ELECTROLYTIC EFFECT ON GROWTH OF GRAPHENE QUANTUM DOTS VIA ELECTROCHEMICAL PROCESS

Quantum dots (QDs) are materials grown in confined dimension also known as 0D materials. QDs can be synthesized in many shapes and forms through various methods making the materials extremely versatile and can be fine-tuned for appropriate applications. Among the potentially scalable methods, Electrochemical process is considered as one of the top-down approaches with the highest potential for scalability and easy-to-process methodology while electrolyte and pH level can play various important roles on the final product. In this work, we grew and studied the effect of electrolytic solution in the growth of graphene quantum dots (GQDs) in colloidal forms using cheap graphite as precursor in KCl and NaOH as electrolytes in various concentrations. It can be inferred from our results that when KCl and NaOH were used in combination with citric acid, the optoelectrical properties and hydrodynamic properties of the resulting growth can be fine-tuned to match the required applications. [Formula: see text] electronics excitation was identified with small tunability of 487–500[Formula: see text]nm wavelength while the hydrodynamic size varied from 80–140[Formula: see text]nm with resulting pH range from 3.0–9.5 adjustable to appropriate applications, while the TEM results showed physical particle size of 1.7–3.7[Formula: see text]nm.

Interpolation Methods Applied on Biomolecules and Condensed Matter Brownian Motion

Biophysical and condensed matter systems connection is of great importance nowadays due to the need for a new approach in microelectronic biodevices, biocomputers or biochips advanced development. Considering that the living and nonliving systems’ submicroparticles are identical, we can establish the biunivocally correspondent relation between these two particle systems, as a biomimetic correlation based on Brownian motion fractal nature similarities, as the integrative property. In our research, we used the experimental results of bacterial motion under the influence of energetic impulses, like music, and also some biomolecule motion data. Our goal is to define the relation between biophysical and physical particle systems, by introducing mathematical analytical forms and applying Brownian motion fractal nature characterization and fractal interpolation. This work is an advanced research in the field of new solutions for high-level microelectronic integrations, which include submicrobiosystems like part of even organic microelectronic considerations, together with some physical systems of particles in solid-state solutions as a nonorganic part. Our research is based on Brownian motion minimal joint properties within the integrated biophysical systems in the wholeness of nature.

snowScatt 1.0: consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh–Gans approximation

More detailed observational capabilities in the microwave (MW) range and advancements in the details of microphysical schemes for ice and snow demand increasing complexity to be included in scattering databases. The majority of existing databases rely on the discrete dipole approximation (DDA) whose high computational costs limit either the variety of particle types or the range of parameters included, such as frequency, temperature, and particle size. The snowScatt tool is innovative in that it provides consistent microphysical and scattering properties of an ensemble of 50 000 snowflake aggregates generated with different physical particle models. Many diverse snowflake types, including rimed particles and aggregates of different monomer composition, are accounted for. The scattering formulation adopted by snowScatt is based on the self-similar Rayleigh–Gans approximation (SSRGA), which is capable of modeling the scattering properties of large ensembles of particles. Previous comparisons of SSRGA and DDA are extended in this study by including unrimed and rimed aggregates up to centimeter sizes and frequencies up to the sub-millimeter spectrum. The results generally reveal the wide applicability of the SSRGA method for active and passive MW applications. Unlike DDA databases, the set of SSRGA parameters can be used to infer scattering properties at any frequency and refractive index; snowScatt also provides tools to derive the SSRGA parameters for new sets of particle structures, which can be easily included in the library. The flexibility of the snowScatt tool with respect to applications that require continuously changing definitions of snow properties is demonstrated in a forward simulation example based on the output of the predicted particle properties (P3) scheme. The snowScatt tool provides the same level of flexibility as commonly used T-matrix solutions, while the computed scattering properties reach the level of accuracy of detailed discrete dipole approximation calculations.

Phase space sampling and inference from weighted events with autoregressive flows

We explore the use of autoregressive flows, a type of generative model with tractable likelihood, as a means of efficient generation of physical particle collider events. The usual maximum likelihood loss function is supplemented by an event weight, allowing for inference from event samples with variable, and even negative event weights. To illustrate the efficacy of the model, we perform experiments with leading-order top pair production events at an electron collider with importance sampling weights, and with next-to-leading-order top pair production events at the LHC that involve negative weights.

