Time management is very important and it may actually affect individual’s overall performance and achievements. Students nowadays always commented that they do not have enough time to complete all the tasks assigned to them. In addition, a university environment’s flexibility and freedom can derail students who have not mastered time management skills. Therefore, the aim of this study is to determine the relationship between the time management and academic achievement of the students. The factor analysis result showed three main factors associated with time management which can be classified as time planning, time attitudes and time wasting. The result also indicated that gender and races of students show no significant differences in time management behaviours. While year of study and faculty of students reveal the significant differences in the time management behaviours. Meanwhile, all the time management behaviours are significantly positively related to academic achievement of students although the relationship is weak. Time planning is the most significant correlated predictor.
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- The following article is Open accessThe Impact of Time Management on Students’ Academic Achievement
S N A M Razali et al 2018 J. Phys.: Conf. Ser. 995 012042
- The following article is Open accessAn Overview of Overfitting and its Solutions
Xue Ying 2019 J. Phys.: Conf. Ser. 1168 022022
View article, An Overview of Overfitting and its SolutionsPDF, An Overview of Overfitting and its SolutionsOverfitting is a fundamental issue in supervised machine learning which prevents us from perfectly generalizing the models to well fit observed data on training data, as well as unseen data on testing set. Because of the presence of noise, the limited size of training set, and the complexity of classifiers, overfitting happens. This paper is going to talk about overfitting from the perspectives of causes and solutions. To reduce the effects of overfitting, various strategies are proposed to address to these causes: 1) “early-stopping” strategy is introduced to prevent overfitting by stopping training before the performance stops optimize; 2) “network-reduction” strategy is used to exclude the noises in training set; 3) “data-expansion” strategy is proposed for complicated models to fine-tune the hyper-parameters sets with a great amount of data; and 4) “regularization” strategy is proposed to guarantee models performance to a great extent while dealing with real world issues by feature-selection, and by distinguishing more useful and less useful features.
- The following article is Open accessDiscriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion
M R Ab Hamid et al 2017 J. Phys.: Conf. Ser. 890 012163
View article, Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT CriterionPDF, Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT CriterionAssessment of discriminant validity is a must in any research that involves latent variables for the prevention of multicollinearity issues. Fornell and Larcker criterion is the most widely used method for this purpose. However, a new method has emerged for establishing the discriminant validity assessment through heterotrait-monotrait (HTMT) ratio of correlations method. Therefore, this article presents the results of discriminant validity assessment using these methods. Data from previous study was used that involved 429 respondents for empirical validation of value-based excellence model in higher education institutions (HEI) in Malaysia. From the analysis, the convergent, divergent and discriminant validity were established and admissible using Fornell and Larcker criterion. However, the discriminant validity is an issue when employing the HTMT criterion. This shows that the latent variables under study faced the issue of multicollinearity and should be looked into for further details. This also implied that the HTMT criterion is a stringent measure that could detect the possible indiscriminant among the latent variables. In conclusion, the instrument which consisted of six latent variables was still lacking in terms of discriminant validity and should be explored further.
- The following article is Open accessDemocritus and Aristotle: Are there atoms and empty space?
Andrew Gregory 2024 J. Phys.: Conf. Ser. 2877 012006
View article, Democritus and Aristotle: Are there atoms and empty space?PDF, Democritus and Aristotle: Are there atoms and empty space?Democritus of Abdera, one of the first atomists and Aristotle the great philosopher and systematiser radically disagreed on what the world was made of. Democritus said there were atoms and empty space, while Aristotle’s view was that there were no atoms and no empty space. There were further disagreements on how to explain phenomena, how many worlds there were and how this world had come about.
- The following article is Open accessMulticollinearity and Regression Analysis
Jamal I. Daoud 2017 J. Phys.: Conf. Ser. 949 012009
View article, Multicollinearity and Regression AnalysisPDF, Multicollinearity and Regression AnalysisIn regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.
