Metrology Tool Research Articles

Fitting the AFM force-distance curves the correct way

Abstract Data fitting is an indispensable tool in modern metrology. However, the
most popular method, least squares, reaches its limit at the naonoscale. As the relative uncertainty in the dependent variable increases, the concept of an exactly known independent variable and an uncertain dependent variable, which is at the core of least squares, looses its validity. The increasing complexity of the measurement process may give rise to correlations. The use of reference samples leads to correlations among the dependent or independent variables, crosstalk between sensors may lead to correlation between independent and dependent variables. These problems can be treated with generalized least squares but only few implementations are available, none of which are suitable for general functions and general covariance matrices. A new algorithm - Optimal Estimation of Function Parameters by Iterated Linearization (OEFPIL) – has been recently suggested which can handle both a wide class of functions as well as general covariance matrices. In this work the OEFPIL algorithm is applied to the analysis of force distance curves in atomic force microscopy (AFM). Force distance curves are used to evaluate the mechanical properties of samples such as the Young’s modulus and adhesion. In this work we apply the new algorithm and compare the results to other methods. The uncertainties obtained by OEFPIL are in good agreement with uncertainties obtained by the Monte Carlo method.

Differential Hall Effect Metrology for Electrical Characterization of Advanced Semiconductor Layers

Semiconductor layers employed in fabricating advanced node devices are becoming thinner and their electrical properties are diverging from those established for highly crystalline standards. Since these properties also change as a function of depth within the film, accurate carrier profiling solutions are required. The Differential Hall Effect (DHE) technique has the unique capability of measuring mobility and carrier concentration (active carriers) through the depth of a semiconductor film. It comprises making successive sheet resistance and sheet Hall coefficient measurements as the thickness of the electrically active layer at a test region is reduced through successive material removal steps. Difference equations are then used to process the data and plot the desired depth profiles. The fundamentals of DHE were established in 1960s. Recently, the adaption of electrochemical processing for the material removal steps, and the integration of all other functionalities in a Differential Hall Effect Metrology (DHEM) tool, has made this technique more practical and accurate and improved its depth resolution to a sub-nm range. In this contribution, we review the development history of this important technique and present data from recent characterization work carried out on Si, Ge and SiGe layers.

Data-driven roughness estimation of additively manufactured samples using build angles

Achieving control of Laser Powder Bed Fusion (L-PBF) over the quality of the print is the main motivation for finding an optimum set of parameters in the process. Surface roughness is one of the characteristics of the print that impacts the performance of the desired functionality. This research focus is to relate the build angle with the surface roughness on the L-PBF printed specimens and utilize machine learning methods for roughness estimation of geometric features with varying build angles. The EOS M290 L-PBF printer was used to print Inconel-718 coupons using standard process parameters while varying build angles from 20 to 90 degrees at fixed 5-degree intervals. The specimens’ surface was analyzed using metrology tools and the data obtained was used for training the machine learning models. Machine learning methods are used to create regression models for estimating the roughness of the specimens using the build angle and location of the sample on the substrate. The findings of this study provide build angle-based predictive estimation of surface roughness of printed L-PBF parts. The machine learning model will help to make reliable decisions on choosing the build angle of a complex part based on the desired surface roughness of its geometric features.

Slowing Down a Coherent Superposition of Circular Rydberg States of Strontium.

Rydberg alkaline earth atoms are promising tools for quantum simulation and metrology. When one of the two valence electrons is promoted to long-lived circular states, the second valence electron can be optically manipulated without significant autoionization. We harness this feature to demonstrate laser slowing of a thermal atomic beam of circular strontium atoms. By driving the main ion core 422nm wavelength resonance, we observe a velocity reduction of 50 m/s without significant autoionization. We also show that a superposition of circular states undergoes very weak decoherence during the cooling process, up to the scattering of more than 1000 photons. This robustness opens new perspectives for quantum simulations over long timescales with circular atoms, while simultaneously cooling their motional state. It makes it possible to mitigate the harmful effects of unavoidable heating due to spin-motion coupling during a quantum simulation.

