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At least 37 records · Page 2

Physics of Quantum Structures in Photovoltaic Devices

There has been considerable activity recently regarding the possibilities of using various nanostructures and nanomaterials to improve photovoltaic conversion of solar energy. Recent theoretical results indicate that dramatic improvements in device efficiency may be attainable through the use of three-dimensional arrays of zero-dimensional conductors (i.e., quantum dots) in an ordinary p-i-n solar cell structure. Quantum dots and other nanostructured materials may also prove to have some benefits in terms of temperature coefficients and radiation degradation associated with space solar cells. Two-dimensional semiconductor superlattices have already demonstrated some advantages in this regard. It has also recently been demonstrated that semiconducting quantum dots can also be used to improve conversion efficiencies in polymeric thin film solar cells. Improvement in thin film cells utilizing conjugated polymers has also be achieved through the use of one-dimensional quantum structures such as carbon nanotubes. It is believed that carbon nanotubes may contribute to both the disassociation as well as the carrier transport in the conjugated polymers used in certain thin film photovoltaic cells. In this paper we will review the underlying physics governing some of the new photovoltaic nanostructures being pursued, as well as the the current methods being employed to produce III-V, II-VI, and even chalcopyrite-based nanomaterials and nanostructures for solar cells.

Raffaelle, Ryne P.↗

The Influence of Tungsten on the Chemical Composition of a Temporally Evolving Nanostructure of a Model Ni-Al-Cr Superalloy

The influence of W on the temporal evolution of gamma' precipitation toward equilibrium in a model Ni-Al-Cr alloy is investigated by three-dimensional atom-probe (3DAP) microscopy and transmission electron microscopy (TEM). We report on the alloys Ni-10 Al-8.5 Cr (at.%) and Ni-10 Al-8.5 Cr-2 W (at.%), which were aged isothermally in the gamma + gamma' two-phase field at 1073 K, for times ranging from 0.25 to 264 h. Spheroidal-shaped gamma' precipitates, 5-15 nm diameter, form during quenching from above the solvus temperature in both alloys at a high number density (approx. 10(exp 23/cu m). As gamma' precipitates grow with aging at 1073 K, a transition from spheriodal- to cuboidal-shaped precipitates is observed in both alloys. The elemental partitioning and spatially resolved concentration profiles across the gamma' precipitates are obtained as a function of aging time from three-dimensional atom-by-atom reconstructions. Proximity histogram concentration profiles of the quaternary alloy demonstrate that W concentration gradients exist in gamma' precipitates in the as-quenched and 0.25-h aging states, which disappear after 1 h of aging. The diffusion coefficient of W in gamma' is estimated to be 6.2 x 10(exp -20) sq m/s at 1073 K. The W addition decreases the coarsening rate constant, and leads to stronger partitioning of Al to gamma' and Cr to gamma.

Sudbrack, Chantal K.↗

The Role of Rhenium on the Temporal Evolution of the Nanostructure of a Model Ni-Al-Cr-Re Superalloy

Rhenium (2 at.%) additions to a model Ni-8.5 at.% Cr-10 at.% Al alloy are studied with respect to its effects on the temporal evolution of the nanostructure and the partitioning behavior of the four elements between the gamma (fcc) and gamma' (L1(sub 2)) phases. Chemical evolution of this quaternary alloy aged at 1073 K from 0.25 to 264 h, is investigated by three-dimensional atom-probe (3DAP) microscopy. The morphology of gamma'-precipitates remains spheroidal, even at an aging time of 264 h. The results demonstrate that Re slows the coarsening of gamma'-precipitates, in comparison to the ternary Ni-10 at.% A1-8.5 at.% Cr alloy at 1073 K.

Yoon, Kevin E.↗

The Temporal Evolution of the Nanostructure of a Model Ni-Al-Cr Superalloy

The early to the later stages of precipitation of ordered gamma'-precipitates (L1(sub 2)) in Ni-5.2 Al-14.2 Cr (at.%) are studied at 873 K. Precipitates with radii as small as 0.45 nm are characterized fully by three-dimensional atom-probe (3DAP) microscopy. Contrary to what is often assumed by theory or in models, the average precipitate composition is shown to evolve with time, such that solute concentrations decrease toward an equilibrium value given by the solvus lines. Power-law time dependencies of the number density, mean radius, and supersaturations of Al and Cr are discussed in light of theoretical predictions for Ostwald ripening.

