Process Recipe Research Articles

A Two-Step Dry Etching Model for Non-Uniform Etching Profile in Gate-All-Around Field-Effect Transistor Manufacturing.

The Gate-All-Around Field-Effect Transistor (GAAFET) is proposed as a successor to Fin Field-Effect Transistor (FinFET) technology to increase channel length and improve the device performance. The GAAFET features a complex multilayer structure, which complicates the manufacturing process. One of the most critical steps in GAAFET fabrication is the selective lateral etching of the SiGe layers, essential for forming the inner-spacer. Industry commonly encounters a non-uniform etching profile during this step. In this paper, a continuous two-step dry etching model is proposed to investigate the mechanism behind the formation of the non-uniform profiles. The model consists of four modules: anisotropic etching simulation, Ge atom diffusion simulation, Si/SiGe etch selectivity calculation and SiGe selective etching simulation. By calibrating and verifying this model with experimental data, the edge rounding and gradient etching rates along the sidewall surface are successfully simulated. Based on further examination of the influence of chamber pressure on the profile using this model, the inner-spacer shape is improved experimentally by appropriately reducing the chamber pressure. This work aims to provide valuable insights for etching process recipes in advanced GAAFETs manufacturing.

Process Recipe and Functional Circuitry Performance on Aerosol Jet Printed Water-Based Silver Ink

Process Recipe and Functional Circuitry Performance on Aerosol Jet Printed Water-Based Silver Ink

White and wholewheat bread consumption and the risk of exposure to acrylamide and 5-hydroxymethylfurfural

This study used a green validated method to evaluate the risk of exposure of individuals of different ages to acrylamide (AA) and 5-hydroxymethylfurfural (5-HMF) by consuming white and wholewheat bread. Recoveries of AA and 5-HMF were 100.7% and 100.1%, respectively, while uncertainty was 2.3% and 6.2%. Levels of AA ranged from 617.22 to 3151.8 μg/kg while levels of 5-HMF ranged from 180.5 to 648.2 μg/kg. Female adolescents were almost 2-fold exposed to AA when they consumed 100% wholewheat bread (2.93 μg/kg bw/day) by comparison with white bread (1.72 μg/kg bw/day). Estimated daily exposure to AA was 1.5-fold higher than international recommendations. These findings raise concern for health risks associated with exposure to processing contaminant as the result of bread consumption, especially made from whole grains. Since development of those compounds is inevitable during breadmaking, it is crucial to standardize processing conditions and recipes to mitigate it.

Reliability Assessment and Multi-Physics Simulation of Additively Printed Wearable Humidity Sensor with Super Capacitive Material for Astronaut in Extreme Condition

Abstract Additive technologies, such as aerosol jet printing, direct write printing are increasingly being used in the production of printed circuit boards because they eliminate the need for costly tooling, such as photomasks or etching containers. This is because additive methods allow for the direct deposition of printing materials onto a substrate. This versatility in a broad variety of applications allows engineers to create diverse applications, such as sensing devices with ECG sensors, pulse-oxygen sensors, galvanic skin response sensors, body temperature sensors, humidity sensors, and so on. Due to its potential for adaptability and integration, the development of additively printed humidity sensors has been the subject of several prior investigations. There are still issues with the reliability of current humidity sensor technology when flexing force is coupled with the humidity sensor. For the avoidance of stability issues, it is required to develop a better printing technique, process recipe, and sensing material encapsulation. In this research, the direct-write (D-write) printing approach with a nScrypt printer was employed to print the humidity sensor as a test vehicle in a laboratory setting. The sensor was characterized by analyzing the print recipe and its interaction with humidity in regards to resistance and humidity sensitivity. Additionally, the characterization of sensor accuracy, hysteresis, linearity, and stability in relation to temperature and humidity variation has been measured. Furthermore, a multi-physics simulation model was created in order to comprehend the electrochemical processes that occur when the humidity sensor is exposed to a very humid environment.