Study of the eddy currents effect in Spinning rotor Gauge

The Spinning Rotor Gauge (SRG) serves as a crucial tool in metrology as a secondary standard vacuum gauge. However, its lower measurement limit is not solely determined by background gas molecular friction damping but is also affected by other contributing factors, collectively termed residual damping. This paper investigates the influence of eddy currents on residual damping. It quantitatively analyzes the electromagnetic torque and eddy current heating power induced within the rotor’s interior and surface, calculates the corresponding kinetic energy loss, and simulates the rotor’s attenuation. The simulation predicts an attenuation of 0.23 Hz within a 12-hour period, corresponding to an average background pressure of 7 × 10-5 Pa. A comparison with observed residual damping data, showing an attenuation of 1.17 Hz and a background pressure of 1.6308 × 10-4 Pa, demonstrates high consistency. This affirms the reliability of the numerical model and calculation results regarding eddy current-induced residual damping presented in this article.

Wavelength-multiplexed multi-mode EUV reflection ptychography based on automatic differentiation

Ptychographic extreme ultraviolet (EUV) diffractive imaging has emerged as a promising candidate for the next generationmetrology solutions in the semiconductor industry, as it can image wafer samples in reflection geometry at the nanoscale. This technique has surged attention recently, owing to the significant progress in high-harmonic generation (HHG) EUV sources and advancements in both hardware and software for computation. In this study, a novel algorithm is introduced and tested, which enables wavelength-multiplexed reconstruction that enhances the measurement throughput and introduces data diversity, allowing the accurate characterisation of sample structures. To tackle the inherent instabilities of the HHG source, a modal approach was adopted, which represents the cross-density function of the illumination by a series of mutually incoherent and independent spatial modes. The proposed algorithm was implemented on a mainstream machine learning platform, which leverages automatic differentiation to manage the drastic growth in model complexity and expedites the computation using GPU acceleration. By optimising over 200 million parameters, we demonstrate the algorithm's capacity to accommodate experimental uncertainties and achieve a resolution approaching the diffraction limit in reflection geometry. The reconstruction of wafer samples with 20-nm high patterned gold structures on a silicon substrate highlights our ability to handle complex physical interrelations involving a multitude of parameters. These results establish ptychography as an efficient and accurate metrology tool.

Self-Calibrating Fluorimetric Analysis of Single-Wall Carbon Nanotube Samples for Electronics Applications

Semiconducting single-wall carbon nanotubes (SWCNTs) are a leading candidate to replace or supplement silicon in future generation chip manufacturing. Because they are produced as structural mixtures with varied electronic properties, SWCNTs must first be carefully sorted and purified. This requires new metrology tools that can reliably measure SWCNT sample compositions to guide sorting processes and confirm product purity. We describe here a novel, self-calibrating optical instrument designed for advanced characterization of SWCNT samples. This desktop system will quickly, sensitively, and non-destructively quantify the concentrations of multiple SWCNT (n,m) species. The key advance is adding variance spectroscopy to rapid excitation-emission fluorimetry. Variance spectroscopy is a recently developed method that can determine absolute concentrations of nanoparticles by analyzing statistical variations in the fluorescence signals from small volumes of dilute samples. Measurements are made by a small accessory module linked to a standard NanoSpectralyzer. It will automatically acquire and analyze variance spectra to find the sensitivity calibration factors needed to convert raw fluorescence intensities into actual concentrations of the different SWCNT species. Those measured calibration factors are valid for subsequent samples with similar processing histories, allowing rapid quantitation from quick excitation-emission scans. We expect that this analytical capability will support advances in basic carbon nanotube science and applications.

