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In this work, predictions from Gibbs Ensemble Monte Carlo simulations on the vapor liquid phase equilibria properties of 10 different binary mixtures of the components, carbon dioxide, 2,3,3,3-tetrafluoropropene (R-1234yf), cis-and trans-1,3,3,3-tetrafluoropropene [R-1234ze(Z/E)], cis- and trans-1,1,1,4,4,4-hexafluorobut-2-ene [R-1336mzz(Z/E)], and trans-1-chloro-3,3,3-trifluoroprop-1-ene [R-1233zd(E)], are presented. For seven of these mixtures, the simulation results represent the first information on their phase behavior, addressing gaps in the existing data on potential HFO-based refrigerant blends. The simulation results together with available experimental data were then used to derive parameters for the multifluid modeling of these mixtures. Different variants of the multifluid model, i.e., predictive mixing rules as well as different parametrizations of the adjustable parameters, are evaluated by assessing their performance in reproducing bubble and dew point lines, as well as saturated densities.

Metallurgical production traditionally involves three steps: extracting metals from ores, mixing them into alloys by liquid processing and thermomechanical processing to achieve the desired microstructures1,2. This sequential approach, practised since the Bronze Age, reaches its limit today because of the urgent demand for a sustainable economy2–5: almost 10% of all greenhouse gas emissions are because of the use of fossil reductants and high-temperature metallurgical processing. Here we present a H2-based redox synthesis and compaction approach that reforms traditional alloy-making by merging metal extraction, alloying and thermomechanical processing into one single solid-state operation. We propose a thermodynamically informed guideline and a general kinetic conception to dissolve the classical boundaries between extractive and physical metallurgy, unlocking tremendous sustainable bulk alloy design opportunities. We exemplify this approach for the case of Fe–Ni invar bulk alloys6,7, one of the most appealing ferrous materials but the dirtiest to produce: invar shows uniquely low thermal expansion6,8,9, enabling key applications spanning from precision instruments to cryogenic components10–13. Yet, it is notoriously eco-unfriendly, with Ni causing more than 10 times higher CO2emission than Fe per kilogram production2,14, qualifying this alloy class as a perfect demonstrator case. Our sustainable method turns oxides directly into green alloys in bulk forms, with application-worthy properties, all obtained at temperatures far below the bulk melting point, while maintaining a zero CO2footprint.

The controlled synthesis of nanoparticles with tailored shapes and morphologies has garnered significant attention, driven by the ever-growing demand for advanced materials with defined properties. In nanoparticle formation, various parameters influence the final product, and among these, the solvent plays a pivotal role, as it constitutes the major component of the reaction medium. In this work, the critical role of solvents in controlling the growth of zinc oxide (ZnO) nanoparticles was investigated, with a focus on simple primary alcoholic solvents as the reaction medium. A model reaction based on the direct solvolysis of anhydrous zinc acetylacetonate was employed to probe the influence of different primary alcohols, specifically methanol, ethanol, and their mixture. A substantial difference in the preferential growth direction of the ZnO nanocrystals in methanol and ethanol was observed through XRD and was further proven through TEM. Thereby, in ethanol, a preferential growth in the [001] direction was observed, resulting in short nanorods as primary particles, while this growth was inhibited in methanol, leading to platelet- or sheet-like primary particles. To unravel the underlying mechanisms responsible for the observed solvent-dependent variations, molecular dynamics (MD) simulations were employed using an optimized interface force field to model the ZnO-alcohol interaction. These simulations provide valuable insights into the preferential adsorption of the solvent molecules onto the polar (0001) and (0001̅) and nonpolar (101̅0) ZnO surfaces, shedding light on the fundamental interactions driving the shape control phenomenon. Essentially, the experimental observations on primary particle morphology could be explained well by the adsorption behavior determined by the MD simulations. Furthermore, this report provides an extensive comparison with various similar reaction systems for ZnO synthesis, deriving correlations with the findings from the model system. These insights contribute to a deeper understanding of the intricate interplay between solvent properties and nanoparticle growth, offering a valuable toolkit for designing and optimizing the synthesis of ZnO nanoparticles with specific shapes and functionalities.

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We study the dynamical behavior of medium-size multimode VCSELs with an elliptical oxide aperture, selected for the best trade-off between high output power and modulation speed for datacom applications, with a focus on their relative intensity noise (RIN) performance. Our experimental results, collected for various VCSELs, outline the presence of several peaks in the RIN spectra within the bandwidth of the transmission system, which can limit the eye opening under direct current modulation. Here, we present a rigorous model to explain for the first time the origin of these peaks. In particular, the frequencies of the spectral RIN peaks are analytically described as the result of the non-trivial interaction among transverse modes by addressing the laser dynamics and the related noise features through a time-domain mode expansion approach, accounting for coherent effects in multimode competition, spatial hole burning, and carrier diffusion. The laser modulation performance is addressed through dynamical simulations with PAM2 and PAM4 modulations, which clearly demonstrate the potential for high-bitrate optical interconnects. Finally, we address the effect of the oxide aperture aspect ratio via electromagnetic simulations, demonstrating how the ellipticity affects the modal frequency detuning and the RIN, thus providing design guidelines for VCSELs with low RIN performance and outlining a clear roadmap for a substantially improved bandwidth-power trade-off in these devices.