Sudbrack, Chantal K.↗

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs

Applications of deep learning (DL) to design nanomaterials are hampered by a lack of suitable data representations and training data. Here, in this study, we report efforts to overcome these limitations and leverage DL to optimize the nonlinear optical properties of core–shell upconverting nanoparticles (UCNPs). UCNPs, which have applications in fields such as biosensing, super-resolution microscopy and three-dimensional printing, can emit visible and ultraviolet light from near-infrared excitations. We report a large-scale dataset of UCNP emission spectra based on accurate but expensive kinetic Monte Carlo simulations (N > 6,000) and use these data to train a heterogeneous graph neural network using a physically motivated representation of UCNP nanostructure. Applying gradient-based optimization on the trained graph neural network, we identify structures with 6.5× higher predicted emission under 800-nm illumination than any UCNP in our training set. Our work reveals design principles for UCNP heterostructures and presents a roadmap for DL-based inverse design of nanomaterials.

Sivonxay, Eric [Lawrence Berkeley National Laborat↗

NASA Tech Briefs, April 2005

Gas-Tolerant Device Senses Electrical Conductivity of Liquid Nanoactuators Based on Electrostatic Forces on Dielectrics Replaceable Microfluidic Cartridges for a PCR Biosensor CdZnTe Image Detectors for Hard-X-Ray Telescopes High-Aperture-Efficiency Horn Antenna Full-Circle Resolver-to-Linear-Analog Converter Continuous, Full-Circle Arctangent Circuit Advanced Three-Dimensional Display System Automatic Focus Adjustment of a Microscope Topics covered include: FastScript3D - A Companion to Java 3D; Generating Mosaics of Astronomical Images; Simulating Descent and Landing of a Spacecraft; Simulating Vibrations in a Complex Loaded Structure; Rover Sequencing and Visualization Program; Software Template for Instruction in Mathematics; Support for User Interfaces for Distributed Systems; Nanostructured MnO2-Based Cathodes for Li-Ion/Polymer Cells; Multi-Layer Laminated Thin Films for Inflatable Structures; Two-Step Laser Ranging for Precise Tracking of a Spacecraft; Growing Aligned Carbon Nanotubes for Interconnections in ICs; Multilayer Composite Pressure Vessels; Texturing Blood-Glucose-Monitoring Optics Using Oxygen Beams; Fault-Tolerant Heat Exchanger; Atomic Clock Based on Opto-Electronic Oscillator; Microfocus/Polycapillary-Optic Crystallographic X-Ray Sys; Depth-Penetrating Luminescence Thermography of Thermal- Barrier Coatings; One-Dimensional Photonic Crystal Superprisms; Measuring Low-Order Aberrations in a Segmented Telescope; Mapping From an Instrumented Glove to a Robot Hand; Application of the Hilbert-Huang Transform to Financial Data; Optimizing Parameters for Deep-Space Optical Communication; and Low-Shear Microencapsulation and Electrostatic Coating.

Source record↗

Tutorial: Machine-Learning-Based CREASE-2D Analysis of 2D SAXS Profiles to Characterize Anisotropic Nanostructures in Soft Materials

We present a tutorial to guide users on how to extend the Computational Reverse Engineering Analysis of Scattering Experiments-2D (CREASE-2D) framework to interpret their experimental two-dimensional small-angle scattering (SAS) data from soft materials (e.g., polymers, peptide amphiphiles, biomolecular fibrils). Unlike most traditional SAS analysis approaches, which typically rely on azimuthally averaged onedimensional (1D) profiles, CREASE-2D utilizes the complete 2D scattering profile to reveal information about anisotropy in the structure. In past applications, CREASE has provided insights into complex structural features, including the cross-sectional shapes of assembled nanostructures and dispersity in these features, which are difficult to discern with existing analytical models. While (1D- ) CREASE has been applied to SANS and SAXS data, this tutorial shares the steps for implementing CREASE-2D using an example of a dipeptide solution system, for which we have SAXS data. We present details for these steps involved in using CREASE-2D to interpret SAXS profiles: how to preprocess SAXS data, define relevant structural features, generate three-dimensional real-space structures for specific values of these features, train a machine learning (ML) surrogate model to predict scattering profiles for given structural features, and optimize these features using genetic algorithms (GA). Then, we use these steps to interpret complex 2DSAXS data collected from dipeptide solutions that, in microscopy images, exhibit nanoscale structures that could be elliptical tubes/ flat tapes/cylinders or a combination of these cross sections. Open-source codes, computational hardware, and software requirements, as well as the strengths and limitations of this protocol, are also presented. We expect researchers working with (soft) biomaterials, peptide amphiphiles, amphiphilic polymer solutions, polymer nanocomposites, and blends of particles/polymers will find this CREASE-2D method and this tutorial of use.

