Atomic Elements Research Articles

Double cavity induced transparency in a Y-type atomic system based on cavity QED photons

We show that a fully quantum-mechanical model consisting of a four-level atom with Y-type atomic structure inside a three-mode cavity can exhibit double cavity induced transparency (CIT). In this model, it is cavity photons that induce the transparency, and there is no need to use external classical fields. As this double-CIT model involves several atomic levels, we adapt the wavefunction approach as a quantum-jump description of dissipation to derive an analytical expression for the steady-state linear susceptibility of a weak cavity field. We then use this analytical expression to investigate the dependence of the CIT transparency windows on the detuning of the coupling fields, intensities of the cavity fields and the cavity linewidths. We also have tested the analytical results by numerically integrating the full set of optical Bloch equations for the atomic density-matrix elements.

Tourmaline Megacryst Reference Materials for High Precision In Situ Boron Isotope and Elemental Measurement by LA‐MC‐ICP‐MS

Tourmaline serves as a vital recorder of geological processes. However, suitable tourmaline reference materials (RMs) for elemental and stable isotopic composition in situ measurements are still limited. In this study, three tourmaline megacrysts (MD‐B66, IM‐B232 and BR‐DG68) were characterised as potential RMs for B isotope measurements by LA‐MC‐ICP‐MS and mass fraction determinations by LA‐ICP‐MS. Over 251 measurements with LA‐MC‐ICP‐MS on ten randomly selected fragments from MD‐B66 consistently yielded B isotope ratios of ‐7.74 ± 0.25‰ (2s), establishing MD‐B66 as a suitably homogeneous primary reference material for high‐precision, in situ microbeam B isotope measurements. Notably, the (long‐term) intermediate precision of 0.25‰ (2s) for in situ B isotope measurements obtained using this reference material is comparable to that reported from solution MC‐ICP‐MS methods in the literature. Two other tourmaline megacrysts, with intermediate precision ranging from ± 0.48‰ to ± 0.61‰ (2s) for δ11B measurement, can be employed as secondary RMs for quality control. The mean δ11B values determined by solution MC‐ICP‐MS for MD‐B66 (‐7.71 ± 0.32‰, n = 12), IM‐B232 (‐13.17 ± 0.62‰, n = 8) and BR‐DG68 (‐13.85 ± 0.32‰, n = 12), with expanded uncertainties at the 95% confidence level, are consistent with those determined by LA‐MC‐ICP‐MS. Among these three new RMs, BR‐DG68 displays relatively homogeneous major and trace element mass fractions. Characterisation using both in situ and wet chemical techniques demonstrated the suitability of BR‐DG68 as the first tourmaline reference material for elemental measurement by LA‐ICP‐MS, which would permit matrix‐matched and therefore more accurate elemental measurement in tourmalines. Unlike electron probe microanalysis with B and Li contents calculated based on stoichiometric assumptions, direct and accurate measurements of the two low atomic number elements, along with other major and trace elements can be achieved by LA‐ICP‐MS with the aid of the newly developed tourmaline reference material BR‐DG68. Overall, current and future studies in geochemistry may benefit from these newly proposed tourmaline RMs, which should lead to significantly improved precision and accuracy for in situ B isotope and elemental measurement.

Surface elemental and structural analysis of ancient Indian punch-marked coins (600 to 200 BCE): insights into metallurgy and economic practices