중국 현대 주방 디자인 연구 동향 시각화 분석

Kitchen has experienced thousands of years of development and change, is the witness and epitome of social and economic metamorphosis and cultural development. 21st century, China's modern kitchen design has undergone a great transformation, in order to clarify the current situation and development trend of kitchen design research in China over the past 20 years, the literature of three Chinese databases was used as the data source, and Cite Space V metrological visual analysis tool was used to map the scientific knowledge of 906 key literature. The scientific knowledge map was drawn. We analysed the publication volume, research institutions, research authors and keywords of the literature from 2000 to 2023, and sorted out the research profiles and trends. Research content from the cabinet design and cabinet design to the study of the behaviour of workers, the object of research from a wide range of people to focus on specific groups of special groups, from the surface layer of sensory design optimization to the essence of the layer of space within the depth of the ethical, the future development trend of the kitchen to become the focus of the direction of the study will be to the space scenarios, science and technology-enabled design, the use of the population segments and other perspectives will continue to be explored in-depth.

Robust inverse parameter fitting of thermal properties from the laser-based Ångstrom method in the presence of measurement noise using physics-informed neural networks (PINNs)

The two-dimensional laser-based Ångstrom method measures the in-plane thermal properties for anisotropic film-like materials. It involves periodic laser heating at the center of a suspended film sample and records its transient thermal response by infrared imaging. These spatiotemporal temperature data must be analyzed to extract the unknown thermal conductivity values in the orthotropic directions, an inverse parameter fitting problem. Previous demonstration of the metrology technique used a least-squares fitting method that relies on numerical differentiation to evaluate the second-order partial derivatives in the differential equation describing transient conduction in the physical system. This fitting approach is susceptible to measurement noise, introducing high uncertainty in the extracted properties when working with noisy data. For example, when noise of a signal-to-noise ratio of 10 is added to simulated amplitude and phase data, the error in the extracted thermal conductivity can exceed 80%. In this work, we introduce a new alternative inverse parameter fitting approach using physics-informed neural networks (PINNs) to increase the robustness of the measurement technique for noisy temperature data. We demonstrate the effectiveness of this approach even for scenarios with extreme levels of noise in the data. Specifically, the PINN-approach accurately extracts the properties to within 5% of the true values even for high noise levels (a signal-to-noise ratio of 1). This offers a promising avenue for improving the robustness and accuracy of advanced thermal metrology tools that rely on inverse parameter fitting of temperature data to extract thermal properties.

Monolithic optical resonator for ultrastable laser and photonic millimeter-wave synthesis

Optical resonators are indispensable tools in optical metrology that usually benefit from an evacuated and highly-isolated environment to achieve peak performance. Even in the more sophisticated design of Fabry-Perot (FP) cavities, the material choice limits the achievable quality factors. For this reason, monolithic resonators are emerging as promising alternative to traditional designs, but their design is still at preliminary stage and far from being optimized. Here, we demonstrate a monolithic FP resonator with 4.5 cm3 volume and 2 × 105 finesse. In the ambient environment, we achieve 18 Hz integrated laser linewidth and 7 × 10−14 frequency stability measured from 0.08 s to 0.3 s averaging time, the highest spectral purity and stability demonstrated to date in the context of monolithic reference resonators. By locking two separate lasers to distinct modes of the same resonator, a 96 GHz microwave signals is generated with phase noise -100 dBc/Hz at 10 kHz frequency offset, achieving orders of magnitude improvement in the approach of photonic heterodyne synthesis. The compact monolithic FP resonator is promising for applications in spectrally-pure, high-frequency microwave photonic references as well as optical clocks and other metrological devices. ©2024. All rights reserved.

Multi-beam coherent Fourier scatterometry

Inspection of surface and nanostructure imperfections play an important role in high-throughput manufacturing across various industries. This paper introduces a novel, parallelised version of the metrology and inspection technique: Coherent Fourier scatterometry (CFS). The proposed strategy employs parallelisation with multiple probes, facilitated by a diffraction grating generating multiple optical beams and detection using an array of split detectors. The article details the optical setup, design considerations, and presents results, including independent detection verification, calibration curves for different beams, and a data stitching process for composite scans. The study concludes with discussions on the system’s limitations and potential avenues for future development, emphasizing the significance of enhancing scanning speed for the widespread adoption of CFS as a commercial metrology tool.

