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Paleontology provides insights into the history of the planet, from the origins of life billions of years ago to the biotic changes of the Recent. The scope of paleontological research is as vast as it is varied, and the field is constantly evolving. In an effort to identify “Big Questions” in paleontology, experts from around the world came together to build a list of priority questions the field can address in the years ahead. The 89 questions presented herein (grouped within 11 themes) represent contributions from nearly 200 international scientists. These questions touch on common themes including biodiversity drivers and patterns, integrating data types across spatiotemporal scales, applying paleontological data to contemporary biodiversity and climate issues, and effectively utilizing innovative methods and technology for new paleontological insights. In addition to these theoretical questions, discussions touch upon structural concerns within the field, advocating for an increased valuation of specimen-based research, protection of natural heritage sites, and the importance of collections infrastructure, along with a stronger emphasis on human diversity, equity, and inclusion. These questions offer a starting point—an initial nucleus of consensus that paleontologists can expand on—for engaging in discussions, securing funding, advocating for museums, and fostering continued growth in shared research directions.
In this paper, we investigate Kolmogorov-type theorems for small perturbations of degenerate Hamiltonian systems. These systems are index by a parameter ξ as $ H(y,x,\xi) = \langle\omega(\xi),y\rangle {+ \bar h(y,\xi)}+\varepsilon P(y,x,\xi,\varepsilon) $, where ɛ > 0. We assume that the frequency mapping $\omega(\cdot)$, $\bar h(y,\cdot)=O(|y|^2)$ and the perturbation $\varepsilon P(y,x,\cdot, \varepsilon)$ maintain Hölder continuity about ξ. We prove that the persistent invariant tori retain the same frequency as those of the unperturbed tori, under a certain topological degree condition and a weak convexity condition for the frequency mapping. Notably, this paper presents, to our understanding, pioneering results on the KAM theorem under such conditions with only assumption of Hölder continuous dependence of frequency mapping ω on the parameter.
The discovery that blazars dominate the extra-galactic $\gamma$-ray sky is a triumph in the Fermi era. However, the exact location of $\gamma$-ray emission region still remains in debate. Low-synchrotron-peaked blazars (LSPs) are estimated to produce high-energy radiation through the external Compton process, thus their emission regions are closely related to the external photon fields. We employed the seed factor approach proposed by Georganopoulos et al. It directly matches the observed seed factor of each LSP with the characteristic seed factors of external photon fields to locate the $\gamma$-ray emission region. A sample of 1 138 LSPs with peak frequencies and peak luminosities was adopted to plot a histogram distribution of observed seed factors. We also collected some spectral energy distributions (SEDs) of historical flare states to investigate the variation of $\gamma$-ray emission region. Those SEDs were fitted by both quadratic and cubic functions using the Markov-chain Monte Carlo method. Furthermore, we derived some physical parameters of blazars and compared them with the constraint of internal $\gamma\gamma$-absorption. We find that dusty torus dominates the soft photon fields of LSPs and most $\gamma$-ray emission regions of LSPs are located at 1–10 pc. The soft photon fields could also transition from dusty torus to broad line region and cosmic microwave background in different flare states. Our results suggest that the cubic function is better than the quadratic function to fit the SEDs.
We introduce the notion of completed $F$-crystals on the absolute prismatic site of a smooth $p$-adic formal scheme. We define a functor from the category of completed prismatic $F$-crystals to that of crystalline étale $\mathbf {Z}_p$-local systems on the generic fiber of the formal scheme and show that it gives an equivalence of categories. This generalizes the work of Bhatt and Scholze, which treats the case of a mixed characteristic complete discrete valuation ring with perfect residue field.