Plasma heating characterization of the large area inductively coupled plasma etchers with the plasma information for managing the mass production

Meter-scale of the large area inductively coupled plasma etchers with the capacitive power coupling are widely applied for the mass production of OLED (organic light emitting diode) display panels. Because of the large area-to-volume ratio of the etcher, the balance between the power loss and absorption is easily located in the capacitive coupling mode rather than the ideal inductively coupled mode. Therefore, the process results are sensitively governed by the power absorption and plasma heating properties of the reactors. We have introduced a new PI (plasma information) parameter, the ratio of the stochastic heating to Ohmic heating of the plasmas, which is monitorable by using the optical emission spectroscopy data of the processing etchers. With the help of this plasma heating characteristic index, we could optimize the process recipes with the detailed control of the etched hole sidewall passivation and related species generation rate in the plasmas; thus, chamber-to-chamber matching in the huge mass production fab with the higher efficiency was possible. It was demonstrated that the introduced PI index with plasma heating mechanism characterization could be applicable to the VM (virtual metrology) modeling as one of the good information supplying core variables. This PI index has shown a very high correlation with the plasma sheath and ion flux governing phenomena for a large number of mass-produced OLED display glasses. From these results, the introduced plasma heating mechanism-based PI index is expected to be utilized as a good reference index for their performance analysis or PI-VM modelings.

Robust modeling of material flows to end‐uses under uncertainty: UK wood flows and material efficiency opportunities

AbstractIn this study we quantify wood flows from raw materials to end‐uses for the United Kingdom in a robust way using a new material flow analysis (MFA) model with uncertainty. This is important to identify opportunities for efficiency given constraints on wood supply. We have developed a new “ProbPACTOT” MFA model which introduces a systematic method to handle mixed units during reconciliation and uncertainty in data observations, conversion factors, and process recipes. This makes it possible to track material flows all the way to end‐uses, which is otherwise difficult because the diverse materials, data types, and units used to quantify end‐products are hard to integrate into standard allocation‐based MFA models. We apply the model for the case of wood in the United Kingdom by defining 56 process recipes and reconciling 117 data observations from various sources. The results quantify upstream production and trade flows, through to 19 specific end‐uses of wood fibers. We use this to show the potential scale of savings by enhancing material efficiency; for example, if pallets were used 25% more intensively, 0.49 0.2 of wood fibers could be saved, corresponding to 4%–7% of the total soft sawnwood consumption of the United Kingdom. Judging the scale of opportunities for wood material efficiency in the United Kingdom is important domestically, and has global significance as the United Kingdom is the second largest net importer of wood products in the world. Moreover, this study proposes an important advancement in MFA giving a structure for modeling uncertain material flows up to end‐uses, applicable to any material. This article met the requirements for a gold‐gold JIE data openness badge described at http://jie.click/badges.

Tensile behaviors of rolled and annealed 90W7Ni3Fe alloy

Tungsten heavy alloys (WHAs) with two-phase composite structures display unique mechanical properties. Here, we explore the effects of rolling strain and annealing temperature on tensile behaviors of 90W7Ni3Fe WHAs. Cold rolling followed by low-temperature annealing (<1000 °C) induces an increase in yield strength at the expense of ductility. The ductility of WHAs can only be restored by raising the annealing temperature to 1000 °C. Keep the annealing at 1000 °C while gradually increasing the rolling strain not only improves the strength of WHAs but also maintain a good ductility. Once exceeding a critical rolling strain of 60 %, the yield strength of WHAs increases to 1480 MPa, while result in a substantial decrease in ductility. The evolutions of two-phase composite structures with rolling and annealing induces the alterations of the tensile properties of WHAs. These results provide a reference for designing thermal-mechanical processing recipes for WHAs.

Processes for Thinning and Polishing Highly Warped Die to a Nearly Consistent Thickness: Part III

Abstract This article is the third in a multi-part series describing techniques for thinning and polishing a highly warped die. Tighter thickness tolerance and thinner samples are always desired. The first article addressed global thinning of a sample. The second focused on the process and problems of thinning only the area of interest. This installment covers processes and considerations for both global and area of interest treatment and provides reference process recipes.

