High Precision Plasma Etch for Pattern Transfer: Towards Fluorocarbon Based Atomic Layer Etching

A basic requirement of a plasma etching process is fidelity of the patterned organic materials. In photolithography, a He plasma pretreatment (PPT) based on high ultraviolet and vacuum ultraviolet (UV/VUV) exposure was shown to be successful for roughness reduction of 193nm photoresist (PR). Typical multilayer masks consist of many other organic masking materials in addition to 193nm PR. These materials vary significantly in UV/VUV sensitivity and show, therefore, a different response to the He PPT. A delamination of the nanometer-thin, ion-induced dense amorphous carbon (DAC) layer was observed. Extensive He PPT exposure produces volatile species through UV/VUV induced scissioning. These species are trapped underneath the DAC layer in a subsequent plasma etch (PE), causing a loss of adhesion. Next to stabilizing organic materials, the major goals of this work included to establish and evaluate a cyclic fluorocarbon (FC) based approach for atomic layer etching (ALE) of SiO2 and Si; to characterize the mechanisms involved; and to evaluate the impact of processing parameters. Periodic, short precursor injections allow precise deposition of thin FC films. These films limit the amount of available chemical etchant during subsequent low energy, plasma-based Ar+ ion bombardment, resulting in strongly time-dependent etch rates. In situ ellipsometry showcased the self-limited etching. X-ray photoelectron spectroscopy (XPS) confirms FC film deposition and mixing with the substrate. The cyclic ALE approach is also able to precisely etch Si substrates. A reduced time-dependent etching is seen for Si, likely based on a lower physical sputtering energy threshold. A fluorinated, oxidized surface layer is present during ALE of Si and greatly influences the etch behavior. A reaction of the precursor with the fluorinated substrate upon precursor injection was observed and characterized. The cyclic ALE approach is transferred to a manufacturing scale reactor at IBM Research. Ensuring the transferability to industrial device patterning is crucial for the application of ALE. In addition to device patterning, the cyclic ALE process is employed for oxide removal from Si and SiGe surfaces with the goal of minimal substrate damage and surface residues. The ALE process developed for SiO2 and Si etching did not remove native oxide at the level required. Optimizing the process enabled strong O removal from the surface. Subsequent 90% H2/Ar plasma allow for removal of C and F residues.

The State of our Toolbox: A Meta-analysis of Reliability Measurement Precision

My study investigated internal consistency estimates of psychometric surveys as an operationalization of the state of measurement precision of constructs in industrial and organizational (I/O) psychology. Analyses were conducted of samples used in research articles published in the Journal of Applied Psychology between 1975 and 2010 in five year intervals (K = 934) from 480 articles yielding 1427 coefficients. Articles and their respective samples were coded for test-taker characteristics (e.g., age, gender, and ethnicity), research settings (e.g., lab and field studies), and actual tests (e.g., number of items and scale anchor points). A reliability and inter-item correlations depository was developed for I/O variables and construct groups. Personality measures had significantly lower inter-item correlations than other construct groups. Also, internal consistency estimates and reporting practices were evaluated over time, demonstrating an improvement in measurement precision and missing data.

Detectability of migrating raptors and its effect on bias and precision of trend estimates

Annual counts of migrating raptors at fixed observation points are a widespread practice, and changes in numbers counted over time, adjusted for survey effort, are commonly used as indices of trends in population size. Unmodeled year-to-year variation in detectability may introduce bias, reduce precision of trend estimates, and reduce power to detect trends. We conducted dependent double-observer surveys at the annual fall raptor migration count at Lucky Peak, Idaho, in 2009 and 2010 and applied Huggins closed-capture removal models and information-theoretic model selection to determine the relative importance of factors affecting detectability. The most parsimonious model included effects of observer team identity, distance, species, and day of the season. We then simulated 30 years of counts with heterogeneous individual detectability, a population decline (λ = 0.964), and unexplained random variation in the number of available birds. Imperfect detectability did not bias trend estimation, and increased the time required to achieve 80% power by less than 11%. Results suggested that availability is a greater source of variance in annual counts than detectability; thus, efforts to account for availability would improve the monitoring value of migration counts. According to our models, long-term trends in observer efficiency or migratory flight distance may introduce substantial bias to trend estimates. Estimating detectability with a novel count protocol like our double-observer method is just one potential means of controlling such effects. The traditional approach of modeling the effects of covariates and adjusting the index may also be effective if ancillary data is collected consistently.

