Structure Refinement Research Articles

Investigations on ancient bronze drums from Majiang, Guangxi, P. R. China

Six different types of Majiang bronze drums from Hechi City, Guangxi, China were collected from the Guangxi Museum to characterize the original scheme of polychromy and materials used for the drums. The composition of all the samples were determined by using scanning electron microscopy with energy-dispersive X-ray spectroscopy. All the bronze drums contain mainly Cu, Sn, Pb, and As. Qualitative analysis of the structure by X-ray powder diffraction indicates that each of the six bronze drums contains four or five phases, namely (Cu, As), Pb, Cu3Sn, and Cu10Sn3 or Cu, Pb, As0.2Cu1.8, Cu3Sn, and Cu10Sn3. The Rietveld structural refinement is performed first time for the quantitative analysis of ancient bronze drums and inorganic cultural relics. This paper reports the result.

Biological characterisation and computational conformation dynamics of putative L-glutaminase YLaM identified from Bacillus licheniformis

ABSTRACT Glutaminases are a unique group of hydrolytic enzymes with potential applications in cancer therapy and the food industry. This study focused on the biological characterisation and computational conformation dynamics of YLaM, a potential L-glutaminase from a halothermotolerant Bacillus licheniformis. The research integrated experimental and computational methods to identify the YLaM sequence and predict its structural and functional properties. YLaM was amplified using a polymerase chain reaction, cloned into a pET-22b(+) vector, sequenced, and submitted to BankIt/NCBI. This experimental work was complemented by in silico analysis, including structural modelling via the I-TASSER web server, molecular docking using AutoDockTools 1.5.6, and molecular dynamic (MD) simulations using GROMACS v5.1.4. The study resulted in the development of a high-quality 3D model of YLaM through homology modelling and structural refinement, enabling a detailed exploration of its binding affinity with L-glutamine (L-Gln). By identifying active site residues using the homotetramer structure of human glutaminase, crucial interactions with L-Gln were validated, confirming its catalytic function. Finally, MD simulations confirmed the stability of the complex under physiological conditions. This combined molecular identification and functional simulations provide comprehensive insights into the physicochemical properties of the enzyme, offering valuable information for subsequent assessments, including recombinant production and biological impact evaluations.

Analysis of magnetic structures in JANA2020.

JANA2020 is a program developed for the solution and refinement of regular, twinned, modulated, and composite crystal structures. In addition, JANA2020 also includes a magnetic option for solving magnetic structures from powder and single-crystal neutron diffraction data. This tool uses magnetic space and superspace symmetry to describe commensurate and incommensurate magnetic structures. The basics of the underlying formulation of magnetic structure factors and the use of magnetic symmetry for handling modulated and non-modulated magnetic structures are presented here, together with the general features of the magnetic tool. Examples of structures solved in the magnetic option of JANA2020 are given to illustrate the operation and capabilities of the program.

The Utilization of Carbonated Steel Slag as a Supplementary Cementitious Material in Cement.

Carbon emission reduction and steel slag (SS) treatment are challenges in the steel industry. The accelerated carbonation of SS and carbonated steel slag (CSS) as a supplementary cementitious material (SCM) in cement can achieve both large-scale utilization of SS and CO2 emission reduction, which is conducive to low-carbon sustainable development. This paper presents the utilization status of CSS. The accelerated carbonation route and its effects on the properties of CSS are described. The carbonation reaction of SS leads to a decrease in the average density, an increase in the specific surface area, a refinement of the pore structure, and the precipitation of different forms of calcium carbonate on the CSS surface. Carbonation can increase the specific surface area of CSS by about 24-80%. The literature review revealed that the CO2 uptake of CSS is 2-27 g/100 g SS. The effects of using CSS as an SCM in cement on the mechanical properties, workability, volume stability, durability, environmental performance, hydration kinetics, and microstructure of the materials are also analyzed and evaluated. Under certain conditions, CSS has a positive effect on cement hydration, which can improve the mechanical properties, workability, bulk stability, and sulfate resistance of SS cement mortar. Meanwhile, SS carbonation inhibits the leaching of heavy metal ions from the solid matrix. The application of CSS mainly focuses on material strength, with less attention being given to durability and environmental performance. The challenges and prospects for the large-scale utilization of CSS in the cement and concrete industry are described.