Punch-marked coins (PMCs) are the oldest coins in India and among the most widely circulated globally, often found in hoards that highlight their extensive use. This study utilizes X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) to analyze the surface elemental composition and chemical properties of nine series (S-0 to S-VIII) of Janapada (S-0) and imperial PMCs (S-1 to S-VIII) dating from 600 to 200 BCE, housed in the Numismatic Society of India at BHU, Varanasi, based on the Gupta-Hardakar classification related to the PMCs. XRD results reveal four prominent diffraction peaks corresponding to metallic silver (Ag) in the face-centred cubic (fcc) phase, with a slight variation in d-spacing (∼ 0.05 Å), suggesting subtle changes in the lattice structure due to smaller atomic radius elements. XPS analysis shows the non-uniform distribution of different elements, with Ag being predominant, alongside copper (Cu), lead (Pb), and trace elements, including gold (Au), only in Janapada PMCs (S-0). The binding energy curves indicate that Ag and Cu are in pure metallic forms, while Pb exists as Pb₂O₃. Importantly, no silver or copper oxide peaks were detected, indicating the metals’ purity throughout the coinage process. The variations in d-spacing observed in these historical samples offer a microscopic perspective into the broader contexts of ancient economies, technologies, and cultural practices. The silver content in these PMCs decreases as Cu and Pb increase across the series up to S-V, followed by a sudden rise in S-VI, which lacks Pb. The presence of Pb induces brittleness and may serve as an indicator of the coins’ age. Additionally, the carbon detected by XPS could result from smelting, surface contamination, or environmental deposition. These findings reflect a high level of metallurgical knowledge and alloying techniques developed between the sixth and third centuries BCE. The varying Ag content raises questions about the economy and demand for coins. At the same time, the structural variations identified through XRD and XPS can aid archaeometallurgists in estimating these coins’ chronological and geographical origins, serving as valuable tools for authentication.

Do Binders Form Surface Films on Active Particles in Li-Ion Electrodes? Revealing Nanoscopic Surface Binder Morphology in Graphitic Electrodes Using Chemical Staining and High-Resolution Energy-Selective Backscattered Electron Imaging

Although polymeric binders constitute only a small fraction (< 5% volume) of Li-ion electrodes, they are an essential component of Li-ion batteries, binding otherwise loose active particles to each other and to the current collector. Yet, despite more than 30 years of development of Li-ion batteries, the exact morphology that binders adopt on and around the active particle surfaces in the electrodes remains extremely difficult to assess, similarly to the fraction of active particle surface covered by the binder. It is already well established that binder chemistry strongly influences key battery surface reactions, such as Li insertion/deinsertion or formation of solid electrolyte interface (SEI).1,2 Also, binder chemistry can be a decisive factor in reaching long cycle stability over rapid failure of, for example, silicon-based electrodes.3 Therefore, quantifying surface coverage of the binders on active particles remains the missing piece for fully understanding binder roles in batteries, and can open new avenues for improving lifetime and rate performance of current and next generation electrodes.In this work, we present a newly established method for large-scale, high-resolution imaging and quantification of carboxymethyl cellulose (CMC) and styrene butadiene rubber (SBR) binders in graphitic Li-ion electrodes. The imaging was enabled using highly selective chemical staining of the binders with high atomic number elements that act as excellent contrast agents during backscattered electron (BSE) imaging. Following staining of the binders, we imaged them using a variant of BSE known as energy-selective backscattered electron imaging (EsB), which operates at low beam voltage and can provide nanometer-level resolution by selective energy filtering of backscattered electrons. By acquiring images at different beam voltages, we selectively captured different fine-scale morphological details of the binder on and around the graphite particles. We revealed binder/carbon additive agglomerates, islands of non-dispersed SBR nanoparticles and, for the first time, details of a continuous thin layer formed by CMC and SBR on the graphite surface that spans across the entire graphitic electrode. Using a combination of Monte Carlo simulations and high resolution cross-sectional EsB imaging, we estimated the thickness of this surface film to be only 10 nanometers. Because of such small thickness, the film adopts the morphology of the underlying graphite surface, which is why it cannot be observed using conventional secondary electron imaging, even at very low beam voltages. Using quantitative image analysis, we also characterized electrodes before and after calendering, finding that calendering shatters the previously-continuous binder film, leaving only 30% of graphitic surfaces covered by irregular patches of the binder layer. We also verified our results by analyzing commercial graphitic electrodes used in electric vehicle batteries, finding identical binder morphologies inside these electrodes.Considering the likely impact of binder coverage on e.g. active particle stability, SEI formation or distribution of local current density during electrochemical cycling, we suggest that this new ability to rapidly image and quantify binder coverage on active particle surfaces will open new avenues to optimize Li-ion electrodes, bridging the gaps between the chemistry, processing and performance of binder-active particle interfaces.(1) Fedorova, A. A.; Levin, O. V.; Eliseeva, S. N.; Katrašnik, T.; Anishchenko, D. V. Investigating the Coating Effect on Charge Transfer Mechanisms in Composite Electrodes for Lithium-Ion Batteries. Int. J. Mol. Sci. 2023, 24.(2) Young, B. T.; Nguyen, C. C.; Lobach, A.; Heskett, D. R.; Woicik, J. C.; Lucht, B. L. Role of Binders in Solid Electrolyte Interphase Formation in Lithium Ion Batteries Studied with Hard X-Ray Photoelectron Spectroscopy. J. Mater. Res. 2019, 34, 97–106.(3) Jung, C. H.; Kim, K. H.; Hong, S. H. Stable Silicon Anode for Lithium-Ion Batteries through Covalent Bond Formation with a Binder via Esterification. ACS Appl. Mater. Interfaces 2019, 11, 26753–26763.Figure 1. Combined secondary electron image (left) and color-enhanced EsB image (right) of an internal part of uncalendered graphitic electrode with chemically stained CMC binder (colored green in the EsB image). Figure 1