Scheduling a Single-Arm Two-Cluster Tool With a Process Module Failure Subject to Wafer Residency Time Constraints

Multi-cluster tools are widely adopted in semiconductor manufacturing. When a process module (PM) at a step fails, a multi-cluster tool cannot complete the process recipe of work-in-process wafers and must be forced to enter a closedown process to be empty. To increase the throughput of a wafer fab, it is economically significant to shorten the failure-closedown process. However, due to the wafer residency time constraints, it is highly challenging to respond to a PM failure and find a corresponding optimal schedule. By assuming no parallel PM at a step, this work is the first to study this important issue for scheduling multi-cluster tools. We analyze the task sequences and synchronization conditions for robot activities to avoid deadlock in a shared buffer module. Upon these analyses, for process-dominant multi-cluster tools whose optimal steady-state schedule is known, algorithms are proposed to synthesize the proper sequences for robots in case of PM failures, then, a nonlinear program model is proposed to find an optimal schedule for the corresponding closedown process or decide no feasible solutions. The proposed model can uniformly deal with different scenarios of PM failures. Examples are given to illustrate the application of the proposed method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In a wafer fab, there are hundreds, even thousands, of cluster tools. It is common that a failure of a processing module happens in a cluster tool. How to intelligently respond to such a random failure in a multi-cluster tool is an important issue in real-world production. This paper studies the scheduling problem of a multi-cluster tool in case of a failure at a PM. For a multi-cluster tool in case of a failure module, the proposed method can significantly reduce the loss of work-in-process wafers and shorten the closedown process.

Fabrication of low-dimensional superparamagnetic vanadium diselenide clusters for expanding magnetic storage capacity

The chip performance has been improving with the process technology in recent years following the Moore's law. Their applications and necessities are in various fields such as 5G communications, Internet of Things (IoT), mining cryptocurrency and Neural network computing (NNC) for artificial intelligence (AI). However, when the processing signals are emitted from processing units and finally transferred to memories, the transferring speed is decreasing. Therefore, among all the novel research of memories, it is anticipated to develop the technology with high storage capacity and enough processing performance. From previous literature of Intel published in 2020, the technology with those characteristics is determined as warm memory. During the following years, the most distinctive technology is MRAM which utilizes magnetic materials as core technology breaking the component frame of using electric materials and impacting the developing direction of memory. But among the development of MRAM in recent years, the significant difficulties are the competition between magnetic anisotropy energy and heat in micro-size range resulting in the transition from superparamagnetism to ferromagnetism confining the smallest size in component development for MRAM. So the novel solution is utilizing the transition metal dichalcogenides (TMDs) in order to produce low dimensional applications of spintronic thin films. In this report, we utilize the TMD material, VSe2 which is firstly published as a process recipe of self-assembled zero dimensional (0D) superparamagnetic clusters. In addition, a novel mechanism called expanding magnetic technology (ExM tech.) is demonstrated by superparamagnetic VSe2/ferromagnetic Co interfaces. The 0D superparamagnetic clusters are successfully synthesized on the surface of ferromagnetic thin films. The direction of magnetization for those superparamagnetic clusters will transform from random alignment to the specific alignment along with the magnetization direction of the ferromagnetic thin films which is attributed to the pinning from the ferromagnetic thin films. Therefore, the total magnetization of magnetic thin films can be significantly enhanced in size range of angstrom by ExM tech. After million cycles of reliability examinations, the magnetic properties remain stable. This technology will be beneficial for the applications on component process which can reach the expected total magnetizations with smaller size of magnetic thin films in MRAM. Those research results give MRAM as a nvRAM great potential on the commercial production.

