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At least 1,243 records · Page 69

Microstructure, compression properties, and oxidation behavior of Hf-25Ta-5Me alloys (Me is Mo, Nb, W, 0.5Mo + 0.5 W, Cr, or Zr)

Hf–Ta based alloys have recently been investigated as potential candidates for high-temperature structural applications. While most attentions have been given to the properties above ~1200 °C where the alloys are mainly single-phase BCC structures and have excellent oxidation performance due to formation of super-oxides, structural properties at lower temperatures are equally important for applications in which an alloy may experience a range of temperatures. In the present work, microstructure, phase composition, mechanical properties and oxidation behavior of six Hf-25Ta-5Me alloys (Me is Mo (HTM alloy), W (HTW), 0.5Mo + 0.5 W (HTMW), Cr (HTC) or Zr (HTZ), the compositions are in at.%) are reported at temperatures below the eutectoid transformation. The alloys were prepared by arc melting followed by hot isostatic pressing for 3 h at 1400 °C and 207 MPa. All the alloys display coarse grains of partially or fully transformed (by a eutectoid reaction) high-temperature BCC phase. The eutectoid regions consist of fine lamellae of Hf-rich HCP and Ta-rich BCC phases. The ternary alloys containing W or Cr also contained small amounts of a cubic Laves phase. At 25 °C, the HTW alloy was the strongest (yield stress σ y = 1966 MPa) but brittle and HTZ was the weakest (σ y = 1120 MPa) but ductile among the studied alloys. Other alloys showed intermediate behaviors. In general, the room temperature ductility of the alloys increased with decreasing σy. All alloys maintained high strength up to 800 °C, but displayed a noticeable strength decrease at 1000 °C. At 1000 °C, HTMW was the strongest alloy (σ y = 468 MPa) and HTC was the weakest alloy (σ y = 368 MPa). All alloys had excellent deformability at 1000 °C. Oxidation behavior of the alloys was studied at 800 °C and 1000 °C and compared with that of Hf–27Ta binary alloy. Although the ternary additions improved oxidation resistance, overall oxidation performance of the studied alloys at 800 °C and 1000 °C was poor.

36 MATERIALS SCIENCE↗

Alloy designs for high temperature Mo-base systems

For high temperature applications Mo base alloy requirements include both superior structural performance and environmental resistance. To address these requirements alloys in the Mo-Si-B system and refractory multi-principal element alloys (RMPEA) are being developed that exhibit a promising potential, but also have some remaining challenges to improve ductility, lower density and enhance environmental resistance. In the Mo-Si-B system microstructures with a Mo solid solution (Moss) Mo 3 Si and Mo 5 SiB 2 (T2) phases have been the focus of attention. However, the Si solubility in the Moss phase diminishes the ductility and toughness. In order to address this issue a new design based upon Moss, Mo 2 B and T 2 phases lowers the Si solubility in the Moss to improve ductility while the T 2 phase maintains the oxidation performance. Selected additions of Al and Ti enable a density reduction to below 8 g/cm 3 . The RMPEA designs for Mo-rich alloys provide for excellent structural performance, but the complex oxidation products provide no protection. However, in this case a new coating design has been introduced that provides the required environmental resistance.

36 MATERIALS SCIENCE↗

Influence of rolling reduction and annealing on recrystallization and grain structure in Ta-2.5W alloys

The microstructural evolution of wrought Tantalum - 2.5 wt% Tungsten (Ta-2.5W) alloys during thermomechanical processing is critical for optimizing their mechanical reliability in demanding applications such as aerospace, chemical processing, and nuclear technology. Despite the widespread use of Ta-W alloys, a comprehensive understanding of how rolling reduction, annealing temperature, and elemental inhomogeneity interact to determine recrystallization behavior and grain refinement remains incomplete. Here, in this study, we systematically investigate the effects of cold rolling and subsequent annealing on the microstructure of Ta-2.5W, with particular attention to grain orientation, stored energy, and elemental banding. Our results demonstrate that higher rolling reduction rates lower the onset and completion temperatures for recrystallization, resulting in finer and more homogeneous grain structures. Electron backscatter diffraction (EBSD) analysis reveals that grains with a 〈111〉 parallel to the plate normal possess higher stored energy and nucleate recrystallization more readily than grains with a 〈001〉 parallel to the plate normal. Elemental mapping shows that tungsten inhomogeneity leads to localized bands of accelerated recrystallization and hardness variation. These findings provide new insights into the mechanisms of microstructure refinement in Ta-2.5W alloys, offering guidance for tailoring processing routes to achieve superior performance in demanding engineering environments.