The role of surface substitution in the atomic disorder-to-order phase transition in multi-component core–shell structures

Intermetallic phases with atomic ordering are highly active and stable in catalysts. However, understanding the atomistic mechanisms of disorder-to-order phase transition, particularly in multi-component systems, remains challenging. Here, we investigate the atom diffusion and phase transition within Pd@Pt-Co cubic nanoparticles during annealing, using in-situ electron microscopy and ex-situ atomic resolution element analysis. We reveal that initial outward diffusing Pd partially substitutes Pt, forming a (Pt, Pd)-Co ternary system in the surface region, enabling the phase transition at a low temperature of 400 °C, followed by shape-preserved inward propagation of the ordered phase. At higher temperatures, excessive interdiffusion across the interface changes the stoichiometric ratio, diminishing the atomic ordering, leading to obvious change in morphology. Calculations indicate that the Pd-substitute in (Pt, Pd)-Co system leads to a significantly lower phase transition temperature compared to that of Pt-Co alloy and thus a lower activation energy for atomic diffusion. These insights into atomistic behavior are crucial for future design of multi-component systems.

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) plays a key role in limiting the performance of metallic fuels in nuclear applications. A comprehensive analysis of chemical elements present in FCCI region is the basis for understanding the phenomena and developing potential mitigating strategies. The detection of low atomic number elements (Z < 11) and lanthanide fission products is challenging for energy dispersive x-ray spectroscopy (EDS). This work used scanning transmission electron microscopy (STEM) based electron energy loss spectroscopy (EELS) to study the distribution of carbon and lanthanides in the FCCI region of a solid U-10Zr (wt%) fuel irradiated to 13.2 at. % burnup at the Fast Flux Testing Facility (FFTF). Processing the STEM-EELS data involved three major steps: 1) enhancing the signal-to-noise ratio by denoising the STEM-EELS spectra using principal component analysis (PCA) methods; 2) identification and mapping of chemical elements with core energy loss edges; 3) microstructural phase segmentation using the K-means clustering method. STEM-EELS analysis indicated the formation of zirconium carbide, a rind-like microstructural phase, in the FCCI region between fuel and cladding. The rind appeared to remain intact at this location for the studied burnup. The study also revealed a shift in the plasmon peak between zirconium-rich region and zirconium carbide. The STEM-EELS mappings demonstrated a different distribution of Ce from other lanthanide elements, such as La, Pr, and Nd, suggesting that the effect of lanthanides in the FCCI region should be separately investigated. The use of K-means clustering method on the STEM-EELS spectra of the FCCI region revealed different phases, especially Fe-Ce and Zr-C, that concurred with the findings from STEM-EELS elemental mappings.