- The following article is Open accessThe determination of the energy values and the composition analysis of M-16 rifle black powders
R Satee et al 2017 J. Phys.: Conf. Ser. 901 012126
View article, The determination of the energy values and the composition analysis of M-16 rifle black powdersPDF, The determination of the energy values and the composition analysis of M-16 rifle black powdersThe determination of the energy values, specifically the heat of combustion of various M-16 black powders was the important part of the bullet efficiency investigations. The calorimetric bomb is commonly used for these determinations. Four M-16 black powders from the different sources were used as samples for this research. It was found that, after using calorimetric bomb technique, the gross heating value in Joules/g of sample S1-S4 were 10,647, 10,416, 5,281 and 3,878 respectively. The chemical compositions of carbon (C), hydrogen (H), nitrogen (N) and sulfer (S) have also been determined. The results indicated that carbon and nitrogen compositions of sample S1 shown the highest values and provided little differences with sample S2 while sample S3 and S4 shown the lowest carbon and nitrogen percentage composition. The hydrogen composition of all samples was equally valued, however, only sample 3 and 4 displayed sulfur values while no sulfur values were detected from sample 1 and 2. From these results, the heat values and chemical composition of M-16 black powders were characterized their sources and the energy values might be estimated from the amount of carbon and nitrogen in the black powders. Thus, it would be possible to use this determination analysis in the forensic investigation.
- The following article is Open accessExplicit Computation of Cheeger Constants for some Classes of Graphs
S Opiyo et al 2019 J. Phys.: Conf. Ser. 1127 012064
View article, Explicit Computation of Cheeger Constants for some Classes of GraphsPDF, Explicit Computation of Cheeger Constants for some Classes of GraphsThis article deals with the explicit computation of the Cheeger constant and its connection to understanding the properties of some classes of graphs. Cheeger constant is a measure of the connectivity or disconnectivity of graphs and gives the best possible way to cut a graph. More precisely, we deal with the problem of splitting the graph into two large components of approximately equal volumes by making a small cut, which is the idea of Cheeger constant of a graph. We computed the Cheeger constants for simple classes of graphs such as 2-comb graphs, cycle graphs, complete graphs, and cube graphs. We further analyzed the dynamics of Cheeger constants of the graphs under vertex-edge transformation.
- The following article is Open accessMachine Learning from Theory to Algorithms: An Overview
Jafar Alzubi et al 2018 J. Phys.: Conf. Ser. 1142 012012
View article, Machine Learning from Theory to Algorithms: An OverviewPDF, Machine Learning from Theory to Algorithms: An OverviewThe current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which is accelerating the adoption of machine learning solutions & practices. Machine Learning enables computers to imitate and adapt human-like behaviour. Using machine learning, each interaction, each action performed, becomes something the system can learn and use as experience for the next time. This work is an overview of this data analytics method which enables computers to learn and do what comes naturally to humans, i.e. learn from experience. It includes the preliminaries of machine learning, the definition, nomenclature and applications’ describing it’s what, how and why. The technology roadmap of machine learning is discussed to understand and verify its potential as a market & industry practice. The primary intent of this work is to give insight into why machine learning is the future.
- The following article is Open accessSpeedup and Password Recovery for Encrypted WinRAR3 without Encrypting Filename on GPUs
Qingbing Ji and Hao Yin 2020 J. Phys.: Conf. Ser. 1673 012047
View article, Speedup and Password Recovery for Encrypted WinRAR3 without Encrypting Filename on GPUsPDF, Speedup and Password Recovery for Encrypted WinRAR3 without Encrypting Filename on GPUsThe encryption mode of WinRAR3 which does not encrypt the file name uses encryption and compression, the password recovery complexity is high. The existing cracking systems crack on a single CPU or GPU platform. Because the decryption algorithm is slow on the CPU platform, while the decompression algorithm is slow on the GPU platform, the overall performance of the cracking algorithm is not high. This paper studies the mode of CPU and GPU collaborative computing, and proposes an efficient cracking method of encrypted WinRAR3 without encrypting filename. By using the CPU + GPU pipeline cooperation method, the waiting time in the calculation is reduced, and the performance of the algorithm is improved; by using the magic number matching method of compressed files, the decompression calculation can be effectively reduced. The experimental results show that the speed of the cracking algorithm proposed by this paper for 8-digit passwords is 24423/s, which is 2.3 times as fast as before.
- The following article is Open accessViolation of Bell’s inequality: Must the Einstein locality really be abandoned?