Effect of hybrid lead-PVA fibers on microstructure and radiation shielding properties of high-performance concrete

With the widespread application of nuclear technology in the medical and energy fields, the demand for efficient radiation shielding materials is increasing. Employing only lead or polyvinyl alcohol (PVA) fiber reinforcement cannot achieve improvements in the brittleness of high-performance concrete (HPC) while also enhancing radiation shielding efficiency and mechanical properties. This study develops a novel HPC for radiation attenuation, incorporating magnetite as the aggregate and reinforced with hybrid lead-PVA fibers (RSHPC). The synergistic effects of various proportions of hybrid lead-PVA fibers on the mechanical properties, three-dimensional microstructure, pore structure, and interfacial transition zone (ITZ) were investigated. In addition, the radiation attenuation capacities of RSHPC with different hybrid lead-PVA fiber proportions were evaluated through experimental and simulation analysis. The results show that hybrid lead-PVA fibers notably improve the air-void structure of RSHPC. The incorporation of PVA fibers, by improving the ITZ of matrix, effectively mitigates the negative impact of lead fibers on mechanical performance. The refinement of pore structure and the introduction of light and heavy nuclides lead to a significant enhancement in the gamma-ray and neutron radiation attenuation capabilities of RSHPC. Utilizing X-ray computed tomography (X-CT) for three-dimensional reconstruction further indicates the optimization impact of hybrid lead-PVA fibers on the microstructure, notably in the improvement of pore distribution and fiber dispersion, thus enhancing the overall properties and radiation attenuation performance of RSHPC.

Structural and magnetic aspects of aluminium substituted dual lanthanum and calcium based hexaferrite nanoparticles for magnetic applications

In the current work, M-type aluminium substituted calcium-lanthanum hexaferrite with chemical formula Ca0.5La0.5Fe12-xAlxO19 (x = 0.00, 0.04, 0.08, 0.12, 0.16) is synthesized by the sol–gel auto combustion method. M-type hexaferrite’s sole-phase crystalline structure was confirmed by X-ray diffraction analysis, which was further used to compute different structural parameters. Structural refinements showed that cell volume decreases from 696.86 Å3 to 692.01 Å3. Moreover, different microstructural parameters are computed, including X-ray density, bulk density, porosity, microstrains and dislocation density. According to VSM analysis, saturation magnetization-(Ms) and remanence magnetization-(Mr) decreased to 17.01 emug−1 and 10.66 emug−1, respectively, while the coercivity increased to 2.165 kOe by increasing the doping concentration to a maximum of x = 0.16. Other magnetic parameters like anisotropy field-(Ha), anisotropy parameter-(B), and magnetocrystalline anisotropy constant-(K), the magnetic moment per formula unit-(µB) were also determined. According to these findings, the synthesized material has excellent potential to be used in magnetic applications.

Nature of Scapolite Color: Ab Initio Calculations, Spectroscopy, and Structural Study

The article describes the results of a comprehensive study of the extra-framework components of scapolites using quantum–chemical calculations, electronic and vibrational spectroscopy, and single-crystal X-ray diffraction and crystal structure refinement. The ab initio calculations were performed using an embedded-cluster approach of extra-framework components in various cation surroundings. As a result, through comparing the experimental and ab initio calculation results, the energies of the electronic and vibrational transitions of various extra-framework components (CO3)2−, (CO3)·−, S3·−, S2·−—as well as the role of these components in the process of the lowering of the symmetry—were determined for scapolites belonging to the marialite–meionite solid–solution series. The nature of the various colors of the scapolites has also been established. Colors from purple to blue are a result of the presence of radiation-induced pairs of defects: carbonate radical anions (CO3)·− and F-centers. However, polysulfide S3·− radical anions are found in some violet scapolites.

