Since the Brain Order Disorder (BOD) group reported on a high density Electroencephalogram (EEG) to capture the neuronal information using EEG to wirelessly interface with a Smartphone [1,2], a larger BOD group has been assembled, including the Obama BRAIN program, CUA Brain Computer Interface Lab and the UCSD Swartz Computational Neuroscience Center. We can implement the pair-electrodes correlation functions in order to operate in a real time daily environment, which is of the computation complexity of O(N3) for N=102~3 known as functional f-EEG. The daily monitoring requires two areas of focus. Area #(1) to quantify the neuronal information flow under arbitrary daily stimuli-response sources. Approach to #1: (i) We have asserted that the sources contained in the EEG signals may be discovered by an unsupervised learning neural network called blind sources separation (BSS) of independent entropy components, based on the irreversible Boltzmann cellular thermodynamics(ΔS < 0), where the entropy is a degree of uniformity. What is the entropy? Loosely speaking, sand on the beach is more uniform at a higher entropy value than the rocks composing a mountain – the internal binding energy tells the paleontologists the existence of information. To a politician, landside voting results has only the winning information but more entropy, while a non-uniform voting distribution record has more information. For the human’s effortless brain at constant temperature, we can solve the minimum of Helmholtz free energy (H = E − TS) by computing BSS, and then their pairwise-entropy source correlation function. (i) Although the entropy itself is not the information per se, but the concurrence of the entropy sources is the information flow as a functional-EEG, sketched in this 2nd BOD report. Area #(2) applying EEG bio-feedback will improve collective decision making (TBD). Approach to #2: We introduce a novel performance quality metrics, in terms of the throughput rate of faster (Δt) & more accurate (ΔA) decision making, which applies to individual, as well as team brain dynamics. Following Nobel Laureate Daniel Kahnmen’s novel “Thinking fast and slow”, through the brainwave biofeedback we can first identify an individual’s “anchored cognitive bias sources”. This is done in order to remove the biases by means of individually tailored pre-processing. Then the training effectiveness can be maximized by the collective product Δt * ΔA. For Area #1, we compute a spatiotemporally windowed EEG in vitro average using adaptive time-window sampling. The sampling rate depends on the type of neuronal responses, which is what we seek. The averaged traditional EEG measurements and are further improved by BSS decomposition into finer stimulus-response source mixing matrix [A] having finer & faster spatial grids with rapid temporal updates. Then, the functional EEG is the second order co-variance matrix defined as the electrode-pair fluctuation correlation function C(s~, s~’) of independent thermodynamic source components. (1) We define a 1-D Space filling curve as a spiral curve without origin. This pattern is historically known as the Peano-Hilbert arc length a. By taking the most significant bits of the Cartesian product a≡ O(x * y * z), it represents the arc length in the numerical size with values that map the 3-D neighborhood proximity into a 1-D neighborhood arc length representation. (2) 1-D Fourier coefficients spectrum have no spurious high frequency contents, which typically arise in lexicographical (zig-zag scanning) discontinuity [Hsu & Szu, “Peano-Hilbert curve,” SPIE 2014]. A simple Fourier spectrum histogram fits nicely with the Compressive Sensing CRDT Mathematics. (3) Stationary power spectral density is a reasonable approximation of EEG responses in striate layers in resonance feedback loops capable of producing a 100, 000 neuronal collective Impulse Response Function (IRF). The striate brain layer architecture represents an ensemble <IRF< e.g. at V1-V4 of Brodmann areas 17-19 of the Cortex, i.e. stationary Wiener-Kintchine-Einstein Theorem. Goal#1: functional-EEG: After taking the 1-D space-filling curve, we compute the ensemble averaged 1-D Power Spectral Density (PSD) and then make use of the inverse FFT to generate f-EEG. (ii) Goal#2 individual wellness baseline (IWB): We need novel change detection, so we derive the ubiquitous fat-tail distributions for healthy brains PSD in outdoor environments (Signal=310°C; Noise=27°C: SNR=310/300; 300°K=(1/40)eV). The departure from IWB might imply stress, fever, a sports injury, an unexpected fall, or numerous midnight excursions which may signal an onset of dementia in Home Alone Senior (HAS), discovered by telemedicine care-giver networks. Aging global villagers need mental healthcare devices that are affordable, harmless, administrable (AHA) and user-friendly, situated in a clothing article such as a baseball hat and able to interface with pervasive Smartphones in daily environment.