High-precision force sensing using a single trapped ion

We introduce quantum sensing schemes for measuring very weak forces with a single trapped ion. They use the spin-motional coupling induced by the laser-ion interaction to transfer the relevant force information to the spin-degree of freedom. Therefore, the force estimation is carried out simply by observing the Ramsey-type oscillations of the ion spin states. Three quantum probes are considered, which are represented by systems obeying the Jaynes-Cummings, quantum Rabi (in 1D) and Jahn-Teller (in 2D) models. By using dynamical decoupling schemes in the Jaynes-Cummings and Jahn-Teller models, our force sensing protocols can be made robust to the spin dephasing caused by the thermal and magnetic field fluctuations. In the quantum-Rabi probe, the residual spin-phonon coupling vanishes, which makes this sensing protocol naturally robust to thermally-induced spin dephasing. We show that the proposed techniques can be used to sense the axial and transverse components of the force with a sensitivity beyond the yN/\wurzel{Hz}range, i.e. in the xN/\wurzel{Hz}(xennonewton, 10^−27). The Jahn-Teller protocol, in particular, can be used to implement a two-channel vector spectrum analyzer for measuring ultra-low voltages.

Evaluation of a 2D multileader training system for improving sustainability and precision orchard management applications in italian apple orchards

The presented study aimed to evaluate the productive and physiological behavior of a 2D multileader apple training systems in the Italian environment both investigating the possibility to increase yield and precision crop load management resolution. Another objective was to find valuable thinning thresholds guaranteeing high yields and matching fruit market requirements. The thesis consists in three studies carried out in a Pink Lady®- Rosy Glow apple orchard trained as a planar multileader training system (double guyot). Fruiting leaders (uprights) dimension, crop load, fruit quality, flower and physiological (leaf gas exchanges and fruit growth rate) data were collected and analysed. The obtained results found that uprights present dependence among each other and as well as a mutual support during fruit development. However, individual upright fruit load and upright’s fruit load distribution on the tree (~ plant crop load) seems to define both upright independence from the other, and single upright crop load effects on the final fruit quality production. Correlations between fruit load and harvest fruit size were found and thanks to that valuable thinning thresholds, based on different vegetative parameters, were obtained. Moreover, it comes out that an upright’s fruit load random distribution presents a widening of those thinning thresholds, keeping un-altered fruit quality. For this reason, uprights resulted a partially physiologically-dependent plant unit. Therefore, if considered and managed as independent, then no major problems on final fruit quality and production occurred. This partly confirmed the possibility to shift crop load management to single upright. The finding of the presented studies together with the benefits coming from multileader planar training systems suggest a high potentiality of the 2D multileader training systems to increase apple production sustainability and profitability for Italian apple orchard, while easing the advent of automation in fruit production.

Big Data approaches as a support for precision livestock farming techniques

With the advent of new technologies it is increasingly easier to find data of different nature from even more accurate sensors that measure the most disparate physical quantities and with different methodologies. The collection of data thus becomes progressively important and takes the form of archiving, cataloging and online and offline consultation of information. Over time, the amount of data collected can become so relevant that it contains information that cannot be easily explored manually or with basic statistical techniques. The use of Big Data therefore becomes the object of more advanced investigation techniques, such as Machine Learning and Deep Learning. In this work some applications in the world of precision zootechnics and heat stress accused by dairy cows are described. Experimental Italian and German stables were involved for the training and testing of the Random Forest algorithm, obtaining a prediction of milk production depending on the microclimatic conditions of the previous days with satisfactory accuracy. Furthermore, in order to identify an objective method for identifying production drops, compared to the Wood model, typically used as an analytical model of the lactation curve, a Robust Statistics technique was used. Its application on some sample lactations and the results obtained allow us to be confident about the use of this method in the future.

A robotic platform for precision agriculture and applications

Agricultural techniques have been improved over the centuries to match with the growing demand of an increase in global population. Farming applications are facing new challenges to satisfy global needs and the recent technology advancements in terms of robotic platforms can be exploited. As the orchard management is one of the most challenging applications because of its tree structure and the required interaction with the environment, it was targeted also by the University of Bologna research group to provide a customized solution addressing new concept for agricultural vehicles. The result of this research has blossomed into a new lightweight tracked vehicle capable of performing autonomous navigation both in the open-filed scenario and while travelling inside orchards for what has been called in-row navigation. The mechanical design concept, together with customized software implementation has been detailed to highlight the strengths of the platform and some further improvements envisioned to improve the overall performances. Static stability testing has proved that the vehicle can withstand steep slopes scenarios. Some improvements have also been investigated to refine the estimation of the slippage that occurs during turning maneuvers and that is typical of skid-steering tracked vehicles. The software architecture has been implemented using the Robot Operating System (ROS) framework, so to exploit community available packages related to common and basic functions, such as sensor interfaces, while allowing dedicated custom implementation of the navigation algorithm developed. Real-world testing inside the university’s experimental orchards have proven the robustness and stability of the solution with more than 800 hours of fieldwork. The vehicle has also enabled a wide range of autonomous tasks such as spraying, mowing, and on-the-field data collection capabilities. The latter can be exploited to automatically estimate relevant orchard properties such as fruit counting and sizing, canopy properties estimation, and autonomous fruit harvesting with post-harvesting estimations.

