Physics Approach Research Articles

Direct and Indirect Effects for Radiosensitization of Gold Nanoparticles in Proton Therapy.

The radiosensitization characteristics of gold nanoparticles (GNPs) have been investigated in a single cell irradiated with monoenergetic beams of protons of various energies using TOPAS-nBio, an advanced toolkit of TOPAS. Both direct and indirect effects against single-strand breaks (SSBs) are investigated and their double-strand breaks (DSBs) have been calculated. A single spherical cell interaction with a detailed DNA structure has been modeled and simulated under different conditions such as particle sizes and concentrations of GNPs, their biodistributions and associated proton energies. The physical interaction among protons, suspension water and GNPs has been simulated using a dual physics approach, while the interaction between water radiolysis and OH radicals was considered in the chemical process to save computational time. The present simulations involve irradiating the cell geometry with a dose of 1 Gy. The range of DSBs (Gy-1 Gbp-1) obtained was 2.1 ± 0.09 to 21.74 ± 0.4 for all GNPs of sizes 6-50 nm the proton energies in the range of 5-50 MeV. Regardless of proton energy and GNP size, the calculations showed that the contribution of indirect and hybrid DSBs remains higher in all simulation types than that of direct DSBs. New simulation outcomes of the indirect DSBs illustrate a percentage increase, while we cannot get an increase in the direct and hybrid DSBs in most cases when compared with no GNPs cases. The indirect DSBs provide the highest enhancement factor of 1.89 at 30 nm GNPs in size for 30 MeV protons energy, and the direct and hybrid DSBs indicate a slight increase in enhancement. The work indicates that the use of GNPs increased indirect DNA DSBs, while hybrid DSBs show only a slight increase in enhancement, and no enhancement is shown in direct DNA DSBs. It is significant to consider other mechanisms such as DNA damage repair when investigating DNA damage.

Birge ratio method for modeling dark uncertainty in multivariate meta-analyses and inter-laboratory studies

In the paper, we introduce a new approach for combining multivariate measurements obtained in individual studies. The procedure extends the Birge ratio method, a commonly used approach in physics in the univariate case, such as for the determination of physical constants, to multivariate observations. Statistical inference procedures are derived for the parameters of the multivariate location-scale model, which is related to the multivariate Birge ratio method. The new approach provides an alternative to the methods based on the application of the multivariate random effects model, which is commonly used for multivariate meta-analyses and inter-laboratory comparisons. In two empirical illustrations, we show that the introduced multivariate Birge ratio approach yields confidence intervals for the elements of the overall mean vector that are considerably narrower than those obtained by the methods derived under the multivariate random effects model.

Machine learning for locally periodic structure transmission modelling

This research aims to obtain an analytical transmission model for locally periodic structures with the approach of data-driven physics. So far, this task has been done mainly numerically for non-trivial geometries. From a dataset of Bloch phases generated for given frequency band and structure geometry parameters, it is possible to learn equations relating dispersion relation to axis-symmetric geometry. The dataset is transformed into a lower-dimensional space by applying Principal Component Analysis (PCA) to reduce the complexity of the problem. In the newly obtained coordinate system, the lower-dimensional patterns are extracted via symbolic regression. The resulting model is interpretable in terms of underlying physics and can be used, e.g., to propose an optimized design for a desired band gap width. Note that this has been so far possible only with numerical optimization repeatedly going back and forth from geometry to the dispersion relation, and hence, it significantly contributes to the overall readability of the system features.