Contamination of implanted surfaces by metals and dopants is a significant limitation to the use of high-dose implantation for semiconductor IC fabrication. RBS, SIMS, SRP, chemical etching and IC device parameter measurements have been used to characterize contaminated surfaces implanted with modern, production-type implanters. Levels of dopant cross-contamination of the order of 10% of the primary dose have been observed. A systematic study of the effects of As, P, B and Sb implanted Si has shown measurable effects on diffusion profiles and junction depths at contamination levels as low as 0.01% of the primary dose. These effects are particularly serious for fast-diffusing contaminants in slow-diffusing primary dopants (such as P contamination in As implants). Evidence has been found for both sputtering and ‘vaporization’ mechanisms for transfer of contaminants from implanter surfaces to the wafer target. The effectiveness of machine design choices and process procedures (such as wafer clamp design, post-implant chemical cleans, and the use of screen oxides) in minimizing the effects of contamination are discussed.

The grand challenges to the semiconductor industry in continuing the scaling of planar CMOS devices are described in the International Technology Roadmap for Semiconductors. One of these challenges is the requirement for the continuing reduction of the junction depth of shallow junctions such as the drain extension. The key potential solutions to this challenge involve the continued development of doping and annealing technologies. This paper describes the challenges and the potential solutions of the ITRS. The potential solutions figure describes much of the efforts of the industry. Each of the key elements of this figure is described. This is reviewed in the context of the highest level advantages and issues associated with each particular technology.

Beam-line ion implantation, the pre-eminent doping method in silicon, is being pushed to the limit by the need to fabricate ultra-shallow junctions. Plasma doping is envisaged to be the alternative technique suited for the shift to simpler, more economical, higher throughput, and cluster-compatible hardware. The technology has gained much momentum in the past several years and an international plasma doping users group has been formed to bring together equipment manufacturers, process engineers, and researchers. In this article (part one of two parts), we will review the current status of plasma doping, present the latest device data, and discuss process and equipment issues.

The National Technology Roadmap for Semiconductors calling for shallow junctions drives the exploration of alternate doping technologies, one of which is plasma doping (PLAD). There are many important issues when evaluating these technologies, but two of the most critical are device performance and contamination. This paper reports results on devices with various channel lengths manufactured by the plasma doping technique. Transistors fabricated with 250 nm technology, 65 A gate oxide, were tested for various device characteristics, such as threshold voltage and transconductance.

Doping requirements for ULSI CMOS transistors are discussed as well as effects that influence doping accuracy and junction location, minimum practical junction depths, the impact of epi or CZ wafers on transistor doping process, elemental contamination and the yield impact of small particles on low-energy implanted junctions. Various doping technologies; beamline implantation, plasma immersion, cluster-ion beams, gas immersion laser doping, CVD/RTP and MBE techniques, are benchmarked.

Plasma immersion ion implantation (PIII) is a cluster compatible doping and processing tool offering many inherent advantages over conventional beamline ion implantation. When first introduced in the late 1980s, the technique was primarily used to enhance the surface mechanical properties of metals. Recently, a substantial amount of research activities have focused on microelectronics and have led to a number of very interesting applications, such as the formation of shallow junction, synthesis of silicon-on-insulator, large area implantation, trench doping, conformal deposition, and so on. In this paper, we will review the principles of PIII, the dynamic sheath model for various kinds of plasma, reactor designs, recent applications in the area of microelectronics, as well as the future of PIII pertaining to semiconductor materials and processing.

Modeling of ULSI ion implantation processing poses a complex set of challenges for efficient description of physical processes. Accuracy requirements for range and damage profiles and the need for advances in modeling of defect-enhanced diffusion and dopant activation of Si are rapidly increasing. The overriding requirement is the need to incorporate accurate physical models into efficient descriptions of 3-dimensional device structures.

Compound implants using Si and F pre-implants with B and BF2 doping implants are investigated for B and F diffusion effects and residual defect levels. Physical methods (RBS, SIMS, SRP) are combined with optical scanning and depth profiling techniques (TW, PAD, Raman) to investigate the insights to be gained from use of a fuller set of characterization tools for defect engineering.

Methods are proposed for preparing a standard reference material (SRM) for ion implantation. This would provide a reliable means for certifying and calibrating equipment and measurement tools. The SRM would be a wafer implanted with a specified species, energy, and dose, and its average sheet resistance and uniformity would be specified within certain tolerances. The proposed standard represents the work of a number of collaborating organizations, which reviewed existing studies and also considered input from implant vendors and service organizations. Fabrication specifications are proposed along with plots indicating sensitivity of key results to various critical parameters of that process.