Human intelligence and human consciousness emerge gradually during the process of cognitive development. Understanding this development is an essential aspect of understanding the human mind and may facilitate the construction of artificial minds with similar properties. Importantly, human cognitive development relies on embodied interactions with the physical and social environment, which is perceived via complementary sensory modalities. These interactions allow the developing mind to probe the causal structure of the world. This is in stark contrast to common machine learning approaches, e.g., for large language models, which are merely passively “digesting” large amounts of training data, but are not in control of their sensory inputs. However, computational modeling of the kind of self-determined embodied interactions that lead to human intelligence and consciousness is a formidable challenge. Here, we present Multimodal Infant Model (MiMo), an open-source multimodal infant model for studying early cognitive development through computer simulations. MIMo's body is modeled after an 18-month-old child with detailed five-fingered hands. MIMo perceives its surroundings via binocular vision, a vestibular system, proprioception, and touch perception through a full-body virtual skin, while two different actuation models allow control of his body. We describe the design and interfaces of MIMo and provide examples illustrating its use.

Women are born with all of their oocytes. The oocyte proteome must be maintained with minimal damage throughout the woman’s reproductive life, and hence for decades. Here we report that oocyte and ovarian proteostasis involves extreme protein longevity. Mouse ovaries had more extremely long-lived proteins than other tissues, including brain. These long-lived proteins had diverse functions, including in mitochondria, the cytoskeleton, chromatin and proteostasis. The stable proteins resided not only in oocytes but also in long-lived ovarian somatic cells. Our data suggest that mammals increase protein longevity and enhance proteostasis by chaperones and cellular antioxidants to maintain the female germline for long periods. Indeed, protein aggregation in oocytes did not increase with age and proteasome activity did not decay. However, increasing protein longevity cannot fully block female germline senescence. Large-scale proteome profiling of ~8,890 proteins revealed a decline in many long-lived proteins of the proteostasis network in the aging ovary, accompanied by massive proteome remodeling, which eventually leads to female fertility decline.

The decision to treat an incidental finding in an asymptomatic patient results from careful risk-benefit consideration and is often challenging. One of the main aspects is after how many years the group who underwent the intervention and faced the immediate treatment complications will gain a treatment benefit over the conservatively managed group, which maintains a lower but ongoing risk. We identify a common error in decision-making. We illustrate how a risk-based approach using the classical break-even point at the Kaplan-Meier curves can be misleading and advocate for using an outcome-based approach, counting the cumulative number of lost quality-adjusted life years instead. In clinical practice, we often add together the yearly risk of the natural course up to the time point where the number equals the risk of the intervention and assume that the patient will benefit from an intervention beyond this point in time. It corresponds to the crossing of the Kaplan-Meier curves. However, because treatment-related poor outcome occurs at the time of the intervention, while the poor outcome in the conservative group occurs over a given time period, the true benefit of retaining more quality-adjusted life years in the interventional group emerges at a much later time. To avoid overtreatment of patients with asymptomatic diseases, decision-making should be outcome-based with counting the cumulative loss of quality-adjusted life years, rather than risk-based, comparing the interventional risk with the ongoing yearly risk of the natural course.

It is unknown whether decompressive craniectomy improves clinical outcome for people with spontaneous severe deep intracerebral haemorrhage. The SWITCH trial aimed to assess whether decompressive craniectomy plus best medical treatment in these patients improves outcome at 6 months compared to best medical treatment alone.