Analysis of Student Problem-Solving Skills on Static Fluid Topics

Abstract Finding high school students’ Problem-Solving Skills (PSS) on static fluid is the aim of this study. A sample of 125 students from a high school in East Java, Indonesia, was employed in this quantitative study employing a survey methodology. The Problem-Solving Skills Test (Cronbarch’s Alpha reliability of 0.66), which consists of six essay questions with a scoring range of 1 to 5, was used to collect the study data. The research data was analyzed using descriptive statistics. The average PSS of the students according to the research results was 20.54 with the conversion of the PSS Test score to a scale of 0-100, placing them in the beginner category. According to the PSS indicators, the rank of students from highest to lowest level is Useful Description, Specific Application of Physics, Mathematical Procedures, Physics Approach, and Logical Progression. Students find that Archimedes’ Law, Pascal’s Law, and Hydrostatic Pressure are the most difficult static fluid subtopic to go through. It is highly recommended that learning methods that can support students’ problem-solving skills, such as project-based learning in conjunction with Science, Technology, Engineering, Art, and Mathematics (STEAM), provide them with the skills to use logic in their thinking when solving problems.

Cationic dye remediation in water treatment with Lizardite–Rice Husk composite: A statistical physics approach

This study presents the development of a novel composite adsorbent, Lizardite-Rice Husk Composite (LRHC), synthesized from lizardite, a mineral derived from chromite ore waste, and rice husk, an agricultural byproduct. The primary objective was to evaluate the efficiency of LRHC in the adsorption of cationic dyes, Malachite Green (MG) and Methylene Blue (MB), from aqueous solutions. Systematic investigations were conducted to assess the influence of adsorbent mass, initial dye concentration, stirring speed, and contact time on adsorption performance. The results revealed that LRHC exhibited optimal adsorption capacities at pH values above 5, with MB and MG adsorption capacities reaching 309.75 mg/g and 51.43 mg/g, respectively. Adsorption equilibrium for MB was achieved within 30 min, indicating rapid dye uptake. Isotherm analysis demonstrated that the Temkin model best described MB adsorption, while the Freundlich model was more suitable for MG, with favorable Langmuir constants. Kinetic studies confirmed that the adsorption followed a second-order model, suggesting chemisorption as the rate-determining step. Intraparticle diffusion and mass transfer were identified as significant contributors to the adsorption process. Thermodynamic studies indicated that MB adsorption was spontaneous (ΔG° = −4.69 kJ/mol for the concentration of 50 mg/L at 298 K) and that MG adsorption was non-spontaneous (ΔG° = 1.52 kJ/mol for the concentration of 50 mg/L at 298 K), with spontaneity increasing at higher initial concentrations. Statistical physics modeling, particularly the monolayer model, provided detailed insights into the adsorption mechanisms and geometry. Furthermore, LRHC demonstrated excellent reusability, maintaining over 80% of its initial adsorption capacity after four regeneration cycles via a heterogeneous Fenton-like reaction. The combination of easy availability, cost-effectiveness, and environmental friendliness makes LRHC a superior adsorbent for the removal of cationic dyes compared to conventional alternatives. This research contributes novel insights into the design and application of composite adsorbents, offering a sustainable solution for water treatment and addressing significant environmental challenges.

The Radiosurgery Society Working Groups on GRID, LATTICE, Microbeam, and FLASH Radiotherapies: 2022 to 2023 Advancements Symposium and Subsequent Progress Made

PurposeSince the inaugural workshop “Understanding High-Dose, Ultra-High Dose Rate and Spatially Fractionated Radiotherapy.” hosted by the NCI and sponsored by the Radiosurgery Society (RSS), growing collaborations and investigations have ensued among experts, practitioners, and researchers. The RSS GRID, Lattice, Microbeam & FLASH (GLMF) Working Groups were formed as a framework for these efforts and have focused on advancing the understanding of the biology, technical/physical parameters, trial design, and clinical practice of these new radiation therapy modalities. Methods and MaterialsIn view of the steadily increasing clinical interest in SFRT and FLASH, a full-day symposium entitled “Advancements in GRID, LATTICE, and FLASH Radiotherapy Symposium” was established in 2022 that immediately preceded the RSS scientific meeting. This well-attended symposium focused on clinical, technical, and physics approaches for SFRT, while closely examining relevant radiobiological underpinnings. Practical clinical trial development was a highlighted discussion. An additional section reviewed proton therapy and other particle-based techniques for the delivery of GRID and Lattice therapy. A treatment planning and delivery tutorial for GRID, Lattice, and proton GRID/Lattice was directed towards the real-world considerations for the development of new clinical GRID or LATTICE programs. An overall similar approach was applied to the discussion of FLASH. This report summarizes the content of the first GLMF Symposium and related work of the RSS GLMF Working Groups in the field of heterogeneous and ultra-high dose rate irradiation, over approximately 2 years. ResultsThe GLMF Working Groups have continued to expand in membership and attendance, and several resultant trial concepts, research efforts, academic discussions, and peer-reviewed publications have followed as the number of institutions and practitioners utilizing SFRT and FLASH continues to grow. ConclusionsThe GLFM Working Groups and the RSS continue to demonstrate excellent progress in proliferating use of and improving understanding of SFRT and ultra-high dose rate radiotherapy techniques.