New insights from crystallography into the effect of Ni content on ductile-brittle transition temperature of 1000 MPa grade high-strength low-alloy steel

The significant effect of Ni content (0.92, 1.94 and 2.94 wt%) on ductile-brittle transition temperature (DBTT) and microstructure in a 1000 MPa grade high-strength low-alloy (HSLA) steel was studied. Using scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), transmission electron microscopy (TEM), Charpy impact test and low-temperature tensile test to study the fundamental reasons for the effect of Ni content on toughness. The results indicated that increasing the Ni content can reduce the DBTT of HSLA steel and improve the impact toughness at low temperatures. EBSD data post-processing analysis revealed that the key reason for the increase in low-temperature toughness is the refinement of the microstructural crystallographic structure, specifically the significant increase in the boundary density of the block and packet. With the increase of Ni content, the density of grain boundary with an orientation difference greater than 5° between two adjacent {110} crystal planes was higher, which can form a higher density of dislocation pile-up group, thus better reducing local stress concentration. Meanwhile, the stacking fault energy (SFE) increases with the increase of Ni content, which made the screw dislocation more prone to cross slip at low temperature, resulting in an increase in plasticity at low temperatures. These observed phenomena and reasons provided a theoretical explanation for the role of Ni content in reducing DBTT and enhancing the toughness of the core in heavy gauge plates.

Towards end-to-end structure determination from x-ray diffraction data using deep learning

Powder crystallography is the experimental science of determining the structure of molecules provided in crystalline-powder form, by analyzing their x-ray diffraction (XRD) patterns. Since many materials are readily available as crystalline powder, powder crystallography is of growing usefulness to many fields. However, powder crystallography does not have an analytically known solution, and therefore the structural inference typically involves a laborious process of iterative design, structural refinement, and domain knowledge of skilled experts. A key obstacle to fully automating the inference process computationally has been formulating the problem in an end-to-end quantitative form that is suitable for machine learning, while capturing the ambiguities around molecule orientation, symmetries, and reconstruction resolution. Here we present an ML approach for structure determination from powder diffraction data. It works by estimating the electron density in a unit cell using a variational coordinate-based deep neural network. We demonstrate the approach on computed powder x-ray diffraction (PXRD), along with partial chemical composition information, as input. When evaluated on theoretically simulated data for the cubic and trigonal crystal systems, the system achieves up to 93.4% average similarity (as measured by structural similarity index) with the ground truth on unseen materials, both with known and partially-known chemical composition information, showing great promise for successful structure solution even from degraded and incomplete input data. The approach does not presuppose a crystalline structure and the approach are readily extended to other situations such as nanomaterials and textured samples, paving the way to reconstruction of yet unresolved nanostructures.

New insights into the evolution mechanism of mechanical and shrinkage properties of UHPC under sustained sub-elevated temperatures

In this paper, the mechanical properties, damage pattern, mass loss, and drying shrinkage of ultra-high performance concrete (UHPC) under sustained sub-elevated temperatures (60 ℃-200 ℃) are studied. The effect of UHPC mixture, temperature levels and durations are analyzed. The performance evolution mechanism is revealed based on the analysis of hydration products and microstructures. Results show that at 150 ℃, the water loss of C-S-H gel is continuous (>90d). After sustained action at 100 ℃-200 ℃ for 3d or 7d, UHPC shows obvious expansion, which is attributed to the interlayer water evaporation of gel phase causing spacing between the gel sheets. At 60 ℃ and 100 ℃, the strength incresear and the mean chain length (MCL) decrease are associated with the increase in the SiO4 tetrahedron production in the C-S-H gel phase. At 150 °C and 200 °C, the increase of C-S-H gel’s MCL, gel phase stiffening, and pore structure refinement are important reasons for the increase in compressive strength of UHPC.

Enhanced soft magnetic properties with high frequency stability of pure iron powder cores via high-pressure compaction – An environment and cost saving solution as a prospective alternative to soft magnetic composites