High-sensitivity and spatial resolution benchtop cone beam XFCT imaging system with pixelated photon counting detectors using enhanced multipixel events correction method

Objective.High atomic number element nanoparticles have shown potential in tumor diagnosis and therapy. X-ray fluorescence computed tomography (XFCT) technology enables quantitative imaging of high atomic number elements by specifically detecting characteristic x-ray signals. The potential for further biomedical applications of XFCT depends on balancing sensitivity, spatial resolution, and imaging speed in existing XFCT imaging systems.Approach.In this study, we utilized a high-energy resolution pixelated photon-counting detector for XFCT imaging. We tackled degradation caused by multi-pixel events in the photon-counting detector through energy and interaction position corrections. Sensitivity and spatial resolution imaging experiments were conducted using PMMA phantoms to validate the effectiveness of the multi-pixel events correction algorithm.Main results.After correction, the system's sensitivity and spatial resolution have both improved. Furthermore, XFCT/CBCT dual-modality imaging of gadolinium nanoparticles within mice subcutaneous tumor was successfully achieved.Significance.These results demonstrate the preclinical research application potential of the XFCT/CBCT dual-modality imaging system in high atomic number nanoparticle-based tumor diagnosis and therapy.

Development of novel multifunctional phase change microcapsules for improving thermal comfort and radiation properties

Microencapsulated phase change materials (MPCMs) have gained widespread application in energy-efficient buildings, aiming to improve thermal comfort and reduce energy consumption. To enhance the engineering feasibility of MPCMs, researchers are now focusing on developing MPCMs with multifunctional properties, beyond single thermal storage functionality. In this study, we proposed a novel and straightforward approach to fabricate multifunctional MPCMs with BaCO3 as shell and a core composed of binary phase change materials (PCMs) and lipophilic-modified graphite (MG) via self-assembly method. The incorporation of BaCO3 shell provides MPCMs with additional resistance to ionizing radiation pollution due to the high atomic number element Ba. Additionally, the incorporation of MG into PCMs enhances its temperature sensitivity. The thermal analysis indicates that the binary PCMs’ composition in MPCMs results in two phase transition temperatures at 3.3 °C and 26.4 °C, making them capable of thermal storage in line with comfortable residential temperatures across different seasons. Furthermore, MPCMs were introduced into cement paste (CPM) and used to construct cement chambers. Adding 10 wt% MPCMs in the CPM chambers placed outdoors in Wuhan (from June 7th to June 9th) led to a 23.8 % decrease in temperature fluctuations compared to the reference sample. Radiation shielding results indicated that the linear attenuation coefficient (μ) of CPM increased by 58.7 %, due to enhanced incoherent scattering and photoelectric effects between high atomic number elements and photons. Additionally, XCOM simulations predicted a strong correlation between MPCM content and μ values, with particularly high accuracy at low photon energies. Overall, the multifunctional MPCMs developed in this study not only offers a new route for reducing residential energy consumption and shielding ionizing pollution, but also broadens the applicability of traditional PCMs in the building and other fields.

Connecting the Wings of Dynamism: Bibliometric Analysis of Artificial Intelligence and Entrepreneurship Fields

This study aims to create a holistic viewpoint by concentrating on two dynamic areas of artificial intelligence and entrepreneurship with bibliometric analysis. The concept of artificial intelligence, which is constantly heard as the digital world gradually penetrates our lives, and entrepreneurship, which is referred to as the atomic element of the economic infrastructure, are addressed in the same pot with this research. The attitude of both areas against varying circumstances constitutes the essential basis of this examination. The view that the effectiveness in the areas can be increased with the synergy to be created between the two focuses is supported. With this intention, the study commences with an informative literature section, where the introductory elements of the areas are conveyed. Afterward, it tries to clarify why these zones need to be examined together. Following this, a bibliometric analysis study, frequently used to bring unfamiliar kinds of literature jointly, is conducted using data obtained from the Web of Science database and subjected to various analyses. In the last stage, the study is completed by examining these outputs and analyzes. As a result, conclusions support “the duo” can be investigated jointly. The study contributes to the idea that artificial intelligence and entrepreneurship are wings working in synchrony for the requirement of success.