Creating an environmentally friendly precursor to form a kaolinite intercalation compound is important for promoting the applications of nanohybrid kaolinite in electrochemical sensors, low- or zero-toxicity drug carriers, and clay-polymer nanocompounds. In the present study, a stable hydrated kaolinite pre-cursor with d001= 0.84 nm was prepared successfully by heating the transition phase, the as-prepared kaolinite-hydrazine intercalate, at temperatures between 40 and 70ºC. The structure of the hydrated kaolinite was characterized by X-ray diffraction and infrared spectroscopy. The morphology was examined using scanning electron microscopy. The results showed that the hydrated hydrazine of the transition phase was easy to decompose to hydrazines and water molecules in the interlayer at 40-70ºC. Hydrazine molecules de-intercalated gradually, and water molecules remained in the ditrigonal holes of the silicate layer with sufficient stability, finally forming the stable 0.84 nm hydrated kaolinite in the system with a success rate of 80–90%. The 0.84 nm hydrated kaolinite may become an excellent precursor for the preparation of other kaolinite intercalates. A degree of intercalation of ~100% was obtained for the kaolinite-ethylene glycol intercalate, and a degree of intercalation of ~80% was obtained for the kaolinite-glycine intercalate from the 0.84 nm hydrated kaolinite precursor.
This paper studies the synchronization control of the blanket remote maintenance robot (BRMR) of the China fusion engineering test reactor (CFETR). First, the general state space mathematical model of BRMR was established by using a physical-based method. Second, based on the receding horizon optimization of model predictive control (MPC) and cross-coupling error reduction in cross-coupling control (CCC), the innovative MPC-CCC controller was proposed to realize the single-system and multisystem error convergence and high accuracy transportation of blanket through the high accuracy synchronization control of BRMR. Third, to verify the control effectiveness of the MPC-CCC controller, two types of simulations and experiments were implied compared with the original proportional-integral (PI) controller in Mover. Results showed that simulation and experiments were highly consistent. It is found that the use of an MPC-CCC controller can result in up to a 70% reduction in displacement error and up to a 59% reduction in synchronization error compared to the PI controller. And the accuracy of the MPC-CCC controller satisfies the real requirement of the maintenance process of the blanket. This work provides the theoretical basis and practical experience for the highly stable, safe, and efficient maintenance of blankets in the future.
In this paper, we provide a new approach to prove some weighted-blowup formulae for genus zero orbifold Gromov–Witten invariants. As a consequence, we show the invariance of symplectically rational connectedness with respect to weighted-blowup along positive centers. Furthermore, we use this method to give a new proof to the genus zero relative-orbifold correspondence of Gromov–Witten invariants.
Introducing state-of-the art computational methods, this book combines detailed explanations with real-world case studies to give a full grounding in the design of engineering materials. This book presents a wide spectrum of key computational methods, such as CALPHAD-method, first-principles calculations, phase-field simulation and finite element analysis, covering the atomic-meso-macro scale range. The reader will see these methods applied to case studies for steel, light alloys, superalloys, cemented carbides, hard coating and energy materials, demonstrating in detail how real-world materials are designed. Online ancillary material includes input files for computational design software, providing the reader with hands-on design experience. Step-by-step instructions will allow you to perform and repeat the simulations discussed in the book. Aimed at both graduate and undergraduate students as well as non-specialist researchers in materials science and engineering, including ceramics, metallurgy, and chemistry, this is an ideal introductory and reference book.
Chapter 5 focuses on the CALPHAD approach and its thermodynamic basis with the crucial concept of “phase." The origins, development, and principles of the CALPHAD method are briefly explained and current software is compiled (Thermo-Calc, Pandat, FactSage, and more). Thermodynamic modeling of Gibbs energy is introduced, from simple pure substances to complex solution phases. Examples of how to establish a thermodynamic database are given, and key issues on the consistency, coherency, quality assurance, and safety of the database are emphasized. The most important application examples in the computational design of alloys and their processing are separated in two levels. In the first level, solely thermodynamic CALPHAD databases are required. It is shown which type of calculations have proved most useful to guide design. In the second level, applications using extended CALPHAD-type databases with kinetic and thermophysical material parameters are outlined for casting, solidification, and heat treatment processes. The use of advanced CALPHAD-type software packages is demonstrated. Finally, a case study on design of Al alloys with improved hot cracking resistance is presented with these tools.