The paper presents the analysis of the magnetic behaviour of soft magnetic powder compacts vs. the increasing compacting pressure. An unexpectedly positive result was obtained at a pressure of 1500 MPa, as the pure iron compact without coating of powder particles and without subsequent heat treatment showed very good magnetic properties compared to the class of soft magnetic composites (SMCs). In particular, the effective relative permeability of μeff ∼120, stable up to a frequency f ∼200 kHz, the maximum total relative permeability of μtotmax ∼700, and the specific electrical resistivity of ρR ∼10−5 Ω m. This phenomenon was explained on the basis of analyses of the samples microstructure, the magnetic and electrical properties, magnetization processes, inner demagnetizing fields, Barkhausen noise and thermal diffusivity. It was found that the grain size refinement inside iron particles occurs at certain elevated compaction pressure because the deformation bands gradually rise and break up with compaction pressure, leading to a higher resistivity of the compact thus to its SMC-like behaviour, despite the counteracting effect of increasing number of iron-iron bridges among neighbouring particles. The grain size refinement causes also the refinement of magnetic domain structure, which facilitates the magnetization reversal, although, the increased internal stresses and microstructural defects affect domain wall mobility negatively. The most favourable combination of the mentioned factors influences, finally resulting in the soft magnetic properties enhancement, appeared at 1500 MPa. Due to high-pressure compaction, the high density (above ∼95 % of iron density) of a compact was achieved, ensuring sufficient mechanical properties. The presented material can serve as a potential supplanter of SMCs in many applications as it provides evident advantages, such as its easy production with minimum chemical waste (because any additional chemical processes and substances needed for particle coatings in conventional SMCs are completely omitted), as well as easy recycling process, which makes it eco-friendly and cost-effective, nevertheless, maintaining the advantages of SMCs.

Sketch Beautification: Learning Part Beautification and Structure Refinement for Sketches of Man-Made Objects.

We present a novel freehand sketch beautification method, which takes as input a freely drawn sketch of a man-made object and automatically beautifies it both geometrically and structurally. Beautifying a sketch is challenging because of its highly abstract and heavily diverse drawing manner. Existing methods are usually confined to their limited training samples and thus cannot beautify freely drawn sketches with both geometric and structural variations. To address this challenge, we adopt a divide-and-combine strategy. Specifically, we first parse an input sketch into semantic components, beautify individual components by a learned part beautification module based on part-level implicit manifolds, and then reassemble the beautified components through a structure beautification module. With this strategy, our method can go beyond the training samples and handle novel freehand sketches. We demonstrate the effectiveness of our system with extensive experiments and a perceptual study.

Effect of particle Froude number on sub-grid effective drag, filtered and residual stresses in fluidized gas-particle flows

Sub-grid effective drag, filtered and residual stresses in the meso-scale of gas-particle fluidized flows are intrinsically affected by underlying micro-scale conditions as well as non-local effects related to macro-scale conditions. In this work we applied microscopic two-fluid modeling to experiment with particle Froude number in order to evaluate the impact of this micro-scale condition over the concerning meso-scale derived sub-grid parameters. We performed highly resolved simulations in periodic domains for particle Froude numbers from 12.21 to 799.22, for a wide range of macro-scale conditions. Results were filtered and classified by ranges of meso-scale markers for the various particle Froude numbers. The particle Froude number was found to considerably affect the structural refinement of the heterogeneous flow fields thereby directly impacting effective drag, filtered and residual stresses. All of those parameters showed systematic behaviors in relation to particle Froude number, thereby providing sound data for new sub-grid modeling propositions.

Augmenting microstructure and tribological performance of wire arc additive manufactured PH13-8Mo stainless steel via TiC/TiB2 nano-particles incorporation

This study aimed to investigate the effect of TiC and TiB2 nano-inoculants addition on the microstructure and tribological behavior of PH13-8Mo stainless steel processed through wire arc additive manufacturing (WAAM). The incorporation of TiC/TiB2 inoculants demonstrated notable efficiency in mitigating the anisotropic wear and scratch response and enhancing wear resistance observed in the as-printed state. This improvement was ascribed to the refinement of the grain structure, disruption of the columnar structure, and increased content of the retained austenite. Notably, TiB2 inoculation exhibited superior grain refinement and achieved the highest hardness. However, the TiC-inoculated condition demonstrated the best wear resistance, attributed to its excellent combination of hardness and fracture resistance, and a higher contribution of strain-induced martensite transformation during wear testing. Additionally, the implementation of post-printing solutionizing and aging treatment was found to improve the scratch and wear resistance of the alloy, attributed to the formation of nano-sized β-NiAl precipitates. The main wear mechanism observed involved oxidation wear, adhesive wear, and three-body abrasive wear. The findings of this study highlight the significant potential of incorporating ceramic-based nano-particles for improving the wear resistance of WAAM PH13-8Mo components, particularly in demanding applications like injection molding dies where superior abrasion resistance is paramount.