Photosensitivity reversal in solution-processed Copper Zinc Tin Sulphide/Cadmium Sulphide superstrate junction

Inverse photosensitivity is a sought-after property for the development of photonic devices and non-volatile memories with low power conversion. Herein, we report on the development of a superstrate-type thin film junction exhibiting inverse photosensitivity which does not involve the use of a pricy transparent conducting oxide layer, providing a method for engineering low-cost thin film devices. Sequential ionic layer adsorption reaction (SILAR) was used to grow Copper Zinc Tin Sulphide (CZTS) and Cadmium sulphide (CdS) large area thin film p-n diode junction. Uniform CZTS thin films with an area of ∼10 cm2 which were free of pin holes or voids could be deposited using an optimized SILAR process recipe. The grown CZTS films exhibited an electrical resistivity of 4.4 × 10−4 Ωm using silver (Ag) electrodes. CdS thin films were sub-sequentially grown over the CZTS layer to form a p-n junction. A knee voltage of 0.2 V in the device configuration “glass/CZTS/CdS/Ag” was observed in the current voltage characteristics. The as-prepared and the vacuum-annealed p-n junction exhibited negative photosensitivity of magnitude 0.21 and 0.16 respectively. The air-annealed device structure exhibited photosensitivity of 216.

Understanding and modelling the aquafeed extrusion process for Atlantic salmon feed with an empirical model

An empirical model was applied to quantitatively model the effects of extrusion variables and recipe compositions on quality of feed pellets. Lab extrusion trials were performed with an Atlantic salmon feed recipe with using a central component design (CCD). Comparing with a coated commercial feed made with the same recipe, the lab extrusion pellets had similar bulk density, hardness, and durability properties. A Response Surface Method (RSM) was also used to regress the extrusion trial data and compared with the empirical model results. The respective Absolute Average Deviation (AAD %) values of the empirical model and RSM regression were 4.1 % and 1.8 % for pellet bulk density, 7.4 % and 4.9 % for pellet hardness, 10.4 % and 10.0 % for pellet oil absorption, 13.7 % and 8.3 % for pellet water stability, and 11.3 % and 5.5 % for pellet durability. Using the model coefficients obtained from the extrusion results, the empirical model can partly extrapolate the pellet qualities of an additional extruded recipe, which has a slightly adjusted wheat gluten and wheat. The model performance was evaluated based on. R2, RSME (root-mean-square deviation), AAD % of the empirical model was better than the RSM model to predict the effects of extrusion variables on pellet quality parameters. The effects of the extrusion process variables and recipe composition on pellet quality parameters are predicted by the empirical model. Its demonstrates that the empirical model is a new method to understand extrusion trial results in different extrusion systems and recipes without changing its mathematical form of expression, which gives a common reference to compare an extruded recipe in different systems and has practical engineering applications.

Abnormal Chamber Detection in the Etching Process Using Time-Series Data Augmentation and Soft Labeling

In the semiconductor manufacturing etching process, a considerable amount of good-quality data can be obtained by the measurement process. As the etching process has an impact on subsequent processes and to check and control the condition of the wafer, the measurement process should be performed as much as possible. However, with the rapid development of technology in manufacturing, the process recipe has undergone frequent changes. Accordingly, the amount of data available in the field is limited, and the effective utilization of measured data is needed to improve the model’s performance in abnormal chamber detection. In this article, we propose to augment time-series data that are collected from equipment sensors in the etching process to improve the model’s performance. To accomplish this task, we utilize dynamic time-warping barycenter averaging (DBA) and soft labeling. DBA is applied to calculate the average of the time series, and the new label is given in the form of a soft label. To verify the efficiency of the proposed method, we compared several regression models with the proposed method and with several benchmark methods. In addition, we compared the proposed method with soft labeling and hard labeling. The experimental results show that the model with the proposed method is superior to the model with its other benchmark methods.