Kurt Jung 2017 J. Phys.: Conf. Ser. 880 012065
View article, Violation of Bell’s inequality: Must the Einstein locality really be abandoned?PDF, Violation of Bell’s inequality: Must the Einstein locality really be abandoned?Since John Bell has established his famous inequality and several independent experiments have confirmed the distinct polarization correlation of entangled photons predicted by quantum mechanics it is evident that quantum mechanics cannot be explained by local realistic theories. Actually, the observed polarization correlation can be deduced from wave optical considerations. The correlation has its origin in the phase coupling of the two circularly polarized wave packets leaving the photon source simultaneously. The experimental results violate Bell’s inequality although no non-local interactions have to be assumed. In consequence the principle of locality remains valid in the scope of quantum mechanics. However, the principle of realism has to be replaced by the less stringent principle of contextuality.
- The following article is Open accessPreface
2026 J. Phys.: Conf. Ser. 3225 011001
Preface
The 2025 3rd International Conference on Mechanical, Aerospace and Electronic Systems (MAES 2025) was held on November 28 – 30, 2025, in Suzhou, China. MAES 2025 served as an international forum for researchers, engineers, and practitioners to present and exchange the latest advances, research results, and practical experiences in the broad fields of mechanical engineering, aerospace science and technology, and electronic systems.
MAES 2025 was co-sponsored by Suzhou Society of Aeronautics and Astronautics, and co-hosted by the State Key Laboratory of Airliner Integration Technology, Flight Simulation and School of Civil Aviation, Northwestern Polytechnical University, and the State Key Laboratory of Air Traffic Management System. With the strong support of these institutions, the conference provided a high-level academic platform that fostered interdisciplinary collaboration and promoted innovation across related domains.
This year’s conference features a wide array of innovative research, ranging from theoretical studies to practical engineering applications. The event is composed of the keynote speeches delivered respectively by Prof. Mingwei Zhang (State Key Laboratory of Air Traffic Management System, China), Prof. Zhiyong Chen (The University of Newcastle, Australia), Prof. Liang Yu (Northwestern Polytechnical University, China), with one technical session.
This volume of proceedings includes a selection of peer-reviewed papers presented at MAES 2025. All submissions underwent a rigorous review process conducted by the Technical Program Committee and external reviewers, ensuring the academic quality, originality, and relevance of the accepted papers. The published contributions reflect current research trends and provide valuable references for future studies and technological development in the related fields.
List of Conference Committee is available in this PDF.
- The following article is Open accessPeer Review Statement
2026 J. Phys.: Conf. Ser. 3225 011002
All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.
• Type of peer review: Double Anonymous
• Conference submission management system: Morressier
• Number of submissions received: 14
• Number of submissions sent for review: 12
• Number of submissions accepted: 9
• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 64.3
• Average number of reviews per paper: 1.09
• Total number of reviewers involved: 6
• Contact person for queries:
Name: Liang YU
Email: liang.yu@nwpu.edu.cn
Affiliation: Northwestern Polytechnical University
- The following article is Open accessInvestigating different acoustic wall treatment materials for attenuation of noise and vibration in a supersonic wind tunnel
A Mogwera et al 2026 J. Phys.: Conf. Ser. 3225 012001
View article, Investigating different acoustic wall treatment materials for attenuation of noise and vibration in a supersonic wind tunnelPDF, Investigating different acoustic wall treatment materials for attenuation of noise and vibration in a supersonic wind tunnelSupersonic wind tunnels generate significant noise and vibrations that can interfere with measurement accuracy, cause structural degradation, and disrupt operations. Traditional approaches to attenuate these problems often focused on airflow dynamics, somehow neglecting the impact of compressor fan vibrations and dynamics. However, acoustic wall treatments placed in the proximity of fans in the wind tunnel can minimize these sounds and vibrations but such investigations seem under researched. Hence, this study investigates the vibro-acoustic performance of three materials: ceramic fibre, mineral wool, and melamine foam using finite element analysis (FEA). The results indicate that ceramic fibre achieved the lowest A-weighted SPL of 24.04 dBA, demonstrating its strong sound-absorbing properties compared to melamine foam and mineral wool, with SPLs of 48.687 dBA and 35.357 dBA, respectively. Analytical validation further confirmed the accuracy of the simulated results. These results highlight ceramic fibre as a highly effective material for acoustic wall treatments in minimizing compressor fan-induced noise and vibrations in supersonic wind tunnel applications.
