Search Results (86)

In nanometer integrated-circuit (IC) manufacturing, advanced technology scaling has intensified the effects of process variations on circuit reliability and performance. Random fluctuations in parameters such as threshold voltage, channel length, and oxide thickness further degrade design margins and increase the likelihood of functional failures. These variations often lead to rare circuit failure events, underscoring the importance of accurate yield estimation and robust design methodologies. Conventional Monte Carlo yield estimation is computationally infeasible as millions of simulations are required to capture failure events with extremely low probability. This paper presents a novel reliability-based circuit design optimization framework that leverages deep transfer learning to improve the efficiency of repeated yield analysis in optimization iterations. Based on pre-trained neural network models from prior design knowledge, we utilize model fine-tuning to accelerate importance sampling (IS) for yield estimation. To improve estimation accuracy, adversarial perturbations are introduced to calibrate uncertainty near the model decision boundary. Moreover, we propose a cascaded batch Bayesian optimization (CBBO) framework that incorporates a smart initialization strategy and a localized penalty mechanism, guiding the search process toward high-yield regions while satisfying nominal performance constraints. Experimental validation on SRAM circuits and amplifiers reveals that CBBO achieves a computational speedup of 2.02×–4.63× over state-of-the-art (SOTA) methods, without compromising accuracy and robustness. Full article

With the increasing application of oxide films in nuclear fuel assemblies, the accurate measurement of thin-film thickness has become increasingly critical. Traditional spectral interferometry techniques have limitations when dealing with new materials and complex structures; therefore, this study proposes a multi-channel wide-spectrum high-resolution analysis technique. This technique optimizes the utilization of photosensitive elements through multi-channel spectral sampling, combined with precision spectroscopic components and an independent optical focusing and imaging system. Simultaneously, it adopts optical correction technologies such as coma optimization and astigmatism correction to improve imaging quality and spectral resolution. Additionally, it enhances data accuracy by means of multi-channel calibration based on the least squares method and non-linear correction. The technique enables high-precision measurement ranging from the nanometer to the millimeter scale, resulting in a significantly wider measurement range compared to traditional spectrometers. Simulation verification shows that this technique outperforms existing technologies in information acquisition, analysis accuracy, and detection efficiency, and has broad application prospects in fields such as semiconductor chip manufacturing and optical coating. In the future, focus will be placed on expanding the spectral range, improving resolution, and enhancing real-time measurement capabilities. Full article

Wide-Bandgap (WBG) semiconductors—silicon carbide (SiC) and gallium nitride (GaN)— enable high-power-density conversion, but performance is limited by where heat is generated and how it is removed. This review links device-level loss mechanisms (conduction and switching, including output-capacitance hysteresis and dynamic on-resistance) to structure-driven hot spots within the ultra-thin (tens of nanometers) two-dimensional electron gas (2DEG) channel of GaN HEMTs and to thermal boundary resistance at layer interfaces. We compare wire-bondless package concepts—double-sided cooling, embedded packaging, and interleaved planar layouts—and survey system-level cooling that shortens the conduction path and raises heat-transfer coefficients. The impact on reliability is discussed using temperature-sensitive electrical parameters (e.g., on-state VDS, threshold voltage, drain leakage, di/dt, and gate current) for real-time junction-temperature estimation and compact electro-thermal RC models for remaining-useful-life prediction. Evidence from recent literature points to interface resistance in GaN-on-SiC as a primary bottleneck, while near-junction cooling and advanced packages are effective mitigations. We argue for integrated co-design—devices, packaging, electromagnetic interference (EMI)-aware layout, and cooling—together with interface engineering and health monitoring to deliver reliable, high-density WBG systems. Full article

Ultrathin oxide semiconductors are promising channel materials for next-generation thin-film transistors (TFTs), but their performance is severely limited by bulk and interface defects as the channel thickness approaches a few nanometers. In this study, we show that high-pressure hydrogen annealing (HPHA) effectively mitigates these limitations in 3.6 nm thick ZnO TFTs. HPHA-treated devices exhibit a nearly four-fold increase in on-current, a steeper subthreshold swing, and a negative shift in threshold voltage compared to reference groups. X-ray photoelectron spectroscopy reveals a marked reduction in oxygen vacancies and hydroxyl groups, while capacitance–voltage measurements confirm more than a three-fold decrease in interface trap density. Low-frequency noise analysis further demonstrates noise suppression and a transition in the dominant noise mechanism from carrier number fluctuation to mobility fluctuation. These results establish HPHA as a robust strategy for defect passivation in ultrathin oxide semiconductor channels and provide critical insights for their integration into future low-power, high-density electronic systems. Full article