Investigating the effect of special nanopore shapes on Graphene mechanical properties using a computationally efficient atomic finite element model

Investigating the effect of special nanopore shapes on Graphene mechanical properties using a computationally efficient atomic finite element model

Grammar and the Formal Identity of Name and Object

In this paper, I will be arguing that the basic infrastructure of an ineffable formal identity between name and object which is presented in the Tractatus is still very much involved in Wittgenstein's early development of the concept of grammar. First, it will be necessary to clearly describe how the identity between name and object is initially formulated in the Tractatus. Hence, in section 1, I will show how the 'picture theory' is ontologically grounded on the identity of linguistics' and worldly atomic structural elements. I will discuss the ‘picture theory’ only briefly, since my main interest is to illuminate how that infrastructure remains a core aspect of Wittgenstein's “middle period” thinking: that is, in what way the identity of name and object is contained and presupposed within his concept of grammar and how it is still used as a condition for our symbolism to make sense. Another way to describe this paper's aim, this time from its end backwards, would be to say that it is to reveal that grammatical systems of rules are nothing other than the implementations of that special kind of identity, for the latter is always and already manifest within our symbolism

Exploring Molecular Heteroencoders with Latent Space Arithmetic: Atomic Descriptors and Molecular Operators.

A variational heteroencoder based on recurrent neural networks, trained with SMILES linear notations of molecular structures, was used to derive the following atomic descriptors: delta latent space vectors (DLSVs) obtained from the original SMILES of the whole molecule and the SMILES of the same molecule with the target atom replaced. Different replacements were explored, namely, changing the atomic element, replacement with a character of the model vocabulary not used in the training set, or the removal of the target atom from the SMILES. Unsupervised mapping of the DLSV descriptors with t-distributed stochastic neighbor embedding (t-SNE) revealed a remarkable clustering according to the atomic element, hybridization, atomic type, and aromaticity. Atomic DLSV descriptors were used to train machine learning (ML) models to predict 19F NMR chemical shifts. An R2 of up to 0.89 and mean absolute errors of up to 5.5 ppm were obtained for an independent test set of 1046 molecules with random forests or a gradient-boosting regressor. Intermediate representations from a Transformer model yielded comparable results. Furthermore, DLSVs were applied as molecular operators in the latent space: the DLSV of a halogenation (H→F substitution) was summed to the LSVs of 4135 new molecules with no fluorine atom and decoded into SMILES, yielding 99% of valid SMILES, with 75% of the SMILES incorporating fluorine and 56% of the structures incorporating fluorine with no other structural change.

Partially recrystallized heterostructure via Mo-doping endows CoCrNi medium-entropy alloy with exceptional strength and ductility

CoCrNi medium-entropy alloy (MEA) has excellent ductility, but the low strength at room temperature limits its practical usage. This study proposes an effective strategy to enhance the strength of CoCrNi MEA without apparent loss of ductility via partially recrystallized heterostructures resulted from doping of large atomic radius element, which was substantiated in a Mo-doping (CoCrNi)98Mo2 MEA. Compared with CoCrNi, the strength of (CoCrNi)98Mo2 is remarkably improved, maintaining the high uniform elongation of ∼24%. The yield strength and ultimate tensile strength increased from 950 MPa, 1287 MPa to 1131 MPa, 1564 MPa, respectively. The difference in deformation between the soft recrystallized region (SRR) and the hard non-recrystallized region (HNRR) leads to an excellent hetero-deformation induced (HDI) strengthening. Additionally, it is easier to reach the critical stress of twinning caused by high HDI stress at the interface of SRR/HNRR, which contributes to activation of high-density twins and produce dynamic Hall-Petch strengthening effect.