- The following article is Open accessEvaluation of Abrasive Wear in Twin-Screw Shredder Blades for PET Block Recycling through DEM
J Vásquez et al 2026 J. Phys.: Conf. Ser. 3225 012002
View article, Evaluation of Abrasive Wear in Twin-Screw Shredder Blades for PET Block Recycling through DEMPDF, Evaluation of Abrasive Wear in Twin-Screw Shredder Blades for PET Block Recycling through DEMThe recycling of polyethylene terephthalate (PET) in block form poses significant mechanical challenges for industrial shredding systems. Among these, abrasive wear on the blades of twin-screw shredders drastically limits operational life and increases maintenance costs. This paper presents a comparative evaluation of the structural performance and wear resistance of four AISI tool steels—AISI A2, AISI D2, AISI M42, and AISI 440C—used as cutting blade materials under realistic PET crushing conditions. A dual methodology is implemented, combining an analytical model based on beam theory and shear stress, and a transient simulation using the Discrete Element Method (DEM) in ANSYS Rocky. PET was modeled as block-shaped particles (hereafter referred to as PET blocks) with an edge length of 0.1 m, with five particles per trial. To enable realistic penetration and fragmentation within the simulation, the Young’s modulus of PET was reduced to 350 MPa, a justified calibration for convergence and interaction fidelity. Wear was simulated using Archard’s model with calibrated coefficients per material. Results confirm that AISI M42 exhibits the best combined performance, with the highest safety factor, lowest deformation, and minimal volumetric wear. The study validates a replicable methodology for material selection in harsh recycling environments.
- The following article is Open accessThickness-Dependent Q-Frequency Optimization for RF Integrated Inductors
Fangyu Hou et al 2026 J. Phys.: Conf. Ser. 3225 012003
View article, Thickness-Dependent Q-Frequency Optimization for RF Integrated InductorsPDF, Thickness-Dependent Q-Frequency Optimization for RF Integrated InductorsThe quality factor (Q-factor) of RF integrated inductors is a critical parameter that directly indicates the performance of radio-frequency integrated circuits (RFICs). Among the factors influencing Q-factor, skin effect and surface scattering are particularly significant, yet commonly omitted in existing models. Metal thickness plays a decisive role in determining the dominant loss mechanism: surface scattering prevails at nanometer scales, whereas skin effect dominates in the micrometer regime. This study develops a physics-based modelling approach to analyze the Q-frequency (Q-f) behaviour under varying metal thicknesses. Both surface scattering and skin effects are incorporated into the resistance model through analytical derivations and integrated into a simulation framework. Comparative analyses between the proposed model and existing experimental data reveal an improvement in Q-factor prediction accuracy. The proposed model optimizes inductor design and highlights the critical role of metal thickness in determining dominant loss mechanisms in RF integrated inductors.
- The following article is Open accessDiscriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion
M R Ab Hamid et al 2017 J. Phys.: Conf. Ser. 890 012163
View article, Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT CriterionPDF, Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT CriterionAssessment of discriminant validity is a must in any research that involves latent variables for the prevention of multicollinearity issues. Fornell and Larcker criterion is the most widely used method for this purpose. However, a new method has emerged for establishing the discriminant validity assessment through heterotrait-monotrait (HTMT) ratio of correlations method. Therefore, this article presents the results of discriminant validity assessment using these methods. Data from previous study was used that involved 429 respondents for empirical validation of value-based excellence model in higher education institutions (HEI) in Malaysia. From the analysis, the convergent, divergent and discriminant validity were established and admissible using Fornell and Larcker criterion. However, the discriminant validity is an issue when employing the HTMT criterion. This shows that the latent variables under study faced the issue of multicollinearity and should be looked into for further details. This also implied that the HTMT criterion is a stringent measure that could detect the possible indiscriminant among the latent variables. In conclusion, the instrument which consisted of six latent variables was still lacking in terms of discriminant validity and should be explored further.