Influence of boron implantation induced defects on solar cells: Modeling the process defects

The effect of process-induced defects on the photo-generated charge-carrier lifetime and solar cell performance is critical, which will help optimize the process recipe. In this work, we attempt to quantify the effects of process-induced defects during boron implantation on the n-type silicon wafer in different annealing ambiences. We have evaluated the role of defects that can be formed during oxygen and inert ambience annealing on n-type bifacial passivated emitter rear totally diffused solar cells using a recombination current prefactor (J0). The numerically calculated J0 is calibrated with the reported experimental J0 values using two different methods: (i) Shockley–Read–Hall lifetime and (ii) effective trap-density method. In the latter method, we used the simulated defect density profiles. Both methods capture the process-induced degradation. We observed that the process-induced defects could deteriorate by almost 1% absolute efficiency for the considered annealing conditions. We found that dislocation loops alone cause an ignorable effect on terminal characteristics, but other process-induced mechanisms could dominantly degrade the cell's performance. To further support, we show that independent defects (apart from coupled defects) other than dislocation loops could explain the experimentally reported boron-implanted diodes’ J–V curves under reverse bias conditions.

Level Set Simulation on Single Wafer Wet Processing Improvement

To improve the single wafer process for wafer edge yield performance, the liquid film thickness is the key indicator to be investigated. The traditional measurement of liquid film thickness is difficult to execute, due to wafer spinning. The numerical method becomes essential to simulate the process. This paper uses the multiple flow level set method to simulate single wafer spin process. An inlet hydraulic jump is approximated by a two-dimensional axisymmetric approach with a collar inlet. Various spin rotation speeds, variable flow rates, different liquid types and contact angles are simulated. The results indicate liquid film discontinuity at a certain radius and a lower shear rate at the wafer edge. After modifying the process recipe based on the level set simulation result, the wafer edge yield shows improvement. This level set simulation model provides useful information for single wafer wet process control. The level set simulation results can estimate the liquid distribution on the wafer surface before the real process and can avoid experiments on production wafers and hence lead to a lower cost.

Effect of Laser Scribing on Coating, Drying, and Crystallization of Absorber Layer of Perovskite Solar Cells

Large‐area perovskite solar modules fabrication has been demonstrated with a rapid process of large‐area slot‐die coating, drying, and crystallization using near‐infrared radiation in ambient air, in which the laser‐scribing process is applied to fabricate the modules. However, defective coating of perovskite layer near laser‐scribed P1 line which isolates the front electrode of transparent conductive oxide (TCO) results very low module efficiencies. Therefore, systematic study is conducted to investigate the root cause, mechanism and solution of the defective coating and crystallization of the perovskite layer. Scanning electron microscope, energy‐dispersive X‐ray spectroscopy, and atomic force microscopy are used to characterize the TCO film before and after P1 scribing. It is found that P1 laser‐scribing process changes surface morphology of TCO at the area near P1 line, which decreases the surface wettability and results discontinuous coating of precursor solution near P1 lines. The absence of TCO material in the P1 trench induces nonuniform heating during NIR annealing step, which is verified by thermal analysis via numerical simulation. After tuning laser process recipes, a large module with an active area of 46 cm2 is fabricated with a power conversion efficiency of 7.2% and geometry fill factor of 93.8%.

Chemistry, Medicine, and Gold-Making: Tycho Brahe, Helwig Dieterich, Otto Tachenius, and Johann Glauber.

17th century chemistry was concerned largely with iatrochemistry (medicinal chemistry) and the transmutation of metals, especially with the purpose of making gold. Thus, Johann Rudolph Glauber made a living making and selling chemicals such as nitric acid and medicaments such as aurum potabile (drinkable gold), but he also believed in the transmutation or "improvement" of metals and the "augmentation" of gold, and he sold recipes for such processes. This perspective aims to provide a snapshot of the range of 17th century chemistry by analysis of the efforts of four representatives to make drugs, chemicals, and gold. It will be concluded that early modern chemists were unable to break out from the conceptual doctrines imposed by Aristotle and Paracelsus, which made transmutation perfectly logical. No further scientific advance could be made until the idea that all things are composed of the same basic constituents was abandoned in favour of the atomic theory.