Annealing↗

Critical review of the Mogi failure criterion based on true-triaxial laboratory data analysis and theoretical considerations

The influence of the intermediate principal stress, σ 2 , is disregarded when rock strength is analyzed using the Mohr-Coulomb or Hoek-Brown criteria. Several polyaxial strength criteria have been proposed to account for the influence of σ 2 . One of the methods that received considerable attention is the Mogi criterion. The criterion modifies the Nadai or Drucker-Prager approaches by exchanging the normal octahedral stress with what is introduced as the mean effective stress, σ m,2 . This change is based on experimental evidence that the influence of the intermediate principal stress on strength is less pronounced than the influence of the minimum principal stress. However, the Mogi criterion was derived somewhat empirically and consequently it is essential to analyze its potential theoretical deficiencies. In the current note, we analyzed the Mogi failure criterion, describing its characteristics in both τ oct –σ m,2 and σ 1 -σ 2 spaces. We investigated the relation between Mohr-Coulomb and Mogi criteria, which marks the basis for the commonly used Mogi-Coulomb approach. Here, we compared the performance of the Mogi criterion against available polyaxial strength data using three fitting approaches: Mogi-Coulomb based on triaxial compression results only, linear Mogi based on all polyaxial strength results, and power law Mogi also based on all data. The analysis reveals several serious deficiencies of the Mogi approach which all suggest that the Mogi criterion cannot properly represent the σ 2 dependence of rock strength in many cases.

58 GEOSCIENCES↗

Comparative verification of hydro-mechanical fracture behavior: Task G of international research project DECOVALEX–2023

Numerical simulations become a necessity when experimental approaches cannot cover the required physical and time scale of interest. One of such area is a simulation of long-term host rock behaviors for nuclear waste disposal and simulation tools involved in the assessment must go through rigorous validation tests. The DECOVALEX project (Development of COupled models and their VAlidation against EXperiments) is dedicated to this purpose by international participants. This work is part of the ongoing phase DECOVALEX–2023 (D–2023, Task G) particularly aiming to simulate fracture behaviors under various conditions. Here, in this study, we cross-verified a variety of numerical methods including continuous and discontinuous approaches against four benchmark exercises with emphasis on numerical accuracy and parameterization of the various numerical approaches. The systematic inter-comparisons of test cases highlight advantages and disadvantages of the different numerical models. Numerical details on discretization effects (e.g. mesh density and orientation) and domain size were investigated in detail for practical applications. It became evident that meticulous attention to mesh resolution and domain size is imperative for achieving accurate numerical simulations, even for static cracks. Moreover, when comparing numerical methods to closed-form solutions for static cracks, all models successfully reproduced the maximum crack opening but encountered challenges near the crack tips. Finally, the paper discusses how to convert between and therefore compare parameters of various numerical approaches. Our benchmark studies reveal that each model necessitates a distinct number of parameters, even in simple scenarios like static crack aperture benchmarks. It is generally more practical to employ fewer parameters to mitigate model over-parameterization and enhance experimental feasibility.

58 GEOSCIENCES↗

Hypofractionated Radiation Therapy for Breast Cancer: Financial Risk and Expenditures in the United States, 2008 to 2017

Rising cancer care expenditures and technological advancement of shorter radiation therapy regimens have drawn significant attention to the use of hypofractionated radiation therapy in clinical care. We examine the costs of hypofractionated whole breast irradiation (HF-WBI) compared with conventional whole breast irradiation (CF-WBI) in the United States and investigate the influences of patient characteristics and commercial insurance on HF-WBI use.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Tailoring Cu-Zr gradient nanoglass structures: Influence of nanoparticle size and cooling rates on glass-glass interfaces