Aqueous batteries, which replace flammable organic electrolytes with water, offer advantages such as intrinsic safety, low cost, and environmental friendliness, making them well-suited to the energy storage needs driven by the increasing proliferation of renewable energy. However, their widespread adoption is hampered by the narrow electrochemical stability window of water, dendrite growth on metal anodes, and various parasitic interfacial reactions. This review proposes a unified three-part framework for biomimetic electrolytes—SEI-mimetic, antifreeze-protein-mimetic, and ion-channel-mimetic—corresponding to three mechanistic strands—water activity regulation, interfacial mechanics, and sub-nanometer transport—to organize and compare various strategies. This paper systematically reviews and evaluates the latest advances in biomimetic electrolytes. It discusses these three biomimetic concepts and their applications in different battery chemistries (monovalent and multivalent metal systems, as well as aqueous redox-flow batteries). It also proposes a roadmap and engineering thresholds for both basic research and commercialization. Full article

To enable multi-channel parallel spectral analysis in array-based devices such as micro-light-emitting diodes (Micro-LEDs) and line-scan spectral confocal systems, the development of compact array spectrometers has become increasingly important. In this work, a novel spectrometer architecture based on a microlens array grating (MLAG) is proposed, which addresses the major limitations of conventional spectrometers, including limited parallel detection capability, bulky structures, and insufficient spatial resolution. By integrating dispersion and focusing within a monolithic device, the system enables simultaneous acquisition across more than 2000 parallel channels within a 10 mm × 10 mm unit consisting of an f = 4 mm microlens and a 600 lines/mm blazed grating. Optimized microlens and aperture alignment allows for flexible control of the divergence angle of the incident light, and the system theoretically achieves nanometer-scale spectral resolution across a 380–780 nm wavelength range, with inter-channel measurement deviation below 1.25%. Experimental results demonstrate that this spectrometer system can theoretically support up to 2070 independently addressable subunits. At a wavelength of 638 nm, the coefficient of variation (CV) of spot spacing among array elements is as low as 1.11%, indicating high uniformity. The spectral repeatability precision is better than 1.0 nm, and after image enhancement, the standard deviation of the diffracted light shift is reduced to just 0.26 nm. The practical spectral resolution achieved is as fine as 3.0 nm. This platform supports wafer-level spectral screening of high-density Micro-LEDs, offering a practical hardware solution for high-precision industrial inline sorting, such as Micro-LED defect inspection. Full article

Since the initial use of biological ion channels to detect single-stranded genomic base pair differences, label-free and highly sensitive resistive pulse sensing (RPS) with nanopores has made remarkable progress in single-molecule analysis. By monitoring transient ionic current disruptions caused by molecules translocating through a nanopore, this technology offers detailed insights into the structure, charge, and dynamics of the analytes. In this work, the RPS platforms based on biological, solid-state, and other sensing pores, detailing their latest research progress and applications, are reviewed. Their core capability is the high-precision characterization of tiny particles, ions, and nucleotides, which are widely used in biomedicine, clinical diagnosis, and environmental monitoring. However, current RPS methods involve bottlenecks, including limited sensitivity (weak signals from sub-nanometer targets with low SNR), complex sample interference (high false positives from ionic strength, etc.), and field consistency (solid-state channel drift, short-lived bio-pores failing POCT needs). To overcome this, bio-solid-state fusion channels, in-well reactors, deep learning models, and transfer learning provide various options. Evolving into an intelligent sensing ecosystem, RPS is expected to become a universal platform linking basic research, precision medicine, and on-site rapid detection. Full article

Porous materials are characterized by the pore surface area (S) and volume (V) accessible to a confined fluid. For mesoporous materials NMR measurements of diffusion are used to assess the S/V ratio, because at short times, only the diffusivity of molecules in the adsorbed layer is affected by confinement and the fractional population of these molecules is proportional to the S/V ratio. For materials with sub-nanometer pores, this might not be true, as the adsorbed layer can encompass the entire pore volume. Here, using molecular simulations, we explore the role played by S and S/V in determining the dynamical behavior of two carbon-bearing fluids—CO₂ and ethane—confined in sub-nanometer pores of silica. S and V in a silicalite model representing a sub-nanometer porous material are varied by selectively blocking a part of the pore network by immobile methane molecules. Three classes of adsorbents were thus obtained with either all of the straight (labeled ‘S-major’) or zigzag channels (‘Z-major’) remaining open or a mix of a fraction of both types of channel blocked, resulting in half of the total pore volume being blocked (‘Half’). While the adsorption layers from opposite surfaces overlap, encompassing the entire pore volume for all pores except the intersections, the diffusion coefficient is still found to be reduced at high S/V, especially for CO₂, albeit not so strongly as would be expected in the case of wider pores. This is because of the presence of channel intersections that provide a wider pore space with non-overlapping adsorption layers. Full article