CREASE↗

Machine learning approaches for intentional materials engineering

In this article, the development of nanoporous metals and metallic composites through dealloying processes presents significant opportunities in materials engineering. However, designing multicomponent precursor alloys and establishing corresponding processing methods that yield predictable compositions and nanostructures remain a complex challenge. This article explores how machine learning (ML)-augmented computational and experimental methodologies can tackle these challenges by predicting precursor alloy compositions, final nanoporous structures, and mechanical properties, while integrating ML-enabled autonomous experimentation for material design and quantification. We highlight recent advancements in applying ML to nanostructured materials design via dealloying and discuss how techniques from other nanomaterial designs can be adapted for improved control over morphological and compositional outcomes in nanoporous and nanocomposite materials. Furthermore, we explore the role of ML in autonomous synchrotron x-ray experimentation, enabling real-time feedback between modeling and experimental setups. ML-driven approaches to microstructure characterization and mechanical property prediction are also examined, with a focus on modeling and advanced imaging techniques such as three-dimensional nanotomography. Finally, this article outlines future directions for ML-enhanced materials science, emphasizing the exploration of high-dimensional parameter spaces and the incorporation of materials kinetics into processing and property evaluation, ultimately advancing the design of nanoporous structures and materials science.

36 MATERIALS SCIENCE↗

Visualizing Size-Dependent Dynamics of CeO 2-δ {100}-Supported CoO x Nanoparticles Under CO 2 Hydrogenation Conditions

Carbon dioxide is a major greenhouse gas. In order to optimize processes focused on its chemical valorization, one needs detailed information about the effects of CO 2 and/or CO 2 /H 2 mixtures on the structure and morphology of metal/oxide catalysts. Here, in this study, the evolution of a catalyst with cobalt supported on CeO 2 -cube nanostructures under CO 2 hydrogenation conditions was investigated by using a set of in situ characterization techniques (X-ray absorption fine structure, X-ray diffraction, diffuse reflectance infrared Fourier transform spectroscopy, and environmental transmission electron microscopy (TEM)). The {100} facets of the ceria support displayed an unexpectedly high stability due to strong interactions with the aggregates of cobalt oxide. A significant influence of interfacial bonding between CoO x and CeO 2-δ {100} is evident through a clear preference in the orientation of CoO x nanoparticles (NPs) with respect to the substrate. For initially reduced Co/CeO 2 -cube nanostructures, a kinetically controlled oxidation of cobalt upon the introduction of CO 2 was observed during the early stages of CO 2 hydrogenation. Environmental TEM revealed the size-dependent morphological behavior of cobalt oxide NPs due to strong interactions with the CeO 2 {100} surface. When the environment was switched from H 2 to a mixture of H 2 and CO 2 at 250 °C, small CoO x NPs (in the largest dimension < 2.5 nm) rapidly transformed from a pyramidal three-dimensional (3D) form to a planar, monatomic layer attached to the concurrently oxidized CeO 2-δ {100} surface. This maximizes the number of sites available for the binding of CO 2 or reaction intermediates. The shape transformation reflected the oxophilic character of cobalt and strong metal–support interactions. The removal of CO 2 from the gas phase led to a reduction of the cobalt oxide NPs by hydrogen and a reversible two-dimensional → 3D transformation. In contrast, no significant morphological changes, apart from further oxidation, were observed for big CoO x NPs (in the largest dimension > 3 nm). These trends are not seen for nanoparticles of noble metals. The observed morphological and structural changes in the small CoO x NPs affected the stability of reaction intermediates and modified the selectivity of the CoO x /CeO 2 catalyst system for methane production.