Rapidly tailor metal–organic frameworks for arsenate removal using graph convolutional neural networks

Metal-organic frameworks (MOFs) are effective materials for the removal of highly toxic arsenates (As(V)). However, the intricate structure–activity relationships of MOFs for As(V) removal remain unclear, thus impeding its targeted fabrication. In this work, we used the graph convolutional neural network to integrate MOFs’ chemical composition, physical structure, and adsorption environment, thereby developing an end-to-end predictive model for As(V) adsorption by MOFs. The model’s high coefficient of determination, low mean absolute error, and experimental verification of MOFs synthesized based on model predictions not previously used in the As (V) adsorption confirmed the precision and general applicability of the model. Our constructed model identified two key features for adsorption, i.e., metal nodes and pore features, and the modular blocks for constructing MOFs. The strategic design for MOFs to absorb As(V) informed by the model, emphasized integrating open single or binuclear metal nets with aromatic di- or tricarboxylic acid linkers within a robust three-dimensional topological net. This work highlights the integration of predictive modeling and structural refinement to enhance MOF design for As (V) adsorption, even in more other pollutants.

A New Spin on Material Properties: Local Magnetic Structure in Functional and Quantum Materials.

The past few decades have made clear that the properties and performances of emerging functional and quantum materials can depend strongly on their local atomic and/or magnetic structure, particularly when details of the local structure deviate from the long-range structure averaged over space and time. Traditional methods of structural refinement (e.g., Rietveld) are typically sensitive only to the average structure, creating a need for more advanced structural probes suitable for extracting information about structural correlations on short length- and time-scales. In this Perspective, we describe the importance of local magnetic structure in several classes of emerging materials and present the magnetic pair distribution function (mPDF) technique as a powerful tool for studying short-range magnetism from neutron total-scattering data. We then provide a selection of examples of mPDF analysis applied to magnetic materials of recent technological and fundamental interest, including the antiferromagnetic semiconductor MnTe, geometrically frustrated magnets, and iron-oxide magnetic nanoparticles. The rapid development of mPDF analysis since its formalization a decade ago puts this technique in a strong position for making continued impact in the study of local magnetism in emerging materials.

Rotherkopfite, KNa2(Fe2+2.5Ti4+1.5)Fe2+(Si4O12)2, a new neptunite-group mineral without essential lithium, from Rother Kopf, Eifel volcanic fields, Germany

Abstract. Rotherkopfite, KNa2(Fe2.52+Ti1.54+)Fe2+(Si4O12)2, is a new member of the neptunite group, from Rother Kopf, Roth, near Gerolstein, Eifel volcanic fields, Rhineland-Palatinate, Germany. It is found in cavities in a quartz–sanidine xenolith embedded in a vesicular alkaline basalt and is associated with fluorophlogopite and an amphibole supergroup mineral that is zoned from potassic-magnesio-fluoro-arfvedsonite on the exterior to potassic-fluoro-richterite in the core. It is presumed to have formed as the result of contact metasomatism of the xenolith by the alkaline basalt melt. Rotherkopfite occurs as brownish-red equant or tabular crystals, up to about 0.2 mm in maximum dimension. The mineral has a light-orange streak, a vitreous lustre, a Mohs hardness of ∼4.5, a brittle tenacity, a curved fracture and a density of 3.20(2) g cm−3. Optically, rotherkopfite crystals are biaxial (+), with α=1.668(5), β=1.678(5), γ=1.720(5) (white light) and 2V(meas) = 53.2(6)°. The empirical formula from electron microprobe analyses, secondary ion mass spectrometry and structure refinement is (K0.87Na0.20)Σ1.07(Na1.99Ca0.01)Σ2.00M1+M2(Fe1.662+Ti1.48Mg0.79Mn0.02)Σ3.95M3(Fe0.642+Li0.16Ti0.15Al0.01)Σ0.96(Si8.00O24). Rotherkopfite is monoclinic with space group C2/c and unit-cell parameters a=16.4599(17), b=12.5457(6), c=10.0487(7) Å, β=115.669(7)°, V=1870.3(3) Å3 and Z=4. The crystal structure (R1=0.0268 for 1324 reflections with I>2σI) is based on two interwoven three-dimensional frameworks: (1) a silicate framework made up of pyroxene-like chains of corner-sharing SiO4 tetrahedra and (2) an octahedral framework made up of chains of edge-sharing metal–oxygen octahedra. The two interwoven frameworks are bound to one another by corner sharing. K and Na are hosted in channels in the combined framework.