Determination of sulfonamides in muscle: a metrological tool for food safety

Sulfonamides represent a wide class of synthetic drugs commonly used in veterinary therapy for the treatment of several bacterial and protozoan infections in cattle, swine and poultry. The use of these drugs in farming can lead to the possibility of having their residues in animal products intended for human consumption. Consequently, to ensure high consumer protection, for sulfonamides European Union (EU) set a Maximum Residue Limit (MRL) equal to 100 µg/kg, either as a single molecule or as a sum of all detected compounds within the class). Official laboratories are directly involved in the execution or residue plans by developing, validating and then applying analytical methods for the measurement of drug residues. Accordingly, official laboratories should update their procedures following the evolution of required drugs and MRLs. A multiclass method previously developed and validated for the determination in animal muscle of ten classes of antibiotics was adjusted to comply with the current European requirements which establish the minimum set of sulfonamides to be determined. Therefore, eight new sulfonamides were added assessing method performance characteristics according to European Regulation (EU) 808/2021.

A study of Citespace-based deep learning applied to face recognition

Face recognition technology has made significant progress in recent years, driven by deep learning and other technologies, and is widely used in public safety, financial payment, intelligent access control, and other fields. Deep learning can effectively extract discriminative features from face images by constructing neural network structures and automatically learning feature mapping relationships, to improve the recognition accuracy. Deep learning shows excellent robustness when dealing with complex scenarios, and scientific metrology and visual analysis tools such as Citespace play an important role in analyzing the current status and development trend of applied research in the field of face recognition. Deep learning methods such as data enhancement techniques and generative adversarial networks have shown strong performance in face recognition tasks. In the future, the further integration and development of deep learning and face recognition technology will promote technological innovation and application expansion. Face recognition technology has important application potential in the digital society and will have wider application prospects in the future.

Self-injection-locked optical parametric oscillator based on microcombs

Narrow-linewidth yet tunable laser oscillators are one of the most important tools for precision metrology, optical atomic clocks, sensing, and quantum computing. Commonly used tunable coherent oscillators are based on stimulated emission or stimulated Brillouin scattering; as a result, the operating wavelength band is limited by the gain media. Based on nonlinear optical gain, optical parametric oscillators (OPOs) enable coherent signal generation within the whole transparency window of the medium used. However, the demonstration of OPO-based Hertz-level linewidth and tunable oscillators has remained elusive. Here, we present a tunable coherent oscillator based on a multimode coherent OPO in a high-Q microresonator, i.e., a microcomb. Single-mode coherent oscillation is realized through self-injection locking (SIL) of one selected comb line. We achieve coarse tuning up to 20 nm and an intrinsic linewidth down to sub-Hertz level, which is three orders of magnitude lower than the pump. Furthermore, we demonstrate that this scheme results in the repetition rate stabilization of the microcomb. These results open exciting possibilities for generating tunable coherent radiation where stimulated emission materials are difficult to obtain, and the stabilization of microcomb sources beyond the limits imposed by the thermorefractive noise in the cavity.

Integrated frequency-modulated optical parametric oscillator.

Optical frequency combs have revolutionized precision measurement, time-keeping and molecular spectroscopy1-7. A substantial effort has developed around 'microcombs': integrating comb-generating technologies into compact photonic platforms5,7-9. Current approaches for generating these microcombs involve either the electro-optic10 or Kerr mechanisms11. Despite rapid progress, maintaining high efficiency and wide bandwidth remains challenging. Here we introduce a previously unknown class of microcomb-an integrated device that combines electro-optics and parametric amplification to yield a frequency-modulated optical parametric oscillator (FM-OPO). In contrast to the other solutions, it does not form pulses but maintains operational simplicity and highly efficient pump power use with an output resembling a frequency-modulated laser12. We outline the working principles of our device and demonstrate it by fabricating the complete optical system in thin-film lithium niobate. We measure pump-to-comb internal conversion efficiency exceeding 93% (34% out-coupled) over a nearly flat-top spectral distribution spanning about 200 modes (over 1 THz). Compared with an electro-optic comb, the cavity dispersion rather than loss determines the FM-OPO bandwidth, enabling broadband combs with a smaller radio-frequency modulation power. The FM-OPO microcomb offers robust operational dynamics, high efficiency and broad bandwidth, promising compact precision tools for metrology, spectroscopy, telecommunications, sensing and computing.