Fish movements and distributions throughout an ecosystem are important for understanding ecological interactions, conservation, and management. Coarse woody habitat (CWH) additions are a popular habitat enhancement tool that can influence movements and distributions of fishes; however, behavioral responses in relation to CWH additions are understudied. The objectives of our study were to test for changes in habitat use and behavioral responses of Muskellunge Esox masquinongy, Smallmouth Bass Micropterus dolomieu, and Walleye Sander vitreusto CWH additions in a small inland northern lake over 3 years and to evaluate two common forms of fish tracking to estimate daily movement of these fishes. We used passive integrated transponder tag data collected continuously at 10 littoral sites and radiotelemetry data collected biweekly during the summer–fall months prior (2017) and following (2018–2019) CWH addition to examine movement behaviors and estimate daily probability of movement for the three species among lake habitats using multistate models. Walleye were the most likely to remain near CWH, followed by Smallmouth Bass and Muskellunge. All species were more likely to move away from the modified and unmodified littoral zones and were more likely to remain in the offshore zone. Increased movement of fish may be in response to CWH creating a refuge for forage fish and subsequent increases in prey search times. Our results suggest that CWH additions may alter established species‐specific annual movements, distributions, and habitat use to differing degrees in ecosystems, as our results differ from other CWH studies. Methodologically, radio‐tagging was most effective for offshore tracking but most labor intensive. Novel passive integrated transponder arrays (less labor intensive once installed) worked well to monitor movement between habitat types in shallow littoral areas. Long‐term monitoring of behavioral changes will be essential to assessing the stability changes caused by these habitat alterations. Impact statementRadio‐tagged and PIT‐tagged Muskellunge, Smallmouth Bass, and Walleye increased movement among habitats after a littoral zone coarse woody habitat addition in a north temperate lake. Radio‐tagged and PIT‐tagged Muskellunge, Smallmouth Bass, and Walleye increased movement among habitats after a littoral zone coarse woody habitat addition in a north temperate lake.

Künstliche Intelligenz (KI) kann zur Entwicklung von Materialien unter Einbeziehung ihrer Herstellung, Verarbeitung, inneren Strukturdefekte und chemischen Komplexität eingesetzt werden. Heute muss sie aber meist noch mit spärlichen Trainingsdaten zurechtkommen. Hybrid‐Methoden können diese Datenbasis in Verbindung mit aktiv geleiteten Experimenten verbessern. Sie schließen thermodynamische und kinetische Datenbanken, kombinatorische Hochdurchsatzexperimente, Ab‐initio‐Daten und automatisierte Sprachverarbeitung ein. Solche KI‐Methoden für das Materialdesign können auch mit physikalischen Modellen kombiniert werden. Bei allen Ansätzen ist die Identifizierung geeigneter Deskriptoren wichtig, die das gesuchte Material zu finden helfen. Aktuell ist die Verbesserung der Kausalitätsermittlung bei der Materialentwicklung mittels KI ein wichtiges Forschungsfeld. Dies gilt für die effizientere Entdeckung potenziell verheißungsvoller Datenausreißer sowie die Vorhersage außerhalb der Trainingsbereiche der KI. Metalle prägen unsere Zivilisation seit 5000 Jahren und sind ein Eckpfeiler der Wirtschaft. Die Nachfrage nach neuen Materialien in Energie, Kommunikation und Verkehr erfordert jedoch kürzere Entwicklungszeiten. Die künstliche Intelligenz bietet dazu Lösungen an.

Red mud is the waste of bauxite refinement into alumina, the feedstock for aluminium production1. With about 180 million tonnes produced per year1, red mud has amassed to one of the largest environmentally hazardous waste products, with the staggering amount of 4 billion tonnes accumulated on a global scale1. Here we present how this red mud can be turned into valuable and sustainable feedstock for ironmaking using fossil-free hydrogen-plasma-based reduction, thus mitigating a part of the steel-related carbon dioxide emissions by making it available for the production of several hundred million tonnes of green steel. The process proceeds through rapid liquid-state reduction, chemical partitioning, as well as density-driven and viscosity-driven separation between metal and oxides. We show the underlying chemical reactions, pH-neutralization processes and phase transformations during this surprisingly simple and fast reduction method. The approach establishes a sustainable toxic-waste treatment from aluminium production through using red mud as feedstock to mitigate greenhouse gas emissions from steelmaking.

Antiferromagnets hosting real-space topological textures are promising platforms to model fundamental ultrafast phenomena and explore spintronics. However, they have only been epitaxially fabricated on specific symmetry-matched substrates, thereby preserving their intrinsic magneto-crystalline order. This curtails their integration with dissimilar supports, restricting the scope of fundamental and applied investigations. Here we circumvent this limitation by designing detachable crystalline antiferromagnetic nanomembranes of α-Fe2O3. First, we show—via transmission-based antiferromagnetic vector mapping—that flat nanomembranes host a spin-reorientation transition and rich topological phenomenology. Second, we exploit their extreme flexibility to demonstrate the reconfiguration of antiferromagnetic states across three-dimensional membrane folds resulting from flexure-induced strains. Finally, we combine these developments using a controlled manipulator to realize the strain-driven non-thermal generation of topological textures at room temperature. The integration of such free-standing antiferromagnetic layers with flat/curved nanostructures could enable spin texture designs via magnetoelastic/geometric effects in the quasi-static and dynamical regimes, opening new explorations into curvilinear antiferromagnetism and unconventional computing.