Holophyly and associated concepts if the unknown is unclassifiable

In natural sciences, the key criterion for proving the existence of an object (like a physical particle of a previously unknown kind, an atom of a previously unknown element or an organism of a previously unknown species) is its observation and/or observation of traces of the existence of this object (radiation, remains of vital activity etc.). Only objects that meet this criterion can be classified (e.g. introduced in the periodic table of elements or described as a species). Single unknown organisms or species can not enter the classification. Despite this, the current system of phylogenetic terms (holo-/monophyly, paraphyly, and polyphyly as they are currently defined) is not adapted to the separation of known and unknown organisms (as well as populations, species, etc.) including ancestral ones. There are longstanding confusion and controversy regarding these “phyletic states”. There seem only two ways in such a situation. The first way is to directly include unknown ancestors in taxa somehow, describe species for them and unavoidably to introduce at least one paraphyletic subtaxon during dividing each taxon. The second way is do not include unknown ancestors in taxa directly and amend the system of concepts and terms. Here the second way was followed and the possible definitions of the main phylogenetic concepts for the views of dealing only with known group members were proposed. Inability to provide a concise definition of holophyly using the existing terms indicates the lack of more basic concepts. These concepts were also proposed here and holophyly was defined using them near the end of the paper. The intersection of four basic “phyly” (enophyly, merophyly, kollitophyly, and schizophyly) results in the unambiguous triad of holophyly, paraphyly, and schizophyly. The definitions of the terms in this triad are believed to be unambiguous unlike the widespread definitions of holo-(mono-), para- and “polyphyly”. Here, many terms were defined using others in order not to make the definitions too cumbersome. Nevertheless, the “primary phyly” seem not less useful in phylogenetic discussions than the phyly of the triad. The same is true for the terms inprestor, rendestor, ancessure, drade and skade as well as for the more precisely defined term clade. The first two terms seem to be necessary and important regardless of the views on the classification of unknown organisms.

A derivation of the Liouville equation for hard particle dynamics with non-conservative interactions

The Liouville equation is of fundamental importance in the derivation of continuum models for physical systems which are approximated by interacting particles. However, when particles undergo instantaneous interactions such as collisions, the derivation of the Liouville equation must be adapted to exclude non-physical particle positions, and include the effect of instantaneous interactions. We present the weak formulation of the Liouville equation for interacting particles with general particle dynamics and interactions, and discuss the results using two examples.

Origin of Probability in Quantum Mechanics and the Physical Interpretation of the Wave Function

The theoretical calculation of quantum mechanics has been accurately verified by experiments, but Copenhagen interpretation with probability is still controversial. To find the source of the probability, we revised the definition of the energy quantum and reconstructed the wave function of the physical particle. Here, we found that the energy quantum ê is 6.62606896 ×10-34J instead of hν as proposed by Planck. Additionally, the value of the quality quantum ô is 7.372496 × 10-51 kg. This discontinuity of energy leads to a periodic non-uniform spatial distribution of the particles that transmit energy. A quantum objective system (QOS) consists of many physical particles whose wave function is the superposition of the wave functions of all physical particles. The probability of quantum mechanics originates from the distribution rate of the particles in a state in the QOS per unit volume at time t and near position r. Based on the revision of the energy quantum assumption and the origin of the probability, we proposed new certainty and uncertainty relationships, explained the physical mechanism of wave-function collapse and the quantum tunnelling effect, derived the quantum theoretical expression of double-slit and single-slit experiments.

snowScatt 1.0: Consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh-Gans Approximation

More detailed observational capabilities in the microwave (MW) and advancements in the details of microphysical schemes for ice and snow demand increasing complexity to be included in scattering databases. The majority of existing databases rely on the Discrete Dipole Approximation (DDA) whose high computational costs limit either the variety of particle types or the range of parameters included, such as frequency, temperature, or particle size. snowScatt is an innovative tool that provides the consistent microphysical and scattering properties of an ensemble of 50 thousand snowflake aggregates generated with different physical particle models. Many diverse snowflake types, including rimed particles and aggregates of different monomer composition, are accounted for. The scattering formulation adopted by snowScatt is based on the Self-Similar Rayleigh-Gans Approximation (SSRGA) which is capable of modeling the scattering properties of large ensembles of particles. Previous comparisons of SSRGA and DDA are extended in this study by including unrimed and rimed aggregates up to cm-sizes and frequencies up to the sub-mm spectrum. The results reveal in general the wide applicability of the SSRGA method for active and passive MW applications. Unlike DDA databases, the set of SSRGA coefficients can be used to infer the scattering properties at any frequency and refractive index. snowScatt also provides tools to derive the SSRGA coefficients for new sets of particle structures which can be easily included in the library. The flexibility of the snowScatt tool with respect to applications that require continuously changing definitions of snow properties is demonstrated in a forward simulation example based on the output of the Predicted Particle Properties (P3) scheme. snowScatt provides the same level of flexibility as commonly used T-matrix solutions while the computed scattering properties reach the level of accuracy of detailed Discrete Dipole Approximation calculations.

Origin of Probability in Quantum Mechanics and the Physical Interpretation of the Wave Function

The theoretical calculation of quantum mechanics has been accurately verified by experiments, but Copenhagen interpretation with probability is still controversial. To find the source of the probability, we revised the definition of the energy quantum and reconstructed the wave function of the physical particle. Here, we found that the energy quantum ê is 6.62606896 ×10-34J instead of hν as proposed by Planck. Additionally, the value of the quality quantum ô is 7.372496 × 10-51 kg. This discontinuity of energy leads to a periodic non-uniform spatial distribution of the particles that transmit energy. A quantum objective system (QOS) consists of many physical particles whose wave function is the superposition of the wave functions of all physical particles. The probability of quantum mechanics originates from the distribution rate of physical particles in a state in the QOS per unit volume at time t and near position r. Based on the revision of the energy quantum assumption and the origin of the probability, we proposed new certainty and uncertainty relationships, explained the physical mechanism of wave-function collapse and the quantum tunnelling effect, derived the quantum theoretical expression of double-slit and single-slit experiments.