Study of Spatial Distortion in InP Nanophotonic Membranes on Different Carrier Substrates

Electron Beam Lithography (EBL) metrology and least-square estimation of wafer-scale distortions is used to determine InP membrane deformation as a result of bonding to different substrate materials. First, the accuracy of EBL as a metrology tool for this particular application was assessed. Next, modelling of distortions was tested on unbonded InP wafers as a reference for extracting post-bonding distortions. Then we investigated the effect of substrate material choice on InP membrane deformation after bonding. We found residual expansion factors of 4.53±1, 312.4±1, and 317±1 ppm of the InP membrane bonded to InP, Si, and 3C-SiC carriers, respectively. For the SiO2 carrier, the 3inch InP membrane split into smaller membranes to reduce the stress, highlighting the importance of substrate choice.

Micro Management

After a slow start, MicroLED displays are finding their way into more consumer tech. But testing the quality of this emerging technology requires ever more powerful metrology tools, says Radiant Vision Systems.

Addressing Die Displacement in Lithography Processes for Advanced Packaging Applications

To perpetuate Moore’s Law, semiconductor manufacturers are adopting advanced packaging technology as the mainstream solution. As a result, today, fan-out wafer level packaging is a key enabler of two- and three-dimensional packaging solutions. Among the manufacturing challenges, die displacement in lithography processes has been widely discussed, but a total solution is yet to come. In this study, we demonstrate die-by-die and global wafer alignment strategies available on-board the Kulicke & Soffa LITEQ 500 projection stepper. The versatility of a die-by-die alignment strategy allows for working with reconstituted wafers without resorting to an external metrology tool. The die displacement residuals can be reduced by three orders of magnitude, typically, from 100um to 100nm. The evaluation of overlay accuracy by implementing a die-by-die and global wafer alignment strategy indicates comparable performances. Considering high volume manufacturing, advanced process control of overlay is also capable of applying to a batch of wafers.

Recent Advances, Applications, and Perspectives in Erbium-Doped Fiber Combs

Optical frequency combs have emerged as a new generation of metrological tools, driving advancements in various fields such as free-space two-way time–frequency transfer, low-noise microwave source generation, and gas molecule detection. Among them, fiber combs based on erbium-doped fiber mode-locked lasers have garnered significant attention due to their numerous advantages, including low noise, high system integration, and cost-effectiveness. In this review, we discuss recent developments in erbium-doped fiber combs and analyze the advantages and disadvantages of constructing fiber combs utilizing different erbium-doped mode-locked fiber lasers. First, we provide a brief introduction to the basic principles of optical frequency combs. Then, we explore erbium-doped fiber combs implemented utilizing various mode-locking techniques, such as nonlinear polarization rotation (NPR), real saturable absorber (SA), and nonlinear amplifying loop mirror (NALM). Finally, we present an outlook on the future perspectives of erbium-doped fiber combs.

High-Speed Near-Surface Tracking for Fast Atomic Force Microscope Scan Switching Based on the Squeeze Film Damping Effect

Atomic force microscope (AFM) is a crucial metrology tool in the semiconductor industry. However, the bottleneck of the AFM technique is its low efficiency, primarily owing to the time-consuming scanning point switching. The traditional method takes approximately one minute for a single switching. To shield the probe and sample, the switching should first lift the probe a considerable distance, move it to the next point, and finally engage the probe slowly to the sample surface. We propose a near-surface tracking method for use in fast scanning point switching. The probe-sample distance was sensed by the squeeze air film damping effect, and the probe was kept at a small constant height during the switching via feedback control. The method can decrease the lift and engage distance from approximately 1 mm to 5 μm, which was two order of reduction; thereby shortening the single switching time from 45 s to 6.1 s, which is an 87% reduction. Generally, the fast switching method can improve the measurement efficiency of the existing AFM working in the air, but it can not be used in liquid and vacuum. Furthermore, the proposed squeeze film damping effect based distance sensing method can be applied in various fields, such as vibration sensing and temperature drift measurement.