Modelling, simulations and monitoring for sustainable plant and animal production systems through precision technique

Protected crop production is a modern and innovative approach to cultivating plants in a controlled environment to optimize growth, yield, and quality. This method involves using structures such as greenhouses or tunnels to create a sheltered environment. These productive solutions are characterized by a careful regulation of variables like temperature, humidity, light, and ventilation, which collectively contribute to creating an optimal microclimate for plant growth. Heating, cooling, and ventilation systems are used to maintain optimal conditions for plant growth, regardless of external weather fluctuations. Protected crop production plays a crucial role in addressing challenges posed by climate variability, population growth, and food security. Similarly, animal husbandry involves providing adequate nutrition, housing, medical care and environmental conditions to ensure animal welfare. Then, sustainability is a critical consideration in all forms of agriculture, including protected crop and animal production. Sustainability in animal production refers to the practice of producing animal products in a way that minimizes negative impacts on the environment, promotes animal welfare, and ensures the long-term viability of the industry. Then, the research activities performed during the PhD can be inserted exactly in the field of Precision Agriculture and Livestock farming. Here the focus is on the computational fluid dynamic (CFD) approach and environmental assessment applied to improve yield, resource efficiency, environmental sustainability, and cost savings. It represents a significant shift from traditional farming methods to a more technology-driven, data-driven, and environmentally conscious approach to crop and animal production. On one side, CFD is powerful and precise techniques of computer modeling and simulation of airflows and thermo-hygrometric parameters, that has been applied to optimize the growth environment of crops and the efficiency of ventilation in pig barns. On the other side, the sustainability aspect has been investigated and researched in terms of Life Cycle Assessment analyses.

Back-in-time void finder: dynamical detection of cosmic voids for precision cosmology

Cosmic voids are vast and underdense regions emerging between the elements of the cosmic web and dominating the large-scale structure of the Universe. Void number counts and density profiles have been demonstrated to provide powerful cosmological probes. Indeed, thanks to their low-density nature and they very large sizes, voids represent natural laboratories to test alternative dark energy scenarios, modifications of gravity and the presence of massive neutrinos. Despite the increasing use of cosmic voids in Cosmology, a commonly accepted definition for these objects has not yet been reached. For this reason, different void finding algorithms have been proposed during the years. Voids finder algorithms based on density or geometrical criteria are affected by intrinsic uncertainties. In recent years, new solutions have been explored to face these issues. The most interesting is based on the idea of identify void positions through the dynamics of the mass tracers, without performing any direct reconstruction of the density field. The goal of this Thesis is to provide a performing void finder algorithm based on dynamical criteria. The Back-in-time void finder (BitVF) we present use tracers as test particles and their orbits are reconstructed from their actual clustered configuration to an homogeneous and isotropic distribution, expected for the Universe early epoch. Once the displacement field is reconstructed, the density field is computed as its divergence. Consequently, void centres are identified as local minima of the field. In this Thesis work we applied the developed void finding algorithm to simulations. From the resulting void samples we computed different void statistics, comparing the results to those obtained with VIDE, the most popular void finder. BitVF proved to be able to produce a more reliable void samples than the VIDE ones. The BitVF algorithm will be a fundamental tool for precision cosmology, especially with upcoming galaxy-survey.

Spacecraft Collision Probability Calculation from Conjunction Data Message and High Precision Orbit Propagator

The increasing number of Resident Space Objects (RSOs) is a threat to spaceflight operations. Conjunction Data Messages (CDMs) are sent to satellite operators to warn for possible future collision and their probabilities. The research project described herein pushed forward an algorithm that is able to update the collision probability directly on-board starting from CDMs and the state vector of the hosting satellite which is constantly updated thanks to an onboard GNSS receiver. A large set of methods for computing the collision probability was analyzed in order to find the best ones for this application. The selected algorithm was then tested to assess and improve its performance. Finally, parts of the algorithm and external software were implemented on a Raspberry Pi 3B+ board to demonstrate the compatibility of this approach with computational resources similar to those typically available onboard modern spacecraft.