The study of gradient nanoglasses (GNGs) has gained attention due to their unique mechanical properties and potential applications in advanced materials. This study employs molecular dynamics simulations to synthesize a GNG using Cu-Zr metallic glass nanoparticles (NPs) sized from 3 to 15 nm. The NPs were produced by melting and quenching metallic clusters at a relatively slow quench rate of 10 9 K/s. The synthesis of GNG is elucidated along with the characterization of its heterogeneous metallic glass nanostructure. A seamless GNG structure is formed through cold compression of Cu 64 Zr 36 amorphous NPs of varying sizes. The influence of NP size on the GNG structure is investigated, utilizing deeply relaxed NPs, which exhibit a characteristic Cu segregation pattern on their surfaces. The results highlight an increase in structural heterogeneity due to heterogeneous mass transport and the development of local composition and density variations caused by Cu segregation at glass-glass interfaces (GGIs). A reduction in NP size is correlated with decreased Cu atomic displacements and local density at GGIs, suggesting that larger NPs may produce stronger GGIs. This research presents a novel methodology for synthesizing heterogeneous metallic glasses, demonstrating the capacity to control and customize nanostructure heterogeneity through the manipulation of NP sizes and cooling rates. Furthermore, these findings enhance our understanding of structural evolution during nanoglass synthesis and lay the foundation for further exploration in nanomaterial synthesis and characterization.

36 MATERIALS SCIENCE↗

Creep behavior of high-entropy alloys: A critical review

High-entropy alloys (HEAs) have been extensively investigated during the last two decades. While substantial progress has been made in understanding their phase stability, microstructure, and deformation mechanisms at room and cryogenic temperatures, the long-term creep behavior (>100 h) of HEAs at high temperatures (>0.6 T m , where T m is the melting temperature) remains relatively underexplored. This knowledge gap is critical, as many engineering applications, including those for power generation and propulsion, require materials with good creep resistance to maintain structural integrity over extended service lifetimes. This review provides a focused and critical assessment of the current understanding of high-temperature deformation and creep behavior of HEAs, with particular attention paid to face-centered cubic HEAs and body-centered cubic refractory HEAs. The underlying deformation mechanisms governing their creep response and the influence of phase stability at elevated temperatures are examined in detail. Recent studies reveal mechanistic differences between HEAs and conventional dilute alloys that do not always lead to improved creep resistance belying their initial promise. Based on these findings, we discuss the challenges in designing HEAs for high-temperature structural applications and outline future research directions that may lead to creep-resistant HEAs.

Creep↗

Modeling nuclear energy’s future role in decarbonized energy systems

Increased attention has been focused on the potential role of nuclear energy in future electricity markets and energy systems as stakeholders target rapid and deep decarbonization and reductions in fossil fuel use. This paper examines models of electric sector planning and broader energy systems optimization to understand the prospective roles of nuclear energy and other technologies. In this perspective, we survey modeling challenges in this environment, illustrate opportunities to propagate best practices, and highlight insights from the deep decarbonization literature on the range of visions for nuclear energy's role. Nuclear energy deployment is highest with combinations of stringent emissions policies, nuclear cost reductions, and constraints on the deployment of other technologies, which underscores model dimensions related to these areas. New modeling capabilities are needed to adequately address emerging issues, including representing characteristics and applications of nuclear energy in systems models, and to ensure the relevance of models for policy and planning as deeper decarbonization is explored.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

From Tg O/GABA-AT, GABA, and T-263 Mutant to Conception of Toxoplasma

Toxoplasma gondii causes morbidity, mortality, and disseminates widely via cat sexual stages. Here, we find T. gondii ornithine aminotransferase (OAT) is conserved across phyla. We solve TgO/GABA-AT structures with bound inactivators at 1.55 Å and identify an inactivator selective for TgO/GABA-AT over human OAT and GABA-AT. However, abrogating TgO/GABA-AT genetically does not diminish replication, virulence, cyst-formation, or eliminate cat’s oocyst shedding. Increased sporozoite/merozoite TgO/GABA-AT expression led to our study of a mutagenized clone with oocyst formation blocked, arresting after forming male and female gametes, with “Rosetta stone”-like mutations in genes expressed in merozoites. Mutations are similar to those in organisms from plants to mammals, causing defects in conception and zygote formation, affecting merozoite capacitation, pH/ionicity/sodium-GABA concentrations, drawing attention to cyclic AMP/PKA, and genes enhancing energy or substrate formation in TgO/GABA-AT-related-pathways. These candidates potentially influence merozoite’s capacity to make gametes that fuse to become zygotes, thereby contaminating environments and causing disease.

59 BASIC BIOLOGICAL SCIENCES↗

Decrease in multiple complement proteins associated with development of islet autoimmunity and type 1 diabetes

Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic ß-cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies - biomarkers of autoimmunity – is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through diagnosis. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D are complement deficient relative to those who do not progress within a similar timeframe. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.

