Revera

Chronic non-healing wounds are a burden in the Long-Term Care (LTC) sector, increasing costs, morbidity, and mortality and causing pain and suffering. The objective of this LTC Innovation pilot was to test the value of a promising new neuromuscular stimulation device in elevating the experience and satisfaction of the residents, engaging and empowering the nursing staff, and improving healing and/or reducing costs. Small, wireless, and worn at the knee, this muscle pump activator is self-contained, wearable, and battery-powered to increase lower-leg blood circulation (up to 60% of that achieved by walking). It has no wires, weighs just 10 g, and is easy to use. Nurses in four LTC homes identified residents with non-healing lower leg wounds. Consent was obtained, and on-site training was delivered. Eleven residents were recruited. Only seven met the inclusion criteria for venous/mixed or diabetic foot ulcers. Of the seven who met the criteria and were adherent with best practices and the muscle pump activator, four healed 100%, and one healed 90%. Two patients with other aetiologies, who were also adherent, healed. All adherent residents had an average weekly decrease in wound size of 9.75% and were extremely happy with the results. Three residents who were non-adherent had a 9.25% increase in wound size per week. One patient with diabetic foot ulcers developed skin changes at the end of life and passed away. Nursing staff and cognisant residents can easily adjust the pulse of muscle pump activator, and application and removal are simple. Most residents feel engaged with the therapy "because they feel it working". The LTC corporation feels that it is a great adjunctive solution for many types of lower-leg wounds (venous, mixed, diabetic, pressure) in addition to best practices in the LTC and Retirement home sectors.

Electrical test measurement in the back-end of line (BEOL) is crucial for wafer and die sorting as well as comparing intended process splits. Any in-line, nondestructive technique in the process flow to accurately predict these measurements can significantly improve mean-time-to-detect (MTTD) of defects and improve cycle times for yield and process learning. Measuring after BEOL metallization is commonly done for process control and learning, particularly with scatterometry (also called OCD (Optical Critical Dimension)), which can solve for multiple profile parameters such as metal line height or sidewall angle and does so within patterned regions. This gives scatterometry an advantage over inline microscopy-based techniques, which provide top-down information, since such techniques can be insensitive to sidewall variations hidden under the metal fill of the trench. But when faced with correlation to electrical test measurements that are specific to the BEOL processing, both techniques face the additional challenge of sampling. Microscopy-based techniques are sampling-limited by their small probe size, while scatterometry is traditionally limited (for microprocessors) to scribe targets that mimic device ground rules but are not necessarily designed to be electrically testable. A solution to this sampling challenge lies in a fast reference-based machine learning capability that allows for OCD measurement directly of the electrically-testable structures, even when they are not OCD-compatible. By incorporating such direct OCD measurements, correlation to, and therefore prediction of, resistance of BEOL electrical test structures is significantly improved. Improvements in prediction capability for multiple types of in-die electrically-testable device structures is demonstrated. To further improve the quality of the prediction of the electrical resistance measurements, hybrid metrology using the OCD measurements as well as X-ray metrology (XRF) is used. Hybrid metrology is the practice of combining information from multiple sources in order to enable or improve the measurement of one or more critical parameters. Here, the XRF measurements are used to detect subtle changes in barrier layer composition and thickness that can have second-order effects on the electrical resistance of the test structures. By accounting for such effects with the aid of the X-ray-based measurements, further improvement in the OCD correlation to electrical test measurements is achieved. Using both types of solution incorporation of fast reference-based machine learning on nonOCD-compatible test structures, and hybrid metrology combining OCD with XRF technology improvement in BEOL cycle time learning could be accomplished through improved prediction capability.

Advanced technology nodes, 10 nm and beyond, employing multipatterning techniques for pitch reduction pose new process and metrology challenges in maintaining consistent positioning of structural features. A self-aligned quadruple patterning (SAQP) process is used to create the fins in FinFET devices with pitch values well below optical lithography limits. The SAQP process bears the compounding effects from successive reactive ion etch and spacer depositions. These processes induce a shift in the pitch value from one fin compared to another neighboring fin. This is known as pitch walking. Pitch walking affects device performance as well as later processes, which work on an assumption that there is consistent spacing between fins. In SAQP, there are three pitch walking parameters of interest, each linked to specific process steps in the flow. These pitch walking parameters are difficult to discriminate at a specific process step by singular evaluation technique or even with reference metrology, such as transmission electron microscopy. We will utilize a virtual reference to generate a scatterometry model to measure pitch walk for SAQP process flow. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)

Gate-all-around (GAA) nanowire (NW) devices have long been acknowledged as the ultimate device from an electrostatic scaling point of view. The GAA architecture offers improved short channel effect (SCE) immunity compared to single and double gate planar, FinFET, and trigate structures. One attractive proposal for making GAA devices involves the use of a multilayer fin-like structure consisting of layers of Si and SiGe. However, such structures pose various metrology challenges, both geometrical and material. Optical Scatterometry, also called optical critical dimension (OCD) is a fast, accurate and non-destructive in-line metrology technique well suited for GAA integration challenges. In this work, OCD is used as an enabler for the process development of nanowire devices, extending its abilities to learn new material and process aspects specific to this novel device integration. The specific metrology challenges from multiple key steps in the process flow are detailed, along with the corresponding OCD solutions and results. In addition, Low Energy X-Ray Fluorescence (LE-XRF) is applied to process steps before and after the removal of the SiGe layers in order to quantify the amount of Ge present at each step. These results are correlated to OCD measurements of the Ge content, demonstrating that both OCD and LE-XRF are sensitive to Ge content for these applications.

Advanced technology nodes, 10nm and beyond, employing multi-patterning techniques for pitch reduction pose new process and metrology challenges in maintaining consistent positioning of structural features. Self-Aligned Quadruple Patterning (SAQP) process is used to create the Fins in FinFET devices with pitch values well below optical lithography limits. The SAQP process bares compounding effects from successive Reactive Ion Etch (RIE) and spacer depositions. These processes induce a shift in the pitch value from one fin compared to another neighboring fin. This is known as pitch walking. Pitch walking affects device performance as well as later processes which work on an assumption that there is consistent spacing between fins. In SAQP there are 3 pitch walking parameters of interest, each linked to specific process steps in the flow. These pitch walking parameters are difficult to discriminate at a specific process step by singular evaluation technique or even with reference metrology such as Transmission Electron Microscopy (TEM). In this paper we will utilize a virtual reference to generate a scatterometry model to measure pitch walk for SAQP process flow.