Chapter 10 starts with category and production processes of cemented carbides. Subsequently, case studies for three cemented carbides are demonstrated. In the case of ultrafine cemented carbide, thermodynamic calculations were utilized to select composition and sintering temperature to avoid segregation of the (Ta,W)C phase. Optimal mechanical properties were obtained via adding VC and Cr3C2 inhibitors and the selected sintering temperature and composition. For WC–Co–Ni–Al cemented carbides, calculated phase diagrams and interfacial energy were employed to optimize the composition of Co–Ni–Al binder phase and sintering temperature. The morphology of WC was controlled through phase-field simulation and microstructure characterization. The best trade-off between transverse rupture strength and Rockwell hardness is obtained accordingly. For gradient cemented carbides, thermodynamic and diffusion calculations were performed to select composition and sintering schedule to provide microstructure parameters. A microstructure-based model was then developed to predict the hardness distribution. This simulation-driven materials design leads to development of these products within three years.
In Chapter 3, we mainly focus on the fundamentals of typical mesoscale simulation methods, which can provide a bridge between atomistic structures and macroscopic properties of materials. Among many mesoscale simulation methods, the phase-field and cellular automaton methods are extremely popular and powerful for simulating microstructure evolution. Consequently, we first give a detailed introduction on the fundamentals of the two methods, briefly describing some other mesoscale simulation methods, such as level set and front tracking. After that, application examples using individual mesoscale simulation methods and integrations of the phase-field method with other simulation methods such as atomistic simulation, crystal plasticity, CALPHAD, and machine learning are described in detail. Finally, a case study for design of high-energy-density polymer nanocomposites using the phase-field method is very briefly presented.
Chapter 8 focuses on the design of important Al- and Mg-based light alloys. Selected examples show how CALPHAD simulation tools can be used to understand and predict the effect of alloying elements and processing conditions on alloy properties and how to use that in the design of alloys. For Al alloys, two case study examples using the extended CALPHAD-type databases are demonstrated. For cast alloy A356 (Al–Si,Mg), the solidification simulation involving dedicated microsegregation modeling is presented. For the wrought alloy 7xxx (Al–Zn,Mg/Cu), elaborate heat treatment simulation with precipitation kinetics is the design tool. For Mg alloy structural components, simulations of solidification path and T6 heat treatment of AZ series (Mg–AlZn) and the development of Mg–Al–Sn-based (AT) cast alloys involving also microsegregation simulation are demonstrated. Finally, the design of biomedical Mg alloy implants utilizing the CALPHAD method and the state-of-the-art bioresorbable Mg alloy stent to cure coronary artery disease is presented.
In Chapter 11, first an introduction to cutting tools is presented, followed by case studies for two hard coatings. For the TiAlN PVD coating case, we describe how to adjust the formation of metastable phase, select the deposition temperature, and manipulate microstructure to obtain desired mechanical properties through first-principles calculations and thermodynamic calculations. The deposition of the TiAlN/TiN and TiAlN/ZrN multilayer guided by first-principles calculations is also briefly mentioned. For the TiCN CVD coating, we demonstrate that computed CVD phase diagrams can accurately describe phases and their compositions under the given temperature, total pressure, and pressures of various gases. Subsequently, computational fluid dynamics (CFD) is used to provide temperature field, velocity, and distributions of various gases inside the CVD reactor. From that information, calculations-designed experiments were conducted and TiCN coatings were deposited highly efficiently. These simulation-driven designs for the hard coatings have found industrial applications in just two years, much quicker compared to the costly experimental approach.
Chapter 9 focuses on superalloys operating at high temperature where high strength as well as creep and corrosion resistance are demanded. We take Ni-based single-crystal superalloys and Ni–Fe-based superalloys for advanced ultrasupercritical (A-USC) power plants as examples to demonstrate how alloy design is accomplished in these multicomponent alloy systems. The first case study introduces the design procedure of Ni-based single-crystal superalloy by using a multicriterion constrained multistart optimization algorithm. In the second case study, the design procedure of an Ni–Fe-based superalloy with the artificial neural network (ANN) model combined with a genetic algorithm (GA) based on an experimental dataset is presented.