Effort to Optimize Learning Physics at Integrated Islamic High School via a Physics based Ethnoscience Approach

The aim of community service program is to enhance the educational experience at the integrated Islamic high school (SMA IT Khairu Ummah) Rejang Lebong district by employing an ethnoscience approach. The service program is implemented in SMA IT Khairu Ummah to address challenges posed by inadequate learning facilities and infrastructure, particularly in physics education, which may impede the teaching and learning process. The implementation of community service initiatives in 2024 comprises four phases. The first phase encompasses observational efforts within schools to acquire a comprehensive picture of the educational environment. The second phase involves the socialization of service activities and coordination with school principal and educators, particularly those teaching physics. The third phase entailed instructing educators on the development of ethnoscience-focused educational resources. The last phase entails regular assessment and guidance involving two Mahasiswa Kampus Merdeka Belajar program and five physics lecturers to guarantee that the community service program positively influences the learning process. The findings indicate that the training positively enhances teacher competencies by implementing ethnoscience education that leverages the local community's cultural and traditional diversity, even amidst constraints of limited facilities and infrastructure. Physics teacher and students of SMA IT Khairu Ummah SMA IT have implemented an ethnoscience-based physics approach that is effective in enhancing students' comprehension of scientific processes and their acquisition of related skills.

Consensus decision making on a complete graph: complex behaviour from simple assumptions

In this paper we investigate a model of consensus decision making [Hartnett A. T., et al., Phys. Rev. Lett., 2016, 116, 038701] following a statistical physics approach presented in [Sarkanych P., et al., Phys. Biol., 2023, 20, 045005]. Within this approach, the temperature serves as a measure of fluctuations, not considered before in the original model. Here, we discuss the model on a complete graph. The main goal of this paper is to show that an analytical description may lead to a very rich phase behaviour, which is usually not expected for a complete graph. However, the variety of individual agent (spin) features - their inhomogeneity and bias strength - taken into account by the model leads to rather non-trivial collective effects. We show that the latter may emerge in a form of continuous or abrupt phase transitions sometimes accompanied by re-entrant and order-parameter flipping behaviour. In turn, this may lead to appealing interpretations in terms of social decision making. We support analytical predictions by numerical simulation. Moreover, while analytical calculations are performed within an equilibrium statistical physics formalism, the numerical simulations add yet another dynamical feature - local non-linearity or conformity of the individual to the opinion of its surroundings. This feature appears to have a strong impact both on the way in which an equilibrium state is approached as well as on its characteristics.

Collision of liquid drops: bounce or merge?

Whether colliding drops will merge with or bounce off each other is critical to numerous processes, and the physics involved is notoriously complex. In particular, experiments show that both sufficiently slow and fast head-on drop collisions lead to merging, but that there is often an intermediate regime in which bouncing is observed; these transitions in behaviour were recently discovered to be surprisingly sensitive to the radius of the drops and the ambient gas pressure. We show here that these transitions between bouncing and merging are governed by nanoscale phenomena; namely, gas-kinetic and disjoining pressure effects. To capture these crucial effects, a novel, open-source computational model is developed for the simulation of colliding drops. The model uses a hybrid approach, based on solving the Navier–Stokes equations in the drop with a lubrication approach for the unconventional physics of the gas film. Our simulations show remarkably good agreement with experiments of head-on collisions and also provide new experimentally verifiable predictions.