- The following article is Open accessAn Overview of Overfitting and its Solutions
Xue Ying 2019 J. Phys.: Conf. Ser. 1168 022022
View article, An Overview of Overfitting and its SolutionsPDF, An Overview of Overfitting and its SolutionsOverfitting is a fundamental issue in supervised machine learning which prevents us from perfectly generalizing the models to well fit observed data on training data, as well as unseen data on testing set. Because of the presence of noise, the limited size of training set, and the complexity of classifiers, overfitting happens. This paper is going to talk about overfitting from the perspectives of causes and solutions. To reduce the effects of overfitting, various strategies are proposed to address to these causes: 1) “early-stopping” strategy is introduced to prevent overfitting by stopping training before the performance stops optimize; 2) “network-reduction” strategy is used to exclude the noises in training set; 3) “data-expansion” strategy is proposed for complicated models to fine-tune the hyper-parameters sets with a great amount of data; and 4) “regularization” strategy is proposed to guarantee models performance to a great extent while dealing with real world issues by feature-selection, and by distinguishing more useful and less useful features.
- The following article is Open accessMulticollinearity and Regression Analysis
Jamal I. Daoud 2017 J. Phys.: Conf. Ser. 949 012009
View article, Multicollinearity and Regression AnalysisPDF, Multicollinearity and Regression AnalysisIn regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.
- The following article is Open accessLarch: An Analysis Package for XAFS and Related Spectroscopies
Matthew Newville 2013 J. Phys.: Conf. Ser. 430 012007
View article, Larch: An Analysis Package for XAFS and Related SpectroscopiesPDF, Larch: An Analysis Package for XAFS and Related SpectroscopiesLARCH, a package of analysis tools for XAFS and related spectroscopies is presented. A complete rewrite of the ifeffit package, the initial release of larch preserves the core XAFS analysis procedures such as normalization, background subtraction, Fourier transforms, fitting of XANES spectra, and fitting of experimental spectra to a sum of feff Paths, with few algorithmic changes made in comparison to IFEFFIT. LARCH is written using Python and its packages for scientific programming, which gives significant improvements over IFEFFIT in the ability to handle multi-dimensional and large data sets, write complex analysis scripts, visualize data, add new functionality, and customize existing capabilities. Like the earlier version, larch can run from an interactive command line or in batch-mode, but larch can also be run as a server and accessed from clients using standard inter-process communication techniques available in a variety of computer languages. larch is freely available under an open source license. Examples of using larch are shown, future directions for development are discussed, and collaborations for adding new capabilities are actively sought.
- The following article is Open accessMachine Learning from Theory to Algorithms: An Overview
Jafar Alzubi et al 2018 J. Phys.: Conf. Ser. 1142 012012
View article, Machine Learning from Theory to Algorithms: An OverviewPDF, Machine Learning from Theory to Algorithms: An OverviewThe current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which is accelerating the adoption of machine learning solutions & practices. Machine Learning enables computers to imitate and adapt human-like behaviour. Using machine learning, each interaction, each action performed, becomes something the system can learn and use as experience for the next time. This work is an overview of this data analytics method which enables computers to learn and do what comes naturally to humans, i.e. learn from experience. It includes the preliminaries of machine learning, the definition, nomenclature and applications’ describing it’s what, how and why. The technology roadmap of machine learning is discussed to understand and verify its potential as a market & industry practice. The primary intent of this work is to give insight into why machine learning is the future.
- The following article is Open accessGreen synthesis of silver nanoparticles and their characterization by XRD
B K Mehta et al 2017 J. Phys.: Conf. Ser. 836 012050
View article, Green synthesis of silver nanoparticles and their characterization by XRDPDF, Green synthesis of silver nanoparticles and their characterization by XRDA cost effective and environment friendly technique for green synthesis of silver nanoparticles has been reported. Silver nanoparticles have been synthesized using ethanol extract of fruits of Santalum album (Family Santalaceae), commonly known as East Indian sandalwood. Fruits of S.album were collected and crushed. Ethanol was added to the crushed fruits and mixture was exposed to microwave for few minutes. Extract was concentrated by Buchi rotavaporator. To this extract, 1mM aqueous solution of silver nitrate (AgNO3) was added. After about 24 hr incubation Ag+ ions in AgNO3 solution were reduced to Ag atoms by the extract. Silver nanoparticles were obtained in powder form. X-ray diffraction (XRD) pattern of the prepared sample of silver nanoparticles was recorded The diffractogram has been compared with the standard powder diffraction card of JCPDS silver file. Four peaks have been identified corresponding to (hkl) values of silver. The XRD study confirms that the resultant particles are silver nanoparticles having FCC structure. The average crystalline size D, the value of the interplanar spacing between the atoms, d, lattice constant and cell volume have been estimated. Thus, silver nanoparticles with well-defined dimensions could be synthesized by reduction of metal ions due to fruit extract of S.album.