Physico‐nutritional characterization of composite cassava and orange‐fleshed sweet potato flours and sensory evaluation of “fufu” prepared from the flour blends

AbstractThe orange‐fleshed sweet potato (OFSP) is being promoted for consumption as a public health tool to combat vitamin A deficiency diseases in Africa. As a staple diet in many households in West Africa, “fufu” aptly lends itself to fortification with OFSP for the delivery of essential micronutrients for health improvement. In this study, the nutritional and functional characteristics of composite cassava/OFSP flours for preparation into "fufu" were examined, and the cooked food was subjected to sensory evaluation. OFSP enriched the nutritional composition as its substitution levels for cassava increased. However, the texture and pasting properties degraded concomitantly during the heating process. Sensory panelists preferred "fufu" prepared from the composite flours with up to 5% replacement of cassava with OFSP. This can potentially contribute 39–77% of the Recommended Dietary Allowance of vitamin A for children and 33% for women of reproductive age and help alleviate related deficiency diseases.Practical applicationsReducing hunger and promoting health is the foremost objective of the Sustainable Development Goals 2 and 3. This requires prioritizing specific food micronutrients and establishing approaches to deliver them to the consuming public. "Fufu" is a staple diet regularly consumed in many households in West Africa. However, its nutritional content is low due to the low content of micronutrients in the traditional ingredients. A new processing recipe for "fufu", which uses the composite flours of the ingredients, aptly lends it to fortification with nutrient‐rich ingredients to administer the essential dietary requirements of its consumers. Given the substantial composition of important food micronutrients, particularly β‐Carotene, in the orange‐fleshed sweet potato (OFSP), it is the most considered candidate crop for meeting the critical dietary needs of people plagued with vitamin A deficiency diseases. The importance of this study, therefore, lies in the development of a new "fufu" product fortified with OFSP to avert the vitamin A deficiency diseases that mostly affect women of reproductive age and children in Africa.

One Class Process Anomaly Detection Using Kernel Density Estimation Methods

We present a one-class anomaly detection method that uses time series sensor data to detect anomalies or faults in semiconductor fabrication processes. Critically, this method is trained using only small amounts of known successful run data, making it possible to implement for many processes and recipes without needing example faults. The proposed method uses kernel density estimation (KDE) to create probability distributions for sensor values during nominal processing. When classifying unseen sensor data, we determine the likelihood that it arose from this (often non-Gaussian) nominal distribution, allowing us to classify new signals as nominal, or faulty. We present model extensions that enable adaptation to changes in the underlying process, i.e., concept drift, as well as transfer learning techniques that enable training of anomaly detectors for new process recipes with less data. The proposed methods are tested on historical data from plasma etch and ion implantation processes, outperforming benchmark methods including traditional statistical process control (SPC), one-class support vector machine (OC-SVM), and variational auto-encoder (VAE) based detectors.

Systematic study of niobium thermal treatments for superconducting radio frequency cavities employing x-ray photoelectron spectroscopy

The structural and chemical composition of the surface layer (100–140 nm) of niobium radiofrequency cavities operating at cryogenic temperature has enormous impact on their superconducting characteristics. During the last years, cavities treated with a new thermal processing recipe, so-called nitrogen infusion, have demonstrated an increased efficiency and high accelerating gradients. The role and importance of nitrogen gas has been a topic of many debates. In the present work we employ variable-energy synchrotron x-ray photoelectron spectroscopy (XPS), to study the niobium surface subjected to the following treatments: vacuum annealing at 800 °C, nitrogen infusion, and vacuum heat treatment as for the infusion process but without nitrogen supply. Careful analysis of XPS energy-distribution curves revealed a slightly increased thickness of the native oxide Nb2O5 for the infused samples (∼3.8 nm) as compared to the annealed one (∼3.5 nm) which indicates insignificant oxygen incorporation into niobium during 120 °C baking and no effect of nitrogen on the formation of oxides or other niobium phases. By conducting an additional in-situ annealing experiment and analyzing the niobium after the failed infusion process, we conclude that the vacuum furnace hygiene particularly during the high-temperature stage is the prerequisite for success of any treatment recipe.