures overcoming PTX-induced resistance. In conclusion, PPH results in remarkable anti-cancer activity in a range of preclinical models supporting further clinical investigation of PPH as a therapeutic anticancer agent.

Three-Dimensional Porous Ti Supported Ni/Sb Co-doped SnO2 Anode for Electrocatalytic Production of Ozone

Electrochemical ozone (O3) production (EOP) offers a promising green alternative for in situ generating high concentration, strongly oxidizing O3. However, its progress is hindered by low durability and poor Faradaic efficiency of the anodes. Herein, a nanosheet-structured nickel and antimony co-doped tin dioxide (Ni/Sb-SnO2) is directly grown on three-dimensional porous titanium (3D-PTi), achieving enhanced EOP performance. The 3D architecture and Ni/Sb co-doping synergistically improve both activity and stability, making it a highly efficient and durable EOP anode. The Ni/Sb-SnO2@3D-PTi anode achieved a Faradaic efficiency above 28% with an energy consumption of 25.44Whg⁻1 at 20mAcm-2 in 0.5M H2SO4, surpassing other SnO2-based comparative anodes. It maintains excellent stability for over 25h at 100mAcm-2. Furthermore, the high-flow O3 generated in situ effectively removes 97% of tetracycline within 2h, with a Total Organic Carbon (TOC) reduction of 66.1%. This work demonstrates the strong potential of EOP-derived advanced oxidation processes for environmental remediation.

Statistical curve models for inferring 3D chromatin architecture

Statistical curve models for inferring 3D chromatin architecture

Salt template synthesis of CoO@Co nanoparticles encapsulated in 3D porous nitrogen‐doped carbon for oxygen reduction reaction

AbstractDeveloping high performance and cost‐effective electrocatalysts toward oxygen reduction reaction (ORR) is of critical significance for fuel cells and metal–air batteries. Herein, CoO@Co nanoparticles encapsulated in three‐dimensional (3D) porous nitrogen‐doped carbon (CoO@Co/Co‐N‐C) have been successfully derived from the cobalt–tannin framework via the NH4Cl salt template strategy. Owing to the generated NH3 and HCl gas from NH4Cl during the pyrolysis process, CoO@Co/Co‐N‐C formed a 3D porous carbon architecture with ultrahigh‐specific surface area (1052.5 m2 g−1). This hybrid catalyst exhibits comparable ORR catalytic activity, as well as superior stability to 20 wt% Pt/C in alkaline conditions. This finding offers a novel and facile strategy to synthesize 3D porous carbon as non‐precious metal electrocatalysts for energy conversion and storage applications.

Reconstructed three-dimensional structure of gas-foamed polycaprolactone/cellulose nanofibrous scaffold for biomedical applications

One of the unavoidable issues with the bio-scaffolding process is the collapse of the visually appealing external three-dimensional (3D) sponge-like structure and the internal porous and multilayered morphology of a gas-foamed nanofibrous scaffold. Herein, a gas-foamed polycaprolactone/cellulose (g-PCL/CL) nanofibers scaffold is first prepared by electrospinning PCL/cellulose acetate, followed by deacetylation and then Sodium borohydride-assisted gas-foaming technique. The deformed 3D architecture of g-PCL/CL nanofiber is finally reconstructed by mixing it with chitosan (CS) solution and molding. This straightforward method leverages the mechanical strength of PCL, the hydrophilic properties of CL, and the curing characteristics of chitosan. The physical characterization validated the successful reformation of the 3D architecture of the CS + PCL/CL scaffold demonstrating the unique porous interior structure assembled with nanofiber-reinforced pore walls. This molding process with chitosan solution enables the formation of mechanically enhanced 3D scaffolds with improved structural integrity, as evidenced by the increased compressive strength of the CS + PCL/CL scaffold (~95 kPa). In vitro studies further demonstrate improved cell adhesion, differentiation, and proliferation for the CS + PCL/CL scaffold. These findings suggest that the structurally reconstructed CS + PCL/CL composite scaffold possesses suitable characteristics to act as a potential bioscaffold, paving the way for promising strategies to retain the structural integrity of collapse scaffolds.

A Testbed for Tidal Migration: The 3D Architecture of an Eccentric Hot Jupiter HD 118203 b Accompanied by a Possibly Aligned Outer Giant Planet