36 MATERIALS SCIENCE↗

Superhydrophobic Array Devices for the Enhanced Formation of 3D Cancer Models

During the metastatic cascade, cancer cells travel through the bloodstream as circulating tumor cells (CTCs) to a secondary site. Clustered CTCs have greater shear stress and treatment resistance, yet their biology remains poorly understood. We therefore engineered a tunable superhydrophobic array device (SHArD). The SHArD-C was applied to culture a clinically relevant model of CTC clusters. Using our device, we cultured a model of cancer cell aggregates of various sizes with immortalized cancer cell lines. These exhibited higher E-cadherin expression and are significantly more capable of surviving high fluid shear stress-related forces compared to single cells and model clusters grown using the control method, helping to explain why clustering may provide a metastatic advantage. Additionally, the SHArD-S, when compared with the AggreWell 800 method, provides a more consistent spheroid-forming device culturing reproducible sizes of spheroids for multiple cancer cell lines. Overall, we designed, fabricated, and validated an easily tunable engineered device which grows physiologically relevant three-dimensional (3D) cancer models containing tens to thousands of cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing the three-dimensional arrangement of polar topology in nanoparticles

In the early 2000s, low dimensional ferroelectric systems were predicted to have topologically nontrivial polar structures, such as vortices or skyrmions, depending on mechanical or electrical boundary conditions. A few variants of these structures have been experimentally observed in thin film model systems, where they are engineered by balancing electrostatic charge and elastic distortion energies. However, the measurement and classification of topological textures for general ferroelectric nanostructures have remained elusive, as it requires mapping the local polarization at the atomic scale in three dimensions. Here we unveil topological polar structures in ferroelectric BaTiO3 nanoparticles via atomic electron tomography, which enables us to reconstruct the full three-dimensional arrangement of cation atoms at an individual atom level. Our three-dimensional polarization maps reveal clear topological orderings, along with evidence of size-dependent topological transitions from a single vortex structure to multiple vortices, consistent with theoretical predictions. The discovery of the predicted topological polar ordering in nanoscale ferroelectrics, independent of epitaxial strain, widens the research perspective and offers potential for practical applications utilizing contact-free switchable toroidal moments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Nanoparticle self-assemblies with modern complexity

Thanks to decades of tireless efforts, nanoparticle assemblies have reached at an extremely high level of controllability, sophistication, and complexity, with new insights provided by integration with graph theory, cutting-edge characterization, and machine learning (ML)-based computation and modeling, as well as with ever-diversifying applications in energy, catalysis, biomedicine, optics, electronics, magnetics, organic biosynthesis, and quantum technology. Nanoparticle assemblies can be crystalline, known as superlattices or supracrystals. Their assembly entails a transition from disorder—dispersed nanoparticles—to order, which can be achieved through classical nucleation pathways or nonclassical pathways via prenucleation precursors or particle aggregation. Further, the periodic lattices allow facile manipulations of electrons, phonons, photons, and even spins, leading to advanced device components and metamaterials. Meanwhile, aperiodic assemblies out of nanoparticles, such as gels, networks, and amorphous solids, also start to attract attentions. Despite the loss of periodicity, symmetry-lowering or symmetry-breaking three-dimensional (3D) structures emerge with unique properties, such as chiroptical activity, topological mechanical strength, and quantum entanglement. Real-space imaging such as electron microscopy and X-ray based tomography methods are utilized to characterize these complex structures, while mathematical tools such as graph theories are in need to describe such complex structures. This issue aims to provide a timely review of the efforts in this greatly broadened materials design space including experiment, simulation, theory, and applications. Nine top experts (and their teams) from four countries deliver six review papers, summarizing fundamental mechanistic understandings of nanoparticle assemblies, highlighted with the developments of state-of-the-art in situ characterization tools and ML-assisted reverse engineering, and newly emergent applications of nanoarchitectures.