Silicon is a promising anode material due to its high theoretical specific capacity, low lithiation potential and low lithium dendrite risk. Yet, the electrochemical performance of silicon anodes in solid-state batteries is still poor (for example, low actual specific capacity and fast capacity decay), hindering practical applications. Here the chemo-mechanical failure mechanisms of composite Si/Li6PS5Cl and solid-electrolyte-free silicon anodes are revealed by combining structural and chemical characterizations with theoretical simulations. The growth of the solid electrolyte interphase at the Si|Li6PS5Cl interface causes severe resistance increase in composite anodes, explaining their fast capacity decay. Solid-electrolyte-free silicon anodes show sufficient ionic and electronic conductivities, enabling a high specific capacity. However, microscale void formation during delithiation causes larger mechanical stress at the two-dimensional interfaces of these anodes than in composite anodes. Understanding these chemo-mechanical failure mechanisms of different anode architectures and the role of interphase formation helps to provide guidelines for the design of improved electrode materials.

This study aimed to evaluate the reliability and reproducibility of different non‐invasive methods for the assessment of peri‐implant mucosal thickness. Subjects with two adjacent dental implants in the central maxillary region were included in this study. Three different methods to assess facial mucosal thickness (FMT) were compared: digital file superimposition using Digital Imaging and Communication in Medicine (DICOM) and stereolithography (STL) files of the arch of interest (DICOM‐STL), DICOM files alone, and non‐ionizing ultrasound (US). Inter‐rater reliability agreements between different assessment methods were analyzed using inter‐class correlation coefficients (ICCs). A total of 50 subjects with 100 bone‐level implants constituted the study population. Assessment of FMT using STL and DICOM files demonstrated excellent inter‐rater reliability agreement. Mean ICC values of 0.97 and 0.95 were observed in the DICOM‐STL and DICOM groups, respectively. Comparison between the DICOM‐STL and US revealed good agreement, with an ICC of 0.82 (95% CI: 0.74 to 0.88) and a mean difference of –0.13 ± 0.50 mm (–1.13 to 0.86). Comparison between DICOM files alone versus US showed good agreement, with an ICC of 0.81 (95% CI: 0.73 to 0.89) and a mean difference of –0.23 ± 0.46 mm (–1.12 to 0.67). Comparison between DICOM‐STL and DICOM files revealed excellent agreement, with an ICC of 0.94 (95% CI: 0.91 to 0.96) and a mean difference of 0.1 ± 0.29 mm (LOA –0.47 to 0.46). Quantification of peri‐implant mucosal thickness via analysis of DICOM‐STL files, DICOM files, or US assessment are comparably reliable and reproducible methods.

The article reports on the revisions to Title IX of the Education Amendments Act of 1972 made by the administration of U.S. President Joe Biden that provoked backlash from left and right. Issues discussed include in lack of due process rights in campus sexual harassment cases, expansion of discrimination with the inclusion of sexual orientation and gender identity in the rules, and bipartisanship on discrimination against transgender athletes.

In the past 20 years, performance analysis in soccer has accumulated a wide variety of key performance indicators (KPI’s) aimed at reflecting a team’s strength and success. Thanks to rapidly advancing technologies and data analytics more sophisticated metrics, requiring high resolution data acquisition and big data methods, are developed. This includes many position-data-based KPI’s, which incorporate precise spatial and temporal information about every player and the ball on the field.

• BCT twinned martensite and its tetragonality were studied in carbon steels by TEM. • A new transition pathway and its underlying mechanism are revealed. • The FCC to BCT transition includes an inhomogeneous shear and a pure distortion. • The C ordering in the BCT reaches the maximum after the single < 1 ¯ 10>{110} shear in FCC. The martensitic transformation (MT) lays the foundation for microstructure and performance tailoring of many engineering materials, especially steels, which are with > 1.8 billion tons produced per year the most important material class. The atomic-scale migration path is a long-term challenge for MT during quenching in high-carbon (nitrogen) steels. Here, we provide direct evidence of (1 1 ¯ 2) body-centred tetragonal (BCT) twinned martensite in carbon steels by transmission electron microscopy (TEM) investigation, and the increase in tetragonality with the C content matches X-ray diffraction (XRD) results. The specific {1 1 ¯ 2} BCT twin planes which are related to the elongated c axis provide essential structural details to revisit the migration path of the atoms in MT. Therefore, the face-centred cubic (FCC) to BCT twin to body-centred cubic (BCC) twin transition pathway and its underlying mechanisms are revealed through direct experimental observation and atomistic simulations. Our findings shed new light on the nature of the martensitic transition, thus providing new opportunities for the nanostructural control of metals and alloys. [ABSTRACT FROM AUTHOR]