Atomic Structure and Chemical Elements (Islamic Perspective) Book as a Learning Resource

This research is a detailed examination of the development of the chemistry educational sources. The aims of the research are to describe (1) the validity of teaching material (2) the students' responses to the teaching material developed. The type of research is research and development (R&amp;D), with model 4D by Thiagarajan. The stages development of 4D are define, design, develop and desseminate. The subjects of this study are students and lecturers of UIN Antasari. The data collection techniques and instruments used in this study are interview guides, questionnaires and observations. Based on the results of expert validation: validation of material experts with an average of 81% with the criteria "Very Valid" and validation of media experts with an average of 83.4% with the criteria "Very Valid" state that the teaching material developed is very valid and is suitable as teaching material. The percentage score of 91.6% with the "Very Good" criteria is obtained from the responses of 10 chemistry education students of UIN Antasari Banjarmasin to the teaching material developed. This book can be used in learning process that involves both students and lecturers. Keywords : Atomic Structure , Islamic Perspective, Self Learning Resource

Context-aware geometric deep learning for protein sequence design

Protein design and engineering are evolving at an unprecedented pace leveraging the advances in deep learning. Current models nonetheless cannot natively consider non-protein entities within the design process. Here, we introduce a deep learning approach based solely on a geometric transformer of atomic coordinates and element names that predicts protein sequences from backbone scaffolds aware of the restraints imposed by diverse molecular environments. To validate the method, we show that it can produce highly thermostable, catalytically active enzymes with high success rates. This concept is anticipated to improve the versatility of protein design pipelines for crafting desired functions.

Sunflower-like eutectic solidification in gas atomized Al0.3CrFeNiTi0.3 medium-entropy alloy powders: A comprehensive microstructural study

The addition of larger atomic size elements, such as Al and Ti, to CrFeNi medium-entropy alloys (MEAs) offers a strategic approach to overcome the strength-ductility trade-off. This study focuses on examining the morphological, solidification, phase, and elemental characteristics of Al0.3CrFeNiTi0.3 feedstock powders produced through gas atomization (GA). The rapid cooling rate inherent in GA results in sunflower-like eutectic solidification. This structure exhibits firstly solidified Cr-rich BCC phases filled with cuboidal-shaped L21-type precipitates, each measuring up to ∼20 nm. Their peripheral regions display outward and radial growth of L21 and Fe-rich BCC eutectic phases, while FCC phase develops at the remaining sites. Intermediate B2 layers between BCC and L21 phases are considered as kinetic buffers, which enhance the interfacial stability. The size and shapes of powders determine their cooling rates, leading to a transition from comparably large sunflower-like eutectic structures to finer equiaxed grains alongside reduced elemental segregation with decreasing powder size. Nano-hardness measurements demonstrate superior mechanical strength in the peripheral regions due to the higher volume fraction of the L21 phase and its optimal interfacial coherency with the Fe-rich BCC phase. Furthermore, the slightly higher concentrations of Al and Ti in Fe-rich BCC phase (compared to the Cr-rich BCC phase) induce a better lattice distortion effect.

Artificial Intelligence and High-Throughput Computational Workflows Empowering the Fast Screening of Metal-Organic Frameworks for Hydrogen Storage.