Suspended solids (SS) composed of micrometer-to-nanometer-scale particles, including silt and organic matter, significantly impact aquatic ecosystems through physicochemical interactions. Accurate monitoring of SS concentration and particle size is critical for environmental protection and pollution prevention. We constructed multiple datasets using received signals after propagation through different aqueous environments. Analysis of the performance of neural networks across different datasets revealed that high-frequency signals with rich spectra have high potential for detecting suspended solid information in complex aqueous environments. Our study explores the performance of two neural networks (Conv1dBGRU and TCN) in combination with channel attention mechanisms in classification tasks focused on the concentration of suspended solids and particle size. We also constructed neural networks for multi-task learning using both hard and soft parameter-sharing methods to simultaneously complete the classification tasks for concentration and particle size. The results show that multi-frequency acoustic signals in combination with neural networks can achieve simultaneous and accurate estimation of the concentration of suspended solids and particle size. Full article

Nanotopography refers to the intricate surface characteristics of materials at the sub-micron (<1000 nm) and nanometer (<100 nm) scales. These topographical surface features significantly influence the physical, chemical, and biological properties of biomaterials, affecting their interactions with cells and surrounding tissues. The development of nanostructured surfaces of polymeric nanocomposites has garnered increasing attention in the fields of tissue engineering and regenerative medicine due to their ability to modulate cellular responses and enhance tissue regeneration. Various top-down and bottom-up techniques, including nanolithography, etching, deposition, laser ablation, template-assisted synthesis, and nanografting techniques, are employed to create structured surfaces on biomaterials. Additionally, nanotopographies can be fabricated using polymeric nanocomposites, with or without the integration of organic and inorganic nanomaterials, through advanced methods such as using electrospinning, layer-by-layer (LbL) assembly, sol–gel processing, in situ polymerization, 3D printing, template-assisted methods, and spin coating. The surface topography of polymeric nanocomposite scaffolds can be tailored through the incorporation of organic nanomaterials (e.g., chitosan, dextran, alginate, collagen, polydopamine, cellulose, polypyrrole) and inorganic nanomaterials (e.g., silver, gold, titania, silica, zirconia, iron oxide). The choice of fabrication technique depends on the desired surface features, material properties, and specific biomedical applications. Nanotopographical modifications on biomaterials’ surface play a crucial role in regulating cell behavior, including adhesion, proliferation, differentiation, and migration, which are critical for tissue engineering and repair. For effective tissue regeneration, it is imperative that scaffolds closely mimic the native extracellular matrix (ECM), providing a mechanical framework and topographical cues that replicate matrix elasticity and nanoscale surface features. This ECM biomimicry is vital for responding to biochemical signaling cues, orchestrating cellular functions, metabolic processes, and subsequent tissue organization. The integration of nanotopography within scaffold matrices has emerged as a pivotal regulator in the development of next-generation biomaterials designed to regulate cellular responses for enhanced tissue repair and organization. Additionally, these scaffolds with specific surface topographies, such as grooves (linear channels that guide cell alignment), pillars (protrusions), holes/pits/dots (depressions), fibrous structures (mimicking ECM fibers), and tubular arrays (array of tubular structures), are crucial for regulating cell behavior and promoting tissue repair. This review presents recent advances in the fabrication methodologies used to engineer nanotopographical microenvironments in polymeric nanocomposite tissue scaffolds through the incorporation of nanomaterials and biomolecular functionalization. Furthermore, it discusses how these modifications influence cellular interactions and tissue regeneration. Finally, the review highlights the challenges and future perspectives in nanomaterial-mediated fabrication of nanotopographical polymeric scaffolds for tissue engineering and regenerative medicine. Full article

As silicon-based complementary metal-oxide-semiconductor (CMOS) technology approaches its physical and scaling limits at sub-3-nanometer nodes, critical challenges including the short-channel effect (SCE), surging power consumption, and aggravated parasitic effects have severely constrained further improvements in device performance, integration density, and energy efficiency. Carbon nanotubes (CNTs), with their superior electrical properties, exceptional gate controllability enabled by one-dimensional nanostructure, and compatibility with existing semiconductor processes, have emerged as an ideal candidate material for post-silicon high-performance electronics. Since their discovery, CNT electronics have evolved from fundamental research to a comprehensive technological framework. This review first systematically elaborates the physical characteristics of CNTs and operation mechanisms of electronic devices. Subsequently, we comprehensively summarize recent research progress in high-performance CNT electronic devices with particular emphasis on their breakthrough achievements. Through critical analysis of current developments, we thoroughly discuss fundamental challenges in material synthesis, device fabrication, and circuit integration, while evaluating potential solutions. Finally, we concentrate on future development directions for high-performance CNT devices, aiming to call for collaborative efforts from both academia and industry to accelerate the transition of CNT electronics from laboratory research to industrial implementation. Full article