Plant-based marbled salami analogs: Emulsion-loaded microgels embedded within protein-polysaccharide hydrogel matrices

The inherent molecular differences between plant and animal proteins make it challenging to accurately simulate the optical and mechanical properties of real meat products using plant-derived ingredients. Soft matter physics approaches are therefore being employed to direct the assembly of plant proteins, polysaccharides, and lipids into meat-like structures. The main focus of the current study was to use soft matter physics approaches to create plant-based analogs of marbled meat products, such as salami, chorizo, or pepperoni. These products have whitish fatty regions embedded within reddish/brown lean regions. In this study, we mimicked the fatty regions in salami using emulsion-loaded alginate beads and the lean regions using composite hydrogels assembled from potato protein and gellan gum. Initially, the textural attributes of the plant-based lean regions were optimized by varying potato protein type (low or high isoelectric point) and concentration. As expected, the mechanical strength of the lean region analogs increased with increasing protein content and depended on protein type. Introducing alginate beads into the salami analogs had little impact on their textural attributes when measured under compression conditions but decreased their stiffness and fracture stress when measured under tensile conditions. In particular, introducing either small or large beads reduced the stiffness and breaking stress of the salami analogs, which was attributed to the introduction of weak points in the composite hydrogel. Finally, we showed that the appearance and textural attributes of real salami could be mimicked in plant-based salami by optimizing its composition and structure. This research provides valuable insights into methods of better simulating the properties of marbled meat products, like sausages and cold-cut meat products, thereby creating a more sustainable food supply.

The phase transformation of the electron forms an atomic capacitor

Reinterpretation of existing experimental results suggests that the electron goes through a phase transformation in the vicinity of the nucleus and forms a nonrevolving surface charge electron shell from point charge and vice versa. Experimental results also strongly suggest that the laws of classical physics are valid at the atomic scale. The static, nonrevolving surface charge electron shell around the nucleus is a capacitor. Following a classical physics approach, the energy stored in this atomic capacitor is calculated for the hydrogen atom. The stored energy in the formed atomic capacitor agrees reasonably well with the rest energy of the electron. This agreement is in line with the predicted phase transformation of the electron and shows that the transformation from point to surface charge and vice versa is energetically feasible.

Digital twins for rapid in-situ qualification of part quality in laser powder bed fusion additive manufacturing

This work concerns the laser powder bed fusion (LPBF) additive manufacturing process. Currently, LPBF parts are inspected post-process using such techniques as X-ray computed tomography, optical and scanning electron microscopy, among others. This empirical build-and-test approach for qualification of part quality is prohibitively expensive and cumbersome. To enable rapid and accurate in-situ qualification of LPBF part quality, in this work, we developed a physics and data-integrated digital twin approach. To demonstrate the approach, Inconel 718 parts of various shapes were manufactured under differing LPBF processing conditions. The process was continuously monitored using in-situ thermal and optical tomography imaging cameras. The part-scale thermal history was predicted using an experimentally validated computational thermal simulation. The simulation-derived thermal history and sensor signatures were used as inputs to a k-nearest neighbor machine learning model. The machine learning model was trained with ground truth porosity and microstructure data obtained from post-process characterization. The approach predicted the onset of porosity, meltpool depth, grain size, and microhardness with an accuracy exceeding 90 % (R2). This work thus takes a critical step towards realizing an in-situ Born Qualified part quality assessment paradigm in LPBF.