59 BASIC BIOLOGICAL SCIENCES↗

Carbon quantum dots interfacial modified graphene/silicon Schottky barrier solar cell

The two-dimensional thin film, as an effective interface modification layer to improve the power conversion efficiency (PCE) of graphene/silicon (Gr/Si) heterojunction solar cells has attracted extensive attention recently. However, the complicated manufacturing process and specialized equipment requirements impede its broad application. Herein, carbon quantum dots (CQDs) fabricated under the mild reaction condition was first time used to modify Gr/Si devices interface structure. The effects of CQDs size distributions and coating thickness on J-V characteristics and the energy band structure of Gr/CQDs/Si solar cells were systematically analyzed. The findings indicate that the PCE of resulting Gr/CQDs/Si solar cells could reach 9.97% when the thickness and sizes of CQDs interlayer are ~26 nm and 4–7 nm, without any chemical doping, which is 6.8-times PCE than that of virgin Gr/Si solar cells. The CQDs interlayer serves as both an electron blocking layer and hole transport layer to reduce the carrier recombination, leading to a lower reverse saturation current as well as a larger VOC then improved the device performance. The enhanced PCE shows that the CQDs species have the potential applications in a cost-effective photovoltaic device.

14 SOLAR ENERGY↗

Experimental investigation and thermodynamic modeling of the binary Pt–Sn system

Here, the thermodynamics of the Pt–Sn system is revisited with attention to phase equilibria involving PtSn 4 , a topological quantum material with interesting physical properties. The phase relationship in the Sn-rich region of the Pt–Sn binary system was investigated by a combination of differential scanning calorimetry and equilibration experiments. Based on the present experiments and a critical evaluation of the available thermodynamic and phase diagram data reported in the literature, thermodynamic assessments of the entire Pt–Sn system were performed using the CALPHAD approach. Two sets of thermodynamic parameters were optimized, where the liquid phase was described using the Bragg-Williams random mixing model and the associate solution model, respectively. The modeling results are compared with the reliable experimental data and are shown to provide good representations of the phase equilibria and thermodynamic properties in this system.

36 MATERIALS SCIENCE↗

Elucidating the structural properties and reversible regional texture effect of GdB 6 under high pressure

As hard and refractory materials with high chemical resistance and mechanical strength, lanthanide hexaborides (LnB 6 ) have attracted much attention. Among the family of LnB 6 , gadolinium hexaboride (GdB 6 ) occupies a special position due to the half-filled 4f shell of Gd. Here, using in situ synchrotron radiation angle-dispersive X-ray diffraction in a diamond anvil cell at room temperature, the structural stability and compression behavior of GdB 6 are investigated extensively, GdB 6 is observed to be structurally stable up to 73 GPa, and the bulk modulus of 177 GPa is obtained under hydrostatic compression. In this paper, an interesting observation of pressure-induced spotty diffraction rings of GdB6 is reported, its formation mechanism can be well described by the reversible regional texture effect, which highlights the rearrangement of crystal grains under high pressure. The rearrangement mechanism has been well explained by investigating the pressure dependence of full width at half maximum, macro-differential stress and grain size. Collective grain rotation behavior motivated by stress difference is critical for the rearrangement process, the strong isotropy and strong stability of GdB 6 structure also provide necessary conditions for high-pressure grain rotation behavior. These results will help to promote the understanding of high-pressure structural properties of GdB 6 , and provide novel insights on the high-pressure grain behavior in hard materials with strong isotropy and three-dimensional skeleton constituted of strong covalent bonds.

