A novel mid-infrared critical dimension (IRCD) metrology has been developed on a platform suitable for fab production. Compared to traditional optical critical dimension (OCD) technology based on ultraviolet, visible, and near-IR light, the IRCD system exploits unique optical properties of common semiconductor fab materials in the mid-infrared to enable accurate measurements of high-aspect-ratio etched features. In this paper, we will show two examples of critical dry etch steps in 3D NAND channel formation module of an advanced node that require nondestructive process control: (1) channel hole active area etch and (2) amorphous carbon hardmask etch. In the first example, we take advantage of the absorption bands of silicon dioxide and silicon nitride to get accurate CD measurements at different depths, resulting in high-fidelity z-profile metrology of the channel – key to guiding process development and accelerated learning for 3D NAND device manufacturing. In the second example, the most common amorphous carbon hardmask materials for advanced 3D NAND nodes are opaque in the traditional OCD wavelength range; however, in the mid-infrared, there is light penetration and hence spectral sensitivity to dimensional parameters including sub-surface features. We show successful detection of intentional process skews and as well accurate bottom CD measurements of the hardmask.
With the aggressive scaling of semiconductor devices, the increasing complexity of device structure coupled with tighter metrology error budget has driven up Optical Critical Dimension (OCD) time to solution to a critical point. Machine Learning (ML), thanks to its extremely fast turnaround, has been successfully applied in OCD metrology as an alternative solution to the conventional physical modeling. However, expensive and limited reference data or labeled data set necessary for ML to learn from often leads to under- or overlearning, limiting its wide adoption. In this paper, we explore techniques that utilize process information to supplement reference data and synergizing physical modeling with ML to prevent under- or overlearning. These techniques have been demonstrated to help overcome the constraint of limited reference data with use cases in challenging OCD metrology for advanced semiconductor nodes.
We have developed a novel in-line solution for the characterization and metrology of high-aspect ratio (HAR) semiconductor structures using transmission small-angle X-ray scattering (SAXS). The solution consists of the Sirius-XCD® tool, NanoDiffract for XCD (NDX) analysis software and high-performance computing infrastructure. The solution provides quantitative information on the orientation and shape of HAR structures, such as 3D NAND channel holes and DRAM capacitors, and can be used for development and control of the critical etch processes used in the formation of such structures. The tool has been designed to minimize expensive cleanroom space without sacrificing performance with typical measurements taking only a few minutes per site. The analysis is done using real-time regression in parallel to the measurements to maximize the throughput of the solution. We will illustrate the key features of the solution using data from a HAR reference wafer and provide results for hole shape and tilt across the wafer together with complimentary data from other techniques. We will also discuss future opportunities for both stand-alone XCD applications and possibilities of XCD-OCD synergies including hybrid metrology in solving complex high-aspect ratio (HAR) and other applications.
Surfaces and interfaces of complex oxides materials provide a rich playground for the exploration of novel magnetic properties not found in the bulk but also the development of functional interfaces to be incorporated into applications. We have recently been able to demonstrate a new type of hybrid spin filter/ magnetic tunnel junction. Our hybrid spin-filter/magnetic-tunnel junction devices are epitaxial oxide junctions of La0:7Sr0:3MnO3 and Fe3O4 electrodes with magnetic NiMn2O4 barrier layers. Depending on whether the barrier is in a paramagnetic or ferromagnetic state, the junction exhibits magnetic tunnel junction behavior where the spin polarized conduction is dominated by the electrode-barrier interface or spin filter behavior where conduction is dominated by barrier layer magnetism.
The volume and weight budgets in missiles and gun-launched munitions have decreased with the military forces' emphasis on soldier-centric systems and rapid deployability. Reduction in the size of control actuation systems employed in today's aerospace vehicles would enhance overall vehicle performance as long as there is no detrimental impact on flight performance. Functional materials such as shape memory alloys (SMA's) offer the opportunity to create compact, solid-state actuation systems for flight applications. A hybrid SMA model was developed for designing micro-actuated flow effectors. It was based on a combination of concepts originally presented by Likhatchev for microstructural modelling and Brinson for modelling of transformation kinetics. The phase diagram for a 0.1mm SMA wire was created by carrying out tensile tests in a Rheometrics RSA-II solids analyser over a range of temperatures from 30°C to 130°C. The characterization parameters were used in the hybrid model to predict the displacement-time trajectories for the wire. Experimental measurements were made for a SMA wire that was subjected to a constant 150g load and short, intense 4.5 to 10V pulses. Actuation frequency was limited by the cooling rate rather than the heating rate. A second set of experiments studied the performance of SMA wires in an antagonistic micro-actuator set-up. A series of 2 or 3V step inputs were alternately injected into each wire to characterize the peak to peak displacement and the motion time constant. A maximum frequency of 0.25Hz was observed. An antagonistic actuator model based on the hybrid SMA model predicted reasonably well the displacement-time results.
Silicon nitride microbridges (50x50 mm2, 0.6 mm thick), suspended over a silicon substrate, were patterned and thinned. These patterns consist of 2 to 12 windows that were thinned to approximately 0.3 mm. Microbolometers were fabricated by sputtering a YBaCuO thin film over the bridges. The experimental results showed that the regionally thinned microbridges have a lower thermal time constants t (about 1.6 ms) than that of the standard pixel configuration (2.6 ms). On the other hand, the fact that the regionally thinned microbolometers having detectivity D* values comparable to or even six times superior than that of the standard pixel showed that the decrease in response time is not penalized by loss of detection performance. The simulation results also show that as the amount of material removed is increased, the thermal time constant drops significantly while the (τ/G)1/2 ratio (where G is the thermal conductance of the pixel) only decreases slightly, suggesting that the reduced response time will not cause a significant drop in detectivity D*. The simulation results of mechanical integrity show that a specific regionally thinned microbridge design has 22 % higher stiffness than that of a standard pixel design with similar thermal properties. The fact that thick regions remained on the regionally thinned pixels (like the edges of the pixels) provide significant mechanical support to the microstructures. This confirms the validity of the regionally thinned microbridges approach.
A substantial reduction in the size of control actuation systems employed in today's aerospace vehicles can enhance overall vehicle performance by reducing envelope volume requirements and inert weight. Functional materials such as shape memory alloys (SMA's) offer the opportunity to create compact, solid-state actuation systems by virtue of the material's ability to convert electrical energy to thermal energy to mechanical energy within its microstructure. A hybrid micro-macro-mechanical SMA model is developed for future closed-loop actuator development studies. The constitutive model is a combination of concepts originally presented by Likhatchev for microstructural modeling and Brinson for modeling of transformation kinetics. Global strain of the heterogeneous solid or polycrystal, where the grains are assumed to be randomly oriented, was calculated by averaging the elastic, thermal, stress-induced and autoaccomodation strains of each grain over the total material volume. The introduction of a frequency distribution function in the micromechanical model provided a convenient way to quantify texture. The model was successfully tested under constant temperature conditions and constant load-low frequency cycling conditions.
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