Metal-organic frameworks (MOFs) are one of the most promising hydrogen-storing materials due to their rich specific surface area, adjustable topological and pore structures, and modified functional groups. In this work, we developed automatically parallel computational workflows for high-throughput screening of ∼11,600 MOFs from the CoRE database and discovered 69 top-performing MOF candidates with work capacity greater than 1.00 wt % at 298.5 K and a pressure swing between 100 and 0.1 bar, which is at least twice that of MOF-5. In particular, ZITRUP, OQFAJ01, WANHOL, and VATYIZ showed excellent hydrogen storage performance of 4.48, 3.16, 2.19, and 2.16 wt %. We specifically analyzed the relationship between pore-limiting diameter, largest cavity diameter, void fraction, open metal sites, metal elements or nonmetallic atomic elements, and deliverable capacity and found that not only geometrical and physical features of crystalline but also chemical properties of adsorbate sites determined the H2 storage capacity of MOFs at room temperature. It is highlighted that we first proposed the modified crystal graph convolutional neural networks by incorporating the obtained geometrical and physical features into the convolutional high-dimensional feature vectors of period crystal structures for predicting H2 storage performance, which can improve the prediction accuracy of the neural network from the former mean absolute error (MAE) of 0.064 wt % to the current MAE of 0.047 wt % and shorten the consuming time to about 10-4 times of high-throughput computational screening. This work opens a new avenue toward high-throughput screening of MOFs for H2 adsorption capacity, which can be extended for the screening and discovery of other functional materials.

Implementing a new Research Data Alliance recommendation, the I-ADOPT framework, for the naming of environmental variables of continental surfaces

To improve data usage in an interdisciplinary context, a clear understanding of the variables being measured is required for both humans and machines. In this paper, the I-ADOPT framework, which decomposes variable names into atomic elements, was tested within the context of continental surfaces and critical zone science, characterized by a large number and variety of observed environmental variables. We showed that the I-ADOPT framework can be used effectively to describe environmental variables with precision and that it was flexible enough to be used in the critical zone science context. Variable names can be documented in detail while allowing alignment with other ontologies or thesauri. We have identified difficulties in modeling complex variables, such as those monitoring fluxes between different environmental compartments and for variables monitoring ratios of physical quantities. We also showed that, for some variables, different decompositions were possible, which could make alignments with other ontologies and thesauri more difficult. The precision of variable names proved inadequate for data discovery services and a non-standard label (SimplifiedLabel) had to be defined for this purpose. In the context of open science and interdisciplinary research, the I-ADOPT framework has the potential to improve the interoperability of information systems and the use of data from various sources and disciplines.

Comparison of photon interaction coefficients for tumor compositions and healthy tissues simulated by Monte Carlo

This study compares interaction coefficients of photons (namely, mass attenuation, energy absorption and energy transfer coefficients) for some tumor tissues with simlar healthy tissues. Monte Carlo calculations were performed for adenoidcystic carcinoma, melanoma, rectal adenocarcinoma, sarcoma and squamous cell lung carcinoma. The simulation model involved a monoenergetic point source producing a pencil beam. Depending on the parameter under study, average flux, energy flux, or dose deposition from photons that travels in an absorber were scored in the range of 10 keV–20 MeV energy using MCNP6.1. The same model was used to compute the interaction coefficients of health tissues (namely, gastrointestinal tract-small intestine wall, lungs-parenchyma, salivary glands, skin, soft tissue (female+male)) for comparison purposes. The results showed that, depending on the contents of the tumor samples, photon interaction coefficients of a tumor may differ from those of a similar healthy tissue. This behavior was distinct, especially for energies up to 100 keV, and was attributed to the presence of relatively higher atomic number elements in the absorber.

Proper orthogonal descriptors for multi-element chemical systems

We introduce the proper orthogonal descriptors for efficient and accurate interatomic potentials of multi-element chemical systems. The potential energy surface of a multi-element system is represented as a many-body expansion of parametrized potentials which are functions of atom positions, atom types, and parameters. The proper orthogonal decomposition is employed to decompose the parametrized potentials as a linear combination of orthogonal basis functions. The orthogonal basis functions are used to construct proper orthogonal descriptors based on the elements of atoms, thus leading to multi-element descriptors. We compose the multi-element proper orthogonal descriptors to develop linear and quadratic interatomic potentials. We devise an algorithm to efficiently compute the total energy and forces of the interatomic potentials constructed from the proper orthogonal descriptors. The potentials are demonstrated for indium phosphide and titanium dioxide in comparison with the spectral neighbor analysis potential (SNAP) and atomic cluster expansion (ACE) potentials.