Characterizing outer companions to hot Jupiters plays a crucial role in deciphering their origins. We present the discovery of a long-period giant planet, HD 118203 c ( mc=11.79−0.63+0.69MJ , ac=6.28−0.11+0.10 au) exterior to a close-in eccentric hot Jupiter HD 118203 b (P b = 6.135 days, m b = 2.14 ± 0.12 M J, r b = 1.14 ± 0.029 R J, e b = 0.31 ± 0.007) based on 20 yr radial velocities (RVs). Using Rossiter–McLaughlin (RM) observations from the Keck Planet Finder, we measured a low sky-projected spin–orbit angle λb=−11°7−10.0+7.6 for HD 118203 b and detected stellar oscillations in the host star, confirming its evolved status. Combining the RM observation with the stellar inclination measurement, we constrained the true spin–orbit angle of HD 118203 b as Ψ b < 33.°5 (2σ), indicating the orbit normal of the hot Jupiter nearly aligned with the stellar spin axis. Furthermore, by combining RVs and Hipparcos-Gaia astrometric acceleration, we constrained the line-of-sight mutual inclination between the hot Jupiter and the outer planet to be 9.°8−9.3+16.2 at the 2σ level. HD 118203 is one of first hot Jupiter systems where both the true spin–orbit angle of the hot Jupiter and the mutual inclination between inner and outer planets have been determined. Our results are consistent with a system-wide alignment, with low mutual inclinations between the outer giant planet, the inner hot Jupiter, and the host star. This alignment, along with the moderate eccentricity of HD 118203 c, implies that the system may have undergone coplanar high-eccentricity tidal migration. Under this framework, our dynamical analysis suggests an initial semimajor axis of 0.3–3.2 au for the proto–hot Jupiter.

Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap.

Disentangling brain aging from disease-related neurodegeneration in patients with multiple sclerosis (PwMS) is increasingly topical. The brain-age paradigm offers a window into this problem but may miss disease-specific effects. In this study, we investigated whether a disease-specific model might complement the brain-age gap (BAG) by capturing aspects unique to MS. In this retrospective study, we collected 3D T1-weighted brain MRI scans of PwMS to build (1) a cross-sectional multicentric cohort for age and disease duration (DD) modeling and (2) a longitudinal single-center cohort of patients with early MS as a clinical use case. We trained and evaluated a 3D DenseNet architecture to predict DD from minimally preprocessed images while age predictions were obtained with the DeepBrainNet model. The brain-predicted DD gap (the difference between predicted and actual duration) was proposed as a DD-adjusted global measure of MS-specific brain damage. Model predictions were scrutinized to assess the influence of lesions and brain volumes while the DD gap was biologically and clinically validated within a linear model framework assessing its relationship with BAG and physical disability measured with the Expanded Disability Status Scale (EDSS). We gathered MRI scans of 4,392 PwMS (69.7% female, age: 42.8 ± 10.6 years, DD: 11.4 ± 9.3 years) from 15 centers while the early MS cohort included 749 sessions from 252 patients (64.7% female, age: 34.5 ± 8.3 years, DD: 0.7 ± 1.2 years). Our model predicted DD better than chance (mean absolute error = 5.63 years, R2 = 0.34) and was nearly orthogonal to the brain-age model (correlation between DD and BAGs: r = 0.06 [0.00-0.13], p = 0.07). Predictions were influenced by distributed variations in brain volume and, unlike brain-predicted age, were sensitive to MS lesions (difference between unfilled and filled scans: 0.55 years [0.51-0.59], p < 0.001). DD gap significantly explained EDSS changes (B = 0.060 [0.038-0.082], p < 0.001), adding to BAG (ΔR2 = 0.012, p < 0.001). Longitudinally, increasing DD gap was associated with greater annualized EDSS change (r = 0.50 [0.39-0.60], p < 0.001), with an incremental contribution in explaining disability worsening compared with changes in BAG alone (ΔR2 = 0.064, p < 0.001). The brain-predicted DD gap is sensitive to MS-related lesions and brain atrophy, adds to the brain-age paradigm in explaining physical disability both cross-sectionally and longitudinally, and may be used as an MS-specific biomarker of disease severity and progression.

Facile fabrication of lightweight and three-dimensional porous Dy2O3 decorated single-walled carbon nanotubes/reduced graphene oxide composite aerogels for broadband microwave absorption

Reduced graphene oxide aerogel (GA) has emerged as a promising microwave absorbing (MA) material. However, it remains a challenge for pure GA to achieve excellent MA performance owing to the limitation of loss model and impedance mismatching. Herein, a 0D@1D/2D construction of Dy2O3 decorated single-walled carbon nanotubes/reduced graphene oxide (Dy2O3@SWCNT/rGO) composite aerogel (DCGA) with high-performance electromagnetic wave (EMW) absorption was successfully obtained using a simple reduction self-assembly process. The DCGA features a distinctive 3D porous network formed by the stacking of lamellar rGO and has a low bulk density. As expected, the microwave attenuation performance of the DCGA exhibits a level of tunability that can be achieved by varying the mass ratio of GO along with Dy2O3@SWCNT. Benefiting from synergistic effect, the resulted ultralight DCGA-3 (4.6 mg/cm−3) exhibits a strong reflection loss (RL) of −57.6 dB (3 mm) at 13 GHz and a low filler loading ratio of ca. 1.4 wt%. Further, the maximal effective absorption bandwidth (EAB) (RL < −10 dB) of DCGA-1 can reach 7.8 GHz (10.2–18 GHz) with a thickness of 2.8 mm. Notably, the EAB of DCGA can completely cover X band and Ku band by adjusting the thickness. The excellent EMW absorbing ability was originated from the combined influence of optimized impedance matching, a distinctive multidimensional porous structure, a leaf-like conductive network and the presence of numerous defects and interfaces. Consequently, this research may aid in the development of graphene-infused hybrid composites featuring a 3D porous architecture, serving as lightweight and efficient absorbers of EMWs.