Microwave assisted preparation of ternary scheelite CaMoO4: Er3+/Yb3+ nano-phosphors for up/down-conversion photoluminescence, temperature sensing and antibacterial properties

Due to their exceptional intrinsic optical characteristics, molybdate compounds have aroused significant attention in recent years for their effective up and downconversion luminescence. In the present study, a series of xEr3+/Yb3+ (x = 0.5 %, 1 %, 2 %, 4 % and Yb3+ =15 %) doped CaMoO4 nanophosphors synthesized through a microwave assisted approach and subsequently the comprehensive analysis of the functionalities such as optical properties, antibacterial traits and their integration with temperature sensing, have been explored. Furthermore, the structural refinement confirms the occurrence of tetragonal scheelite phase of the prepared materials. The morphology of the material was identified by FE-SEM and HR-TEM analysis which reveals particles are in spherical shape. Up-conversion luminescence intensities were found to be dependent on doping concentration, laser excitation power and external temperature upon 980 nm light excitation. The temperature sensing response of the optimized sample was examined based on intensity ratio of two emission bands that involves thermally connected energy levels of Er3+ ion. The maximum absolute sensitivity of 10.74 × 10−3 K−1 (at 500 K) was found, demonstrating its potential application in high temperature thermometry. The comprehensive analysis and the outcome of the present study suggests the potential prospect of the as-synthesized material in food preservation, medical equipment, water treatment, and as an optical coating agent for solid state luminous devices.

Short-range order structural response of CdSe nanocrystals under 120 MeV swift heavy ions irradiation: A pair distribution function analysis

Swift heavy ion (SHI) irradiation deposits large amount of energy in the target material which thereby influences the structural features of the sample. In this work, the structural response of CdSe material has been studied under high energetic 120 MeV SHI irradiation. The long-range structural modifications of CdSe under SHI have been analyzed using Rietveld study. On the other hand, the short-range behavior of SHI irradiated CdSe has been studied using Pair distribution function (PDF), which can be interpreted as a distance map between two atoms in terms of a PDF peak. The small-box structural refinement of the samples has been performed using the PDFgui package for the study of modifications in the atomic arrangement after the SHI irradiation. In addition to this, structural characteristics such as unit cell parameters as determined from long-range (Rietveld) refinement are compared to that obtained from short-range (small-box) refinement. Moreover, atomic displacement factor for CdSe also has been determined to study the atomic disorder in the nanocrystal under the influence SHI irradiation. Finally, impact of SHI induced stress generated on the CdSe sample and its influence also has been studied based on the width of the PDF peak.

Achieving a superior combination of strength and ductility by adjusting heterogeneous structure in a Fe–Mn–Al–Mo–C lightweight steel

A combination of high strength and good ductility was achieved by adjusting heterogeneous structure through varying annealing temperatures ranging from 750 to 900 °C after cold rolling in a Fe–Mn–Al–Mo–C lightweight steel. The microstructure consists of heterogeneous recrystallized, unrecrystallized grains containing nanoscale Mo2C precipitates, and intergranular Mo-enriched carbides. As annealing temperature increases, the fraction of recrystallization, and the average Schmid factor increase, while the average grain sizes and the volume fraction of Mo2C decrease. Annealing at 825 °C forms a desirable heterogeneous structure characterized by a normal bimodal grain distribution and diffuse precipitation of intragranular Mo2C particles. Tensile test results indicated that higher annealing temperatures decrease strength but enhance ductility. However, the yield strength of the 825 °C annealed sample only slightly decreases compared to the 800 °C annealed sample owing to the synergistic contributions of various strengthening mechanisms, including grain boundary, solid solution, precipitation, and heterogeneous deformation-induced strengthening. Furthermore, its ductility significantly improves, approaching that of the 850 °C annealed sample, facilitated by sustained heterogeneous deformation-induced strengthening effects and significant refinement in grain structure. The high strain hardening rate of the C825 sample is attributed to dynamic slip band refinement and local stress adjustments during later deformation stages. The heterogeneous grain structure induces a strong HDI strengthening effect due to uneven deformation, which also contributes to the high strain hardening rate. These findings highlight the potential of Fe–26Mn–8Al-1.2C–3Mo lightweight steel for applications requiring a balance of strength and ductility.