Identification of the nature of traps involved in the field cycling of Hf₀.₅Zr₀.₅O₂-based ferroelectric thin films

The discovery of ferroelectricity in hafnium oxide has revived the interest in ferroelectric memories as a viable option for low power non-volatile memories. However, due to the high coercive field of ferroelectric hafnium oxide, instabilities in the field cycling process are commonly observed and explained by the defect movement, defect generation and field induced phase transitions. In this work, the optical and transport experiments are combined with ab-initio simulations and transport modeling to validate that the defects which act as charge traps in ferroelectric active layers are oxygen vacancies. A new oxygen vacancy generation leads to a fast growth of leakage currents and a consequent degradation of the ferroelectric response in Hf₀.₅Zr₀.₅O₂ films. Two possible pathways of the Hf₀.₅Zr₀.₅O₂ ferroelectric property degradation are discussed

Particle spectrum in the modified NMSSM in the strong Yukawa coupling limit

A theoretical analysis of solutions of renormalisation group equations in the MSSM corresponding to the quasi-fixed point conditions shows that the mass of the lightest Higgs boson in this case does not exceed $94\pm 5\text{GeV}$. It means that a substantial part of the parameter space of the MSSM is practically excluded by existing experimental data from LEP II. In the NMSSM the upper bound on the lightest Higgs boson mass reaches its maximum in the strong Yukawa coupling regime, when Yukawa constants are considerably larger the gauge ones on the Grand Unification scale. In this paper a particle spectrum in a simple modification of NMSSM which leads to a self-consistent solution in the considered region of the parameter space is studied. This model allows one to get $m_h\sim 125\text{GeV}$ even for comparatively low values of $\tan\beta\ge 1.9$. For an analysis of the Higgs boson spectrum and neutralino spectrum a method for diagonalisation of mass matrices proposed formerly is used. The mass of the lightest Higgs boson in this model does not exceed $130.5\pm 3.5\text{GeV}$.Comment: 34 pages, 5 figures included, LaTeX 2

Can the Universe Create Itself?

The question of first-cause has troubled philosophers and cosmologists alike. Now that it is apparent that our universe began in a Big Bang explosion, the question of what happened before the Big Bang arises. Inflation seems like a very promising answer, but as Borde and Vilenkin have shown, the inflationary state preceding the Big Bang must have had a beginning also. Ultimately, the difficult question seems to be how to make something out of nothing. This paper explores the idea that this is the wrong question --- that that is not how the Universe got here. Instead, we explore the idea of whether there is anything in the laws of physics that would prevent the Universe from creating itself. Because spacetimes can be curved and multiply connected, general relativity allows for the possibility of closed timelike curves (CTCs). Thus, tracing backwards in time through the original inflationary state we may eventually encounter a region of CTCs giving no first-cause. This region of CTCs, may well be over by now (being bounded toward the future by a Cauchy horizon). We illustrate that such models --- with CTCs --- are not necessarily inconsistent by demonstrating self-consistent vacuums for Misner space and a multiply connected de Sitter space in which the renormalized energy-momentum tensor does not diverge as one approaches the Cauchy horizon and solves Einstein's equations. We show such a Universe can be classically stable and self-consistent if and only if the potentials are retarded, giving a natural explanation of the arrow of time. Some specific scenarios (out of many possible ones) for this type of model are described. For example: an inflationary universe gives rise to baby universes, one of which turns out to be itself. Interestingly, the laws of physics may allow the Universe to be its own mother.Comment: 48 pages, 8 figure

Artificial neural network for predictive synthesis of single-walled carbon nanotubes by aerosol CVD method

We propose to use artificial neural networks to process the experimental data and to predict the performance of the aerosol CVD synthesis of single-walled carbon nanotubes based on Boudouard reaction. We employ five key input parameters of the growth (pressures of CO, CO2 and ferrocene as well as the residence time and the growth temperature) to control the performance of produced nanotube films (yield, mean and standard deviation of the diameter distribution, and defectiveness). The prediction errors were found to be comparable with the corresponding experimental errors. We believe the proposed approach is of great interest for the synthesis of nanocarbons with tailored characteristics.Peer reviewe