Early Detection of Macular Atrophy Automated Through 2D and 3D Unet Deep Learning

Macular atrophy (MA) is an irreversible endpoint of age-related macular degeneration (AMD), which is the leading cause of blindness in the world. Early detection is therefore an unmet need. We have developed a novel automated method to identify MA in patients undergoing follow-up with optical coherence tomography (OCT) for AMD based on the combination of 2D and 3D Unet architecture. Our automated detection of MA relies on specific structural changes in OCT, including six established atrophy-associated lesions. Using 1241 volumetric OCTs from 125 eyes (89 patients), the performance of this combination Unet architecture is extremely encouraging, with a mean dice similarity coefficient score of 0.90 ± 0.14 and a mean F1 score of 0.89 ± 0.14. These promising results have indicated superiority when compared to human graders, with a mean similarity of 0.71 ± 0.27. We believe this deep learning-aided tool would be useful to monitor patients with AMD, enabling the early detection of MA and supporting clinical decisions.

Mouse Small Intestinal Organoid Cultures.

The intestinal epithelium is a highly dynamic and self-renewing tissue that is crucial for maintaining gut homeostasis. It can be cultured in vitro from isolated crypts to form three-dimensional (3D) intestinal organoids. These organoids have the ability to proliferate and differentiate into various epithelial cell lineages, offering a more physiologically relevant model compared to traditional two-dimensional (2D) culture systems. Mesenchymal cells, located near epithelial cells, regulate epithelial behavior through paracrine signaling and provide structural support. Building on recent advances in the biology of epithelial and mesenchymal cells, we have developed a coculture system that integrates intestinal organoids with mesenchymal cells. In this system, intestinal organoids are cultured in direct or indirect contact with mesenchymal cells, allowing for the simulation of signal exchange and interactions within the in vivo-like microenvironment. This coculture system not only preserves the 3D architecture of the organoids but also enhances their physiological relevance by introducing cellular complexity. The system is capable of long-term maintenance and is adaptable to a wide range of experimental manipulations. As such, this coculture model serves as a powerful tool for studying the interactions between the intestinal epithelium and its surrounding stroma, providing new insights into stem cell biology, tissue regeneration, and disease mechanisms. Here, we introduce the methods of mouse crypt isolation, intestinal organoid culture, and its coculture with mesenchymal cell.

2025 Roadmap on 3D Nano-magnetism.

The transition from planar (2D) to three-dimensional (3D) magnetic nanostructures represents a significant advancement in both fundamental research and practical applications, offering vast potential for next-generation technologies like ultrahigh-density storage, memory, logic, and neuromorphic computing. Despite being a relatively new field, the emergence of 3D nanomagnetism presents numerous opportunities for innovation, prompting the creation of a comprehensive roadmap by leading international researchers. This roadmap aims to facilitate collaboration and interdisciplinary dialogue to address challenges in materials science, physics, engineering, and computing.&#xD;The roadmap comprises eighteen sections, roughly divided into three parts. The first section explores the fundamentals of 3D nanomagnetism, focusing on recent trends in fabrication techniques and imaging methods crucial for understanding complex spin textures, curved surfaces, and small-scale interactions. Techniques such as two-photon lithography and focused electron beam-induced deposition enable the creation of intricate 3D architectures, while advanced imaging methods like electron holography and Lorentz electron Ptychography provide sub-nanometer resolution for studying magnetization dynamics in three dimensions. Various 3D magnetic systems, including coupled multilayer systems, artificial spin ice, magneto-plasmonic systems, topological spin textures, and molecular magnets, are discussed.&#xD;The second section introduces analytical and numerical methods for investigating 3D nanomagnetic structures and curvilinear systems, highlighting geometrically curved architectures, interconnected nanowire systems, and other complex geometries. Finite element methods are emphasized for capturing complex geometries, along with direct frequency domain solutions for addressing magnonic problems.&#xD;The final section focuses on 3D magnonic crystals and networks, exploring their fundamental properties and potential applications in magnonic circuits, memory, and spintronics. Computational approaches using 3D nanomagnetic systems and complex topological textures in 3D spintronics are highlighted for their potential to enable faster and more energy-efficient computing.&#xD.

MRI-Enhanced metastatic ovarian tumour detection: leveraging enhanced 3D CNN and Data augmentation for exceptional accuracy

ABSTRACT Metastatic Ovarian Tumour remains a challenging medical condition that occurs in the ovaries of female reproductive organs. This severe disease may reduce the life span of the affected person by causing serious effects like imbalanced hormones, improper digestive system, pelvic pain and fertility issues leading to depression. The proposed model employs a 3D CNN architecture, proven effective in image classification tasks, to analyse MRI scans. A few existing approaches have used 2D CNN to detect the tumour, but it is lacking in capturing spatial and temporal features of MRI, which leads to information loss. The MRI-based model achieved an impressive accuracy of 98.6%, showcasing its potential as a valuable tool for early diagnosis. This level of accuracy holds promise for clinical applications, allowing for timely interventions and improved patient life span in cases of ovarian cancer.