Microscopic and macroscopic analysis of hexavalent chromium adsorption on polypyrrole-polyaniline@rice husk ash adsorbent using statistical physics modeling

This paper contributed with new findings to understand and characterize a heavy metal adsorption on a composite adsorbent. The synthesized polypyrrole–polyaniline@rice husk ash (PPY–PANI@RHA) was prepared and used as an adsorbent for the removal of hexavalent chromium Cr(VI). The adsorption isotherms of Cr(VI) ions on PPY–PANI@RHA were experimentally determined at pH 2, and at different adsorption temperatures (293, 303, and 313 K). Multi-layer model developed using statistical physics formalism was applied to theoretically analyze and characterize the different interactions and ion exchanges during the adsorption process for the elimination of this toxic metal from aqueous solutions, and to attribute new physicochemical interpretation of the process of adsorption. The physicochemical structures and properties of the synthesized PPY–PANI@RHA were characterized via Fourier transform infrared spectroscopy (FTIR). Fitting findings showed that the mechanism of adsorption of Cr(VI) on PPY–PANI@RHA was a multi-ionic mechanism, where one binding site may be occupied by one and two ions. It may also be noticed that the temperature augmentation generated the activation of more functional groups of the composite adsorbent, facilitating the interactions of metal ions with the binding sites and the access to smaller pore. The energetic characterization suggested that the mechanism of adsorption of the investigated systems was exothermic and Cr(VI) ions were physisorbed on PPY-PANI@RHA surface via electrostatic interaction, reduction of Cr(VI) to Cr(III), hydrogen bonding, and ion exchange. Overall, the utilization of the theory of statistical physics provided fruitful and profounder analysis of the adsorption mechanism. The estimation of the pore size distribution (PSD) of the polypyrrole-polyaniline@rice husk ash using the statistical physics approach was considered stereographic characterization of the adsorbent (here PPY–PANI@RHA was globally a meso-porous adsorbent). Lastly, the mechanism of Cr(VI) removal from wastewater using PPY-PANI@RHA as adsorbent was macroscopically investigated via the estimation of three thermodynamic functions.

Analytic soliton solutions to the shallow water dispersive long gravity wave equations: the first integral approach in nonlinear physics

In this article, we investigate the (2+1)-dimensional dispersive long water wave equation and the (1+1)-dimensional Phi-four equation, which describe the behavior of long gravity waves with small amplitudes, long wave propagation in oceans and seas, coastal structures and harbor design, effects of wave motion on sediment transport, quantum field theory, phase transitions of matter, ferromagnetic systems, liquid-gas transitions, and the structure of optical solitons. We use the first integral technique and obtain new and generic solutions for the models under consideration. By setting definite values for the associated parameters, various types of richly structured solitons are generated. The solitons include kink, flat kink, bell-shaped, anti-bell-shaped, and singular kink formations. These solutions allow for a profound understanding of the behavior and properties of the phenomena, offering new insights and potential applications in the associated field. The first integral technique is simpler, directly integrates the models, and the solutions offer clear insights into the underlying phenomena without requiring intermediate steps, making it widely applicable to various other models, including nonlinear equations and those that are challenging to solve using other standard techniques.

Statistics of earthquakes based on the extended LGGR model

Earthquake and avalanche statistics show a magnitude distribution (Gutenberg-Richter) and a distribution of consecutive times (Omori). In order to describe such phenomena within a statistical physics approach we generalize our Local Growth Global Reset (LGGR) model for resets to arbitrary lower states of the unobserved background variable. This variable is the accumulated stress for quakes, and the quakes themselves are the jumps between two such values. In a given class of transition rates between states with different stress values an analytic determination of the stationary PDF is possible. We utilize these findings to real-world data from various earthquakes.

Multiple Representations in Physics Learning: A Bibliometric Analysis

The application of multiple representation approach in physics learning has been adopted by several researchers, especially to improve the ability and achieve effective learning. The use of multiple representation approach in physics learning over the past few years has provided good results on student learning outcomes, including being able to improve and develop abstract physics concepts, scientific complex skills, metacognition skills, and problem solving. This research is the result of a review based on bibliometric analysis of multiple representations in physics learning. Data was obtained based on Scopus sources from 2013 to 2023, then obtained data as many as 121 articles which then the data was processed using RStudio and VOSViewer. Based on the results of the analysis using Rstudio and VOSViewer, it also displays other information such as year, country, author, institution, journal, co-word analysis, co-occurrence network, and visual density on occurrence. The results of this study provide a framework of the current trends of multiple representations in physics learning both in the present and some indicators that can be used as opportunities for future research.