36 MATERIALS SCIENCE↗

STORM Super-Resolution Visualization of Self-Assembled γPFD Chaperone Ultrastructures in Methanocaldococcus jannaschii

Gamma-prefoldin (γPFD), a unique chaperone found in the extremely thermophilic methanogen Methanocaldococcus jannaschii, self-assembles into filaments in vitro, which so far have been observed using transmission electron microscopy and cryo-electron microscopy. Utilizing three-dimensional stochastic optical reconstruction microscopy (3D-STORM), here we achieve ~20 nm resolution by precisely locating individual fluorescent molecules, hence resolving γPFD ultrastructure both in vitro and in vivo. Through CF647 NHS ester labeling, we first demonstrate the accurate visualization of filaments and bundles with purified γPFD. Next, by implementing immunofluorescence labeling after creating a 3xFLAG-tagged γPFD strain, we successfully visualize γPFD in M. jannaschii cells. Through 3D-STORM and two-color STORM imaging with DNA, we show the widespread distribution of filamentous γPFD structures within the cell. These findings provide valuable insights into the structure and localization of γPFD, opening up possibilities for studying intriguing nanoscale components not only in archaea but also in other microorganisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanically Strong, Polymer Cross-linked Aerogels (X-Aerogels)

Aerogels comprise a class of low-density, high porous solid objects consisting of dimensionally quasi-stable self-supported three-dimensional assemblies of nanoparticles. Aerogels are pursued because of properties above and beyond those of the individual nanoparticles, including low thermal conductivity, low dielectric constant and high acoustic impedance. Possible applications include thermal and vibration insulation, dielectrics for fast electronics, and hosting of functional guests for a wide variety of optical, chemical and electronic applications. Aerogels, however, are extremely fragile materials, hence they have found only limited application in some very specialized environments, for example as Cerenkov radiation detectors in certain types of nuclear reactors, aboard spacecraft as collectors of hypervelocity particles (refer to NASA's Stardust program) and as thermal insulators on planetary vehicles on Mars (refer to Sojourner Rover in 1997 and Spirit and Opportunity in 2004). Along these lines, the X-Aerogel is a new NASA-developed strong lightweight material that has resolved the fragility problem of traditional (native) aerogels. X-Aerogels are made by applying a conformal polymer coating on the surfaces of the skeletal nanoparticles of native aerogels (see Scanning Electron Micrographs). Since the relative amounts of the polymeric crosslinker and the backbone are comparable, X-Aerogels can be viewed either as aerogels modified by the templated accumulation of polymer on the skeletal nanoparticles, or as nanoporous polymers made by remplated casting of polymer on a nanostructured framework. The most striking feature of X-Aerogels is that for a nominal 3-fold increase in density (still a ultralighweight material), the mechanical strength can be up to 300 times higher than the strength of the underlying native aerogel. Thus, X-Aerogels combine a multiple of the specific compressive strength of steel, with the the thermal conductivity of styrofoam. X-Aerogels have been demonstrated with several polymers such as polyurethanes/polyureas, epoxies and polyolefins, while crosslinking of approximately 35 different oxide aerogels yields a range of dimensionally stable, porous lightweight materials with unique combinations of structural, magnetic and optical properties. The main theme in materials development for space exploration is multifunction. For example, use of one material for thermal insulation/structural component will free weight for useful payload. In that regard, X-aerogels are evaluated at NASA for cryogenic fuel storage tanks and for spacesuits. Along the same lines, major impact fro X-Aerogels is also expected in commercial applications for thermal/acoustic insulation, in catalytic reformers and converters, in filtration membranes and membranes for fuel cells, as platforms for optical, electrical and magnetic sensors, and as lightweight structural component for aircraft and satellites.

Leventis, Nicholas↗

Advanced monolithic 2D multilayer Laue lens (MLL) optics for hard x-ray nanofocusing and nanotomography

We report on the development of a new generation of monolithic two-dimensional (2D) multilayer Laue lens (MLL) optics suitable for high-resolution hard x-ray nanoimaging. The 2D optics were assembled on microfabricated silicon templates with high orthogonality and lateral alignment precision, which were characterized using white-light interferometry and confirmed by x-ray measurements. The developed monolithic 2D MLL optics were successfully employed for hard x-ray nanofocusing and nanotomography experiments using the ptychography imaging modality, demonstrating sub-10 nm resolution in 2D and sample-limited ∼30 nm in three-dimensional while exhibiting excellent stability during extended measurements. The new 2D MLL templates with high alignment accuracy represent an important step forward in the development of 2D MLL optics toward direct nanoimaging experiments with sub-10 nm spatial resolution.