- The following article is Open accessA comparison of TEM and DLS methods to characterize size distribution of ceramic nanoparticles
T. G. F. Souza et al 2016 J. Phys.: Conf. Ser. 733 012039
View article, A comparison of TEM and DLS methods to characterize size distribution of ceramic nanoparticlesPDF, A comparison of TEM and DLS methods to characterize size distribution of ceramic nanoparticlesThe accuracy of dynamic light scattering (DLS) measurements are compared with transmission electron microscopy (TEM) studies for characterization of size distributions of ceramic nanoparticles. It was found that measurements by DLS using number distribution presented accurate results when compared to TEM. The presence of dispersants and the enlargement of size distributions induce errors to DLS particle sizing measurements and shifts its results to higher values.
- The following article is Open accessPyFAI, a versatile library for azimuthal regrouping
Jérôme Kieffer and Dimitrios Karkoulis 2013 J. Phys.: Conf. Ser. 425 202012
View article, PyFAI, a versatile library for azimuthal regroupingPDF, PyFAI, a versatile library for azimuthal regrouping2D area detectors like CCD or pixel detectors have become popular in the last 15 years for diffraction experiments (e.g. for WAXS, SAXS, single crystal and powder diffraction (XRPD)). These detectors have a large sensitive area of millions of pixels with high spatial resolution. The software package pyFAI has been designed to reduce SAXS, WAXS and XRPD images taken with those detectors into 1D curves (azimuthal integration) usable by other software for in-depth analysis such as Rietveld refinement, or 2D images (a radial transformation named caking). As a library, the aim of pyFAI is to be integrated into other tools like PyMca or EDNA with a clean pythonic interface. However pyFAI features also command line tools for batch processing, converting data into q-space (q being the momentum transfer) or 2θ-space (θ being the Bragg angle) and a calibration graphical interface for optimizing the geometry of the experiment using the Debye-Scherrer rings of a reference sample. PyFAI shares the geometry definition of SPD but can directly import geometries determined by the software FIT2D. PyFAI has been designed to work with any kind of detector and geometry (transmission or reflection) and relies on FabIO, a library able to read more than 20 image formats produced by detectors from 12 different manufacturers. During the transformation from cartesian space (x,y) to polar space (2θ, χ), both local and total intensities are conserved in order to obtain accurate quantitative results. Technical details on how this integration is implemented and how it has been ported to native code and parallelized on graphic cards are discussed in this paper.
- The following article is Open accessOptical properties of graphene
L A Falkovsky 2008 J. Phys.: Conf. Ser. 129 012004
Reflectance and transmittance of graphene in the optical region are analyzed as a function of frequency, temperature, and carrier density. We show that the optical graphene properties are determined by the direct interband electron transitions. The real part of the dynamic conductivity in doped graphene at low temperatures takes the universal constant value, whereas the imaginary part is logarithmically divergent at the threshold of interband transitions. The graphene transmittance in the visible range is independent of frequency and takes the universal value given by the fine structure constant.
- The following article is Open accessRaman scattering in nanosized nickel oxide NiO
N Mironova-Ulmane et al 2007 J. Phys.: Conf. Ser. 93 012039
View article, Raman scattering in nanosized nickel oxide NiOPDF, Raman scattering in nanosized nickel oxide NiOMagnetic ordering in nanosized (100 and 1500 nm) nickel oxide NiO powders, prepared by the plasma synthesis method, was studied using Raman scattering spectroscopy in a wide range of temperatures from 10 to 300 K. It was observed that the intensity of two-magnon band decreases rapidly for smaller crystallites size. This effect is attributed to a decrease of antiferromagnetic spin correlations and leads to the antiferromagnetic-to-paramagnetic phase transition.
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Journal of Physics: Conference Series
doi: 10.1088/issn.1742-6596
Online ISSN: 1742-6596
Print ISSN: 1742-6588