Exploring Effective Teaching Approaches in Physics: Insights from Khan-Charbagh District High Schools

Exploring Effective Teaching Approaches in Physics: Insights from Khan-Charbagh District High Schools

In-silico design of Metal oxide-Biochar composites for enhanced dibenzothiophene adsorption: DFT and statistical physics approach

This study proposes an efficient in-silico adsorbent material selection strategy for clean fuel combustion by leveraging Density Functional Theory (DFT) calculated reactivity parameters to optimize material configurations for enhanced dibenzothiophene (DBT) adsorption from model fuel oil (n-octane). A DFT screening identified TiO2 as the optimal material for DBT adsorption from biochar and four metal oxide (MOx) based on calculated adsorption energies (Eads). Further DFT optimization identified a 10 % TiO2 composition with biochar (TBC10) as the optimal material. This composite exhibited the strongest DBT interaction (−370.3 kcal mol−1) and a remarkably short sulfur-titanium bond (2.64 Å), indicative of an ideal adsorption geometry. Notably, TBC10 features a unique composite structure: TiO2 connected to BC via van der Waals forces, while DBT directly interacts with AC through π-π stacking and covalent sulfur-titanium bonds. To validate theoretical predictions, the designed composites were synthesized and experimentally evaluated. The excellent alignment between experimental adsorption performance and DFT-calculated adsorption energies corroborated TBC10′s superior DBT adsorption capacity. Employing a systematic optimization process, the most effective parameters for TBC10′s DBT removal from a 150 mL solution containing an initial DBT concentration of 45 mg L-1 were established as: a 30 min contact time, an adsorbent dosage of 13 mg, and a temperature of 25 °C. Under these conditions, TBC10 achieved a remarkable removal efficiency (RRDBT) of 99.82 % and a maximum DBT uptake capacity (qDBT) of 31.1 mg g−1. Kinetic and statistical physics modeling revealed a multi-molecular adsorption process with distinct binding sites, characterized by spontaneous endothermic interactions and involving both physical and chemical mechanisms. The in-silico methodology for adsorbent design reduces experimentation time, cost and identifies optimal candidates for DBT removal, enhancing fuel desulfurization and promoting sustainable combustion. This novel in-silico design paradigm holds immense potential for the development of next-generation adsorbents for various environmental remediation and industrial separation processes.

Exploration of High School Students' Problem-Solving Ability Based on Gender in Fluid Material

This research explores high school students' problem-solving abilities based on gender in a static and dynamic fluid material. The type of research is quantitative descriptive research design. The population of this research was class XII students at one of the state schools in Malang, East Java. The sampling technique was purposive sampling, which was done by selecting students taught by the same teacher. The selected sample consisted of 115 students, 34 males and 81 females. The data in this study was collected by giving a test, where the test instrument used was seven essay questions on fluid material, which had a reliability coefficient of 0.70 (high). The data obtained was then analyzed using descriptive statistics, t-test, and the ANOVA test. The research results show differences in problem-solving ability between male and female students, where female students have higher problem-solving ability than male students in all problem-solving processes. The physics approach is the highest process mastered by students, while the mathematical procedure is the lowest. A physics problem-solving process is still in the low category, indicating that efforts are needed to improve students' problem-solving ability.

An integrated approach of petrophysical analysis and rock physics modeling to distinguish the Upper Cretaceous sandstone heterogeneity in the Muglad rift basin of Sudan

An integrated approach of petrophysical analysis and rock physics modeling to distinguish the Upper Cretaceous sandstone heterogeneity in the Muglad rift basin of Sudan