In this study, damage induced by Ar+ and Si+ ion implantation and its annealing behavior during rapid thermal annealing for 10 sec at temperatures between 575-1100°C were investigated by thermal wave modulated optical reflectance, deep level transient spectroscopy, reflection high energy electron diffraction, Rutherford backscattering aligned spectra and transmission electron microscopy. Our data show that (1) thermal wave signal and its variation with repect to rapid thermal anneal temperature strongly depend upon implant dose and anneal temperature; (2) both implant species induce four distinctive deep trap levels; (3) these traps evolve during rapid thermal annealing!; and (4) for the single Si+ ion implanted samples, the variation of total trap concentration with respect to rapid thermal anneal temperatures follows that of TW. However, in the case of Ar+ ion implanted samples, no apparent correlation between thermal wave signal and DLTS trap condition could be made.

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Although the ion implantation process has been widely used in silicon device manufacturing for two decades, there are major challenges for the future in each of the three coupled arenas that we have discussed. Our understanding of physical phenomena is not sufficiently complete, the demands for specific applications continually increase and the performance, reliability and cost of manufacturing machines are business imperatives.

Part I of this article (SST, December 1991) reviewed the history of ion implant uniformity mapping. In Part II, presently available equipment and techniques are reviewed and their capabilities summarized.

The Greater Silicon Valley Implant Users Group (GSVIUG) has been working with the American Society for Testing Materials (ASTM) and the National Institute of Standards and Technology (NIST, previously known as NBS) to develop a standard for ion implantation. This standard would address two critical needs of the industry: (1) standard reference material (SRM) for certifying and calibrating equipment, and (2) a recommended standard procedure for fabricating such a standard. The SRM would be a wafer that had been implanted with a specified species, energy and dose. Its average sheet resistance and uniformity would be certified to be within certain tolerances. It would be used to verify the performance of the four-point probe and sheet resistance mapping equipment and to calibrate analytical characterization techniques such as secondary ion mass spectroscopy (SIMS), Rutherford backscattering spectroscopy (RBS) and spreading resistance profiling (SRP). An unannealed sample could be used to calibrate Thermawave, ellipsometer and other optical tools and to verify annealing systems. The standard procedure would prescribe the recommended steps to produce the same wafer in the fab. This would help determine if an implanter is operating correctly at the specified conditions. We have reviewed all the previous implant round robins and studies and solicited input from implant vendors and implant service organizations in recommending a set of implant conditions for a proposed standard. Particular attention was paid to the requirement of stability over time and minimum variation with ambient temperature. Fabrication specifications for species, energy and dose are detailed. Plots are also presented for the sensitivity to various parameters that could influence the results, such as substrate resistivity, screen oxide thickness, anneal time and temperature and measurement conditions.

This paper is a review of current work to improve particulate control in ion implantation equipment. The first section includes current published research work which will be outlined and summarized. The second section focusses on work performed at National Semiconductor Corporation on testing and implementing an in situ particle monitoring system. The first equipment test consisted of a single monitor mounted in a medium current implanter. This test indicated that the particle signal correlated to surface scan monitor tests and that operating characteristics of the ion implanters which produce particles were observable. Our followup effort was an implementation of the in situ counters on all the implanters as a single particle counting system for the fab. The result of this work was a pareto-like analysis of machine and process issues which result in particle events. A correlation of lot-specific particle counts to yield was also developed. The advances in machine particulate control are contrasted with the needs and trends in process development. Although the advances in particulate control have been excellent, the predicted future requirements are even more stringent. The implications of these needs on both particulate performance and measurement are discussed.

The uniformity of ion implantation across a chip is becoming more important as the density of devices on a chip increases and the matching tolerance of device parameters across a chip decreases and becomes more critical. In order to investigate ion-implant micro-uniformity, a special van der Pauw mask was designed with 400 structures per square centimeter. This mask has been used with a polysilicon-on-oxide test structure to investigate chip micro-uniformity. Both medium- and high-current implanters have been studied using this dense van der Pauw pattern. Contour maps, 3D maps and histograms are used to display the variation of dose across a chip area. Results are also presented for micro-nonuniformity patterns deliberately introduced on a wafer. Several optical techniques are also presented to map closely spaced stripes across the wafer.

In the early days of semiconductor manufacturing, the four-point probe became established as the tool-of-choice for monitoring diffusion processes. The application of the four-point probe to ion implantation in the early 1960s was basically limited to the single-point measurement of dose, since the equipment did not have the necessary precision or repeatability to provide useful uniformity results. As a result, implanter uniformity was determined by either a visual observation of a heavily doped wafer or by a mylar burn. Unfortunately, these techniques were either subject to interpretation by the user or could not provide a parameter that could be statistically tracked or characterized.During the last 30 years, the commercial ion implanter as well as the dose and uniformity characterization equipment used to characterize this production tool have progressed significantly. Indeed, several generations of electrical and optimal equipment have been developed to measure both the dose and uniformity of the increasingly advanced and complex ion implanter. This paper will review all of the techniques and equipment used to measure the uniformity of ion implantation. In addition, various graphical techniques developed to present early measurement results will be discussed.