Machine learning methods for aerosol synthesis of single-walled carbon nanotubes

Funding Information: The authors thank Prof. Esko I. Kauppinen and Dr. Fedor Fedorov for fruitful discussions. E.M.Kh. and T.K. acknowledge Academy of Finland (Profi 5 Project) and Finnish National Agency for Education (the EDUFI fellowship grant). D.V.K. acknowledges RSF (grant No. 20-73-10256; ANN, optimal dataset). D.V.K and A.G.N. acknowledge Council on grants of RF (grant No НШ-1330.2022.1.3). Publisher Copyright: © 2022 The AuthorsThis work is devoted to the strategy towards the optimal development of multiparametric process of single-walled carbon nanotube (SWCNT) synthesis. Here, we examine the implementation of machine learning techniques and discuss features of the optimal dataset size and density for aerosol chemical vapor deposition method with a complex carbon source. We employ the dataset of 369 points, comprising synthesis parameters (catalyst amount, temperature, feed of carbon sources) and corresponding carbon nanotube characteristics (yield, quality, structure, optoelectrical figure of merit). Assessing the performance of six machine learning methods on the dataset, we demonstrate Artificial Neural Network to be the most suitable approach to predict the outcome of synthesis processes. We show that even a dataset of 250 points with the inhomogeneous distribution of input parameters is enough to reach an acceptable performance of the Artificial Neural Network, wherein the error is most likely to arise from experimental inaccuracy and hidden uncontrolled variables. We believe our work will contribute to the selection of an appropriate regression algorithm for the controlled carbon nanotube synthesis and further development of an autonomous synthesis system for an “on-demand” SWCNT production.Peer reviewe

A spark discharge generator for scalable aerosol CVD synthesis of single-walled carbon nanotubes with tailored characteristics

We have designed and built an exhaust-free spark discharge generator for robust aerosol CVD synthesis of single-walled carbon nanotubes. The systematic study has shown the generator to provide a facile and repeatable route to precisely control the size of the catalyst particle and, therefore, carbon nanotube growth. Using a comprehensive set of methods (the analysis of differential mobility of the aerosol particles, optical spectroscopy, scanning and transmission electron microscopy, Raman spectroscopy, and atomic force microscopy) we have revealed the relation between the defectiveness, length, diameter distribution of carbon nanotubes and specific features of a generator such as electrode characteristics (breakdown voltage, composition, and current) as well as the nature of the surrounding media (carrier gas nature, flow rate). The design used has resulted in separation of the nanoparticle formation and carbon nanotube nucleation processes. This provides a mutual independence of the growth parameters and the diameter distribution of the single-walled carbon nanotubes enhancing the scalability of the process. For instance, the breakdown voltage has been shown to have nearly zero effect on diameter and length distribution of carbon nanotubes produced while strictly governing the yield. We focus here on producing specifically short carbon nanotubes (l < 500 nm) of pronounced defectiveness for drug delivery and transistor applications.Peer reviewe

Fine-tuning of spark-discharge aerosol CVD reactor for single-walled carbon nanotube growth

We report a development of recently designed apparatus equipped with a spark discharge generator of catalytic nanoparticles for robust aerosol CVD synthesis of single-walled carbon nanotubes. We achieve a profound control over the diameter distribution and the defectiveness of carbon nanotubes produced. By providing a justified comparison of the apparatus with the most abundant aerosol CVD reactor utilizing ferrocene as a catalyst precursor, we reveal the role of the activation procedure: while spark-discharge generator provides aerosol of nanoparticles (ex situ route), the ferrocene vapor decomposes in the nanotube growth zone providing an in situ formation of the catalyst. With other parameters being equal, we reveal the differences in the nanotube growth (diameter and length distribution, yield, defectiveness) employing a comprehensive set of methods (the analysis of differential mobility of the aerosol particles, optical spectroscopy, scanning and transmission electron microscopy, Raman spectroscopy, and atomic force microscopy). We show the ex situ activation in the spark discharge reactor to provide a lower utilization degree of the nanoparticles due to over-coagulation. However, the same method provides an independence of the key performance parameters of the nanotubes opening a room for scaling the apparatus.Peer reviewe