36 MATERIALS SCIENCE↗

Re-investigation of high-temperature phase equilibria in Fe-rich Sm–Fe–Ti alloys

Recently renewed attempts to develop high-performance rare-earth-lean permanent magnets based on the Sm(Fe,Ti) 12 compound have drawn attention to the limited knowledge about the high-temperature phase equilibria in the Sm–Fe–Ti system. Experimental investigation of equilibrated alloys with electron probe microanalysis, X-ray diffraction and thermomagnetic analysis revealed several inaccuracies in the currently accepted phase relations at 1000°C and allowed for a revision of the Fe-rich corner of the Sm–Fe–Ti phase diagram. The Sm(Fe,Ti) 12 and Sm 3 (Fe,Ti) 29 phases were found to have more extended Ti ranges of 5.1–9.7 at% and 2.8–6.9 at%, respectively. With increasing of the Ti content, the Curie temperature of the Sm(Fe,Ti) 12 remains nearly constant at 306–312°C, whereas that of the Sm 3 (Fe,Ti) 29 increases from 188°C to 207°C. The low-titanium Sm 3 (Fe,Ti) 29 phase equilibrates not only with the Sm(Fe,Ti) 12 and Sm2(Fe,Ti) 17 phases, but also with (α-Fe) solid solution. Newly demonstrated equilibrium between Sm 2 (Fe,Ti) 17 and TiFe 2 phases makes impossible the earlier reported equilibrium between the Sm 3 (Fe,Ti) 29 and Sm(Fe,Ti) 11 phases. Because of an invariant reaction at 1000 °C, the revised phase diagram also features a class II four-phase equilibrium Sm 3 (Fe,Ti) 29 + TiFe 2 + Sm(Fe,Ti) 12 + Sm 2 (Fe,Ti) 17 . Peritectic decomposition of the Sm(Fe,Ti) 11 phase, which occurs either at 1075°C or at 1087°C, was found to have among its products the Sm(Fe,Ti) 12 phase. Although no such equilibration was attempted, it must be possible to obtain above 1087°C a two-phase state composed of the Sm(Fe,Ti) 12 phase and a liquid – which is important for manufacturing of the Sm(Fe,Ti) 12 - based permanent magnets via the liquid-phase sintering.

36 MATERIALS SCIENCE↗

Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types

In the last decade, the widespread adoption of electronic health record documentation has created huge opportunities for information mining. Natural language processing (NLP) techniques using machine and deep learning are becoming increasingly widespread for information extraction tasks from unstructured clinical notes. Disparities in performance when deploying machine learning models in the real world have recently received considerable attention. In the clinical NLP domain, the robustness of convolutional neural networks (CNNs) for classifying cancer pathology reports under natural distribution shifts remains understudied. In this research, we aim to quantify and improve the performance of the CNN for text classification on out-of-distribution (OOD) datasets resulting from the natural evolution of clinical text in pathology reports. We identified class imbalance due to different prevalence of cancer types as one of the sources of performance drop and analyzed the impact of previous methods for addressing class imbalance when deploying models in real-world domains. Our results show that our novel class-specialized ensemble technique outperforms other methods for the classification of rare cancer types in terms of macro F1 scores. We also found that traditional ensemble methods perform better in top classes, leading to higher micro F1 scores. Based on our findings, we formulate a series of recommendations for other ML practitioners on how to build robust models with extremely imbalanced datasets in biomedical NLP applications.

60 APPLIED LIFE SCIENCES↗

Process mining for healthcare: Characteristics and challenges

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

59 BASIC BIOLOGICAL SCIENCES↗

Arm and shoulder muscle segmentation in axial MRI with UNet deep learning model

Quantifying individual upper-limb muscle volumes from MRI provides key insight into muscle-specific strength, deficits, and adaptations. Manual delineation is the gold standard but time‑intensive, and the performance of current deep learning approaches, particularly for small or anatomically complex muscles, remains incompletely characterized. We evaluated a state‑of‑the‑art deep learning framework across the entire upper limb and analyzed factors governing segmentation performance, with attention to the forearm. Three previously published MRI datasets (1.5 T, 3D GRE T1‑weighted; total n = 39) spanning young, middle‑aged, and older adults were curated and quality‑checked, including expert manual segmentations for 31 muscles. Following multiclass mask reconstruction, we trained three 3D nnU‑Net multiclass models matched to the muscle subsets present across datasets, using five‑fold cross‑validation and a composite Dice Similarity Coefficient (DSC) + cross entropy loss. Segmentation accuracy was assessed with DSC. Performance varied across muscles (mean DSC = 0.806 ± 0.098), ranging from 0.920 (Deltoid) to 0.461 (Extensor pollicis brevis). In uncertainty‑weighted regressions, muscle volume was positively associated with DSC (R2 = 0.36, p < 0.001), whereas training segmentation count and muscle orientation showed negligible associations (R2 ≤ 0.06). A weighted mixed‑effects model identified volume as the strongest evaluated predictor, explaining 23.9% of variance in DSC; orientation and training count each contributed <1%, leaving 61.5% unexplained. These results indicate that deep learning–based segmentation can accurately quantify muscle volume for many upper‑limb muscles but remains constrained for small, low‑contrast forearm muscles.

Gillespie, Samuel↗