The FAMU experiment: characterization of innovative detectors for high precision spectroscopy

The incompatibility between the proton radius values measured in recent years has given rise to what is now called the proton radius puzzle. This discrepancy is nowadays without explanation. In order to find a solution to the proton radius puzzle a new experiment has been proposed. The aim of this experiment, called FAMU, is to obtain a new and more precise measure of the Zemach radius of the proton, ie the quantity that has the highest uncertainty in high precision spectroscopy. If this measurement confirmed the results obtained before 2010, the starting date of the puzzle, then the discrepancy would be caused by procedural errors or ignored corrections. Otherwise, the new value would indicate the presence of new physics still unkown.

A Highly Improved Method For Sensitive Determination Of Amitriptyline In Pharmaceutical Formulations Using An Unmodified Carbon Nanotube Electrode In The Presence Of Sulfuric Acid.

The present paper describes a novel, simple and reliable differential pulse voltammetric method for determining amitriptyline (AMT) in pharmaceutical formulations. It has been described for many authors that this antidepressant is electrochemically inactive at carbon electrodes. However, the procedure proposed herein consisted in electrochemically oxidizing AMT at an unmodified carbon nanotube paste electrode in the presence of 0.1 mol L(-1) sulfuric acid used as electrolyte. At such concentration, the acid facilitated the AMT electroxidation through one-electron transfer at 1.33 V vs. Ag/AgCl, as observed by the augmentation of peak current. Concerning optimized conditions (modulation time 5 ms, scan rate 90 mV s(-1), and pulse amplitude 120 mV) a linear calibration curve was constructed in the range of 0.0-30.0 μmol L(-1), with a correlation coefficient of 0.9991 and a limit of detection of 1.61 μmol L(-1). The procedure was successfully validated for intra- and inter-day precision and accuracy. Moreover, its feasibility was assessed through analysis of commercial pharmaceutical formulations and it has been compared to the UV-vis spectrophotometric method used as standard analytical technique recommended by the Brazilian Pharmacopoeia.

Chemical Immobilization Of Crosslinked Polymeric Ionic Liquids On Nitinol Wires Produces Highly Robust Sorbent Coatings For Solid-phase Microextraction.

Super elastic nitinol (NiTi) wires were exploited as highly robust supports for three distinct crosslinked polymeric ionic liquid (PIL)-based coatings in solid-phase microextraction (SPME). The oxidation of NiTi wires in a boiling (30%w/w) H2O2 solution and subsequent derivatization in vinyltrimethoxysilane (VTMS) allowed for vinyl moieties to be appended to the surface of the support. UV-initiated on-fiber copolymerization of the vinyl-substituted NiTi support with monocationic ionic liquid (IL) monomers and dicationic IL crosslinkers produced a crosslinked PIL-based network that was covalently attached to the NiTi wire. This alteration alleviated receding of the coating from the support, which was observed for an analogous crosslinked PIL applied on unmodified NiTi wires. A series of demanding extraction conditions, including extreme pH, pre-exposure to pure organic solvents, and high temperatures, were applied to investigate the versatility and robustness of the fibers. Acceptable precision of the model analytes was obtained for all fibers under these conditions. Method validation by examining the relative recovery of a homologous group of phthalate esters (PAEs) was performed in drip-brewed coffee (maintained at 60 °C) by direct immersion SPME. Acceptable recoveries were obtained for most PAEs in the part-per-billion level, even in this exceedingly harsh and complex matrix.

Strain Gauges's Analysis On Implant-retained Prosthesis' Cast Accuracy.

A proper cast is essential for a successful rehabilitation with implant prostheses, in order to produce better structures and induce less strain on the implants. The aim of this study was to evaluate the precision of four different mold filling techniques and verify an accurate methodology to evaluate these techniques. A total of 40 casts were obtained from a metallic matrix simulating three unit implant-retained prostheses. The molds were filled using four different techniques in four groups (n = 10): Group 1 - Single-portion filling technique; Group 2 - Two-step filling technique; Group 3 - Latex cylinder technique; Group 4 - Joining the implant analogs previously to the mold filling. A titanium framework was obtained and used as a reference to evaluate the marginal misfit and tension forces in each cast. Vertical misfit was measured with an optical microscope with an increase of 120 times following the single-screw test protocol. Strain was quantified using strain gauges. Data were analyzed using one-way ANOVA (Tukey's test) (α =0.05). The correlation between strain and vertical misfit was evaluated by Pearson test. The misfit values did not present statistical difference (P = 0.979), while the strain results showed statistical difference between Groups 3 and 4 (P = 0.027). The splinting technique was considered to be as efficient as the conventional technique. The strain gauge methodology was accurate for strain measurements and cast distortion evaluation. There was no correlation between strain and marginal misfit.