Understanding microscale dynamic behavior in heterogeneous materials (e.g., polycrystalline or semiconductor systems) under impact loading requires diagnostics capable of resolving ~100 μm features. This study introduces a 19-core fiber-optic array probe with 100 μm spatial resolution, integrated with DISAR velocimetry on a light gas gun platform, enabling two-dimensional continuous measurement of free-surface velocity. The system overcomes limitations of conventional single-point methods (e.g., VISAR’s millimeter-scale resolution and reflectivity constraints) by achieving nanosecond temporal resolution and sub-nanometer displacement sensitivity. Under ~8 GPa impact loading, the probe captures spatiotemporal velocity heterogeneity in polycrystalline materials, including localized pull-back signals and periodic oscillations caused by shock wave reflections at microstructural interfaces. These observations reveal dynamic processes such as damage initiation and evolution, directly linking velocity profiles to microscale material response. The results provide experimental evidence of how grain-scale defects influence shock propagation and energy dissipation, advancing predictive models for extreme-condition material performance. This high-resolution, multi-channel approach offers a paradigm shift in diagnosing heterogeneous material behavior under high-strain-rate loading. Full article

Fiber-optic Fabry–Pérot (F–P) sensors offer significant potential for non-invasive hemodynamic monitoring, but existing sensing systems face limitations in multi-channel measurement capabilities and dynamic demodulation accuracy. This study introduces a sparse-frequency-scanning white-light interferometry (SFS-WLI) system with an adaptive mode-locked cross-correlation (MLCC) algorithm to address these challenges. The system leverages telecom-grade semiconductor lasers (191.2–196.15 THz sweep range, 50 GHz step) and a Fibonacci-optimized MLCC algorithm to achieve real-time cavity length demodulation at 5 kHz. Compared to normal MLCC algorithm, the Fibonacci-optimized algorithm reduces the number of computational iterations by 57 times while maintaining sub-nanometer resolution under dynamic perturbations. Experimental validation demonstrated a carotid–radial pulse wave velocity of 5.12 m/s in a healthy male volunteer. This work provides a scalable and cost-effective solution for cardiovascular monitoring with potential applications in point-of-care testing (POCT) and telemedicine. Full article

The disadvantage of phase change materials (PCMs) that store thermal energy is their low thermal conductivity. The macro-, micro-, and nanoencapsulation of PCMs are some of the ways to eliminate this drawback. Liquids with micro- and nanometer-sized capsules containing PCMs have become innovative working fluids for heat transfer—a slurry of encapsulated PCMs. This paper shows the results of in-depth studies on the nature of fluid movement (slurry of microencapsulated PCMs) in pipe channels. The slurry flowed inside a tube with a diameter of 4 mm in the range of Re = 350–11,000. The PCM microcapsule (mPCM) concentration ranged from 4.30% to 17.2%. A pressure loss measurement was carried out on a section of 400 mm. The temperature of the flowing slurry was selected so that the PCMs in the microcapsules were in a liquid state and were solid during subsequent measurement series after undergoing a phase transformation. It was found that the boundary of the transition from laminar to turbulent flow is influenced by both the mPCM concentration in the slurry and the state of matter of the PCMs in the microcapsules. The influence of the slurry concentration and the state of matter of the PCMs in the microcapsules on changes such as fluid movement is presented (in terms of the critical Reynolds number). Full article

With the improvement of integration levels to several nanometers or less, semiconductor leakage current has become an important issue, and oxide-based semiconductors, which have replaced Si-based channel layer semiconductors, have attracted attention. Herein, we fabricated capacitors with a metal–insulator–semiconductor–metal structure using HfO₂ thin films deposited at 240 °C and TiO₂ thin films deposited at 300 °C via remote plasma (RP) and direct plasma (DP) atomic layer deposition and analyzed the effects of the charge-trapping and semiconducting properties of these films. Charge-trapping memory (CTM) devices with HfO₂ (charge-trapping layer) and TiO₂ (semiconductor) films were fabricated and characterized in terms of their memory properties. Al₂O₃ thin films were used as blocking and tunneling layers to prevent the leakage of charges stored in the charge-trapping layer. For the TiO₂ layer, the heat-treatment temperature was optimized to obtain an anatase phase with optimal semiconductor properties. The memory characteristics of the RP HfO₂–TiO₂ CTM devices were superior to those of the DP HfO₂–TiO₂ CTM devices. This result was ascribed to the decrease in the extent of damage and contamination observed when the plasma was spaced apart from the deposited HfO₂ and TiO₂ layers (i.e., in the case of RP deposition) and the reduction in the concentration of oxygen vacancies at the interface and in the films. Full article