36 MATERIALS SCIENCE↗

4D-STEM Mapping of Nanocrystal Reaction Dynamics and Heterogeneity in a Graphene Liquid Cell

Chemical reaction kinetics at the nanoscale are intertwined with heterogeneity in structure and composition. However, mapping such heterogeneity in a liquid environment is extremely challenging. Here, in this work, we integrate graphene liquid cell (GLC) transmission electron microscopy and four-dimensional scanning transmission electron microscopy to image the etching dynamics of gold nanorods in the reaction media. Critical to our experiment is the small liquid thickness in a GLC that allows the collection of high-quality electron diffraction patterns at low dose conditions. Machine learning-based data-mining of the diffraction patterns maps the three-dimensional nanocrystal orientation, groups spatial domains of various species in the GLC, and identifies newly generated nanocrystallites during reaction, offering a comprehensive understanding on the reaction mechanism inside a nanoenvironment. This work opens opportunities in probing the interplay of structural properties such as phase and strain with solution-phase reaction dynamics, which is important for applications in catalysis, energy storage, and self-assembly.

four-dimensional scanning transmission electron mi↗

Chemical and architectural intricacy from nanoscale tetrahedra and their analogues

The tetrahedron, as the simplest platonic shape, is a profound building block with the potential to create intricate superstructures. Noteworthy designs utilizing tetrahedral building blocks include the Sierpiński tetrahedron (the most fundamental three-dimensional fractal), a one-dimensional helical structure known as the tetrahelix, and various crystalline and quasicrystalline packings. Historically, the practicality of tetrahedral superstructures has been evident, providing stable, well-defined frameworks for various constructions, including truss bridges, tower cranes, and electricity transmission line pylons. In the field of self-assembled nanocrystal superlattices, tetrahedral nanocrystals, as building blocks, occupy a unique place among all the possible nanoscale particles. Mathematical models, simulation work, and experimental studies using nanocrystals in the laboratory have suggested that self-assembled structures derived from nanoscale tetrahedral building blocks are notably intricate, giving rise to new horizons of high-entropy nanocrystal superlattices. An important implication from previous works is that such tetrahedral nanocrystal superlattices form through highly delicate interparticle interactions, emphasizing the importance of the fine features of these nanocrystals. In this article, we summarize the advances in superlattices assembled from tetrahedral nanocrystals. Here, we first define the tetrahedron and tetrahedron analogues based on Conway’s transformation and graph theory, underscoring their relevance to the crystallization process producing tetrahedral nanocrystals. Then, we showcase previous reports on the synthesis of tetrahedral nanocrystals and the resulting nanocrystal superstructures. Finally, we conclude by offering insights and perspective into the chemical and architectural intricacy that could emerge from tetrahedral nanocrystals.

Nanostructure↗

Carbon-Based Nano-Electro-Mechanical-Systems

We provide an overview of our work where carbon-based nanostructures have been applied to two-dimensional (2D) planar and three-dimensional (3D) vertically-oriented nano-electro-mechanical (NEM) switches. In the first configuration, laterally oriented single-walled nanotubes (SWNTs) synthesized using thermal chemical vapor deposition (CVD) were implemented for forming bridge-type 2D NEMS switches, where switching voltages were on the order of a few volts. In the second configuration, vertically oriented carbon nanofibers (CNFs) synthesized using plasma-enhanced (PE) CVD have been explored for their potential application in 3D NEMS. We have performed nanomechanical measurements on such vertically oriented tubes using nanoindentation to determine the mechanical properties of the CNFs. Electrostatic switching was demonstrated in the CNFs synthesized on refractory metallic nitride substrates, where a nanoprobe was used as the actuating electrode inside a scanning-electron-microscope. The switching voltages were determined to be in the tens of volts range and van der Waals interactions at these length scales appeared significant, suggesting such structures are promising for nonvolatile memory applications. A finite element model was also developed to determine a theoretical pull-in voltage which was compared to experimental results.

Complementary-Metal-Oxide-Semiconductor (CMOS)↗