Ab Initio Phase Diagram of Chromium to 2.5 TPa

Chromium possesses remarkable physical properties such as hardness and corrosion resistance. Chromium is also a very important geophysical material as it is assumed that lighter Cr isotopes were dissolved in the Earth's molten core during the planet's formation, which makes Cr one of the main constituents of the Earth's core. Unfortunately, Cr has remained one of the least studied 3d transition metals. In a very recent combined experimental and theoretical study (Anzellini et al., Scientific Reports, 2022), the equation of state and melting curve of chromium were studied to 150 GPa, and it was determined that the ambient body-centered cubic (bcc) phase of crystalline Cr remains stable in the whole pressure range considered. However, the importance of the knowledge of the physical properties of Cr, specifically its phase diagram, necessitates further study of Cr to higher pressure. In this work, using a suite of ab initio quantum molecular dynamics (QMD) simulations based on the Z methodology which combines both direct Z method for the simulation of melting curves and inverse Z method for the calculation of solid-solid phase transition boundaries, we obtain the theoretical phase diagram of Cr to 2.5 TPa. We calculate the melting curves of the two solid phases that are present on its phase diagram, namely, the lower-pressure bcc and the higher-pressure hexagonal close-packed (hcp) ones, and obtain the equation for the bcc-hcp solid-solid phase transition boundary. We also obtain the thermal equations of state of both bcc-Cr and hcp-Cr, which are in excellent agreement with both experimental data and QMD simulations. We argue that 2180 K as the value of the ambient melting point of Cr which is offered by several public web resources ("Wikipedia," "WebElements," "It's Elemental," etc.) is most likely incorrect and should be replaced with 2135 K, found in most experimental studies as well as in the present theoretical work

Needs, trends, and advances in scintillators for radiographic imaging and tomography

Scintillators are important materials for radiographic imaging and tomography (RadIT), when ionizing radiations are used to reveal internal structures of materials. Since its invention by R\"ontgen, RadIT now come in many modalities such as absorption-based X-ray radiography, phase contrast X-ray imaging, coherent X-ray diffractive imaging, high-energy X- and $\gamma-$ray radiography at above 1 MeV, X-ray computed tomography (CT), proton imaging and tomography (IT), neutron IT, positron emission tomography (PET), high-energy electron radiography, muon tomography, etc. Spatial, temporal resolution, sensitivity, and radiation hardness, among others, are common metrics for RadIT performance, which are enabled by, in addition to scintillators, advances in high-luminosity accelerators and high-power lasers, photodetectors especially CMOS pixelated sensor arrays, and lately data science. Medical imaging, nondestructive testing, nuclear safety and safeguards are traditional RadIT applications. Examples of growing or emerging applications include space, additive manufacturing, machine vision, and virtual reality or `metaverse'. Scintillator metrics such as light yield and decay time are correlated to RadIT metrics. More than 160 kinds of scintillators and applications are presented during the SCINT22 conference. New trends include inorganic and organic scintillator heterostructures, liquid phase synthesis of perovskites and $\mu$m-thick films, use of multiphysics models and data science to guide scintillator development, structural innovations such as photonic crystals, nanoscintillators enhanced by the Purcell effect, novel scintillator fibers, and multilayer configurations. Opportunities exist through optimization of RadIT with reduced radiation dose, data-driven measurements, photon/particle counting and tracking methods supplementing time-integrated measurements, and multimodal RadIT.Comment: 45 pages, 43 Figures, SCINT22 conference overvie

Precision pulse shape simulation for proton detection at the Nab experiment

The Nab experiment at Oak Ridge National Laboratory, USA, aims to measure the beta-antineutrino angular correlation following neutron $\beta$ decay to an anticipated precision of approximately 0.1\%. The proton momentum is reconstructed through proton time-of-flight measurements, and potential systematic biases in the timing reconstruction due to detector effects must be controlled at the nanosecond level. We present a thorough and detailed semiconductor and quasiparticle transport simulation effort to provide precise pulse shapes, and report on relevant systematic effects and potential measurement schemes

Monte Carlo of Trapped Ultracold Neutrons in the UCNτ Trap

In the UCNτ experiment, ultracold neutrons (UCN) are confined by magnetic fields and the Earth’s gravitational field. Field-trapping mitigates the problem of UCN loss on material surfaces, which caused the largest correction in prior neutron experiments using material bottles. However, the neutron dynamics in field traps differ qualitatively from those in material bottles. In the latter case, neutrons bounce off material surfaces with significant diffusivity and the population quickly reaches a static spatial distribution with a density gradient induced by the gravitational potential. In contrast, the field-confined UCN—whose dynamics can be described by Hamiltonian mechanics—do not exhibit the stochastic behaviors typical of an ideal gas model as observed in material bottles. In this report, we will describe our efforts to simulate UCN trapping in the UCNτ magneto-gravitational trap. We compare the simulation output to the experimental results to determine the parameters of the neutron detector and the input neutron distribution. The tuned model is then used to understand the phase space evolution of neutrons observed in the UCNτ experiment. We will discuss the implications of chaotic dynamics on controlling the systematic effects, such as spectral cleaning and microphonic heating, for a successful UCN lifetime experiment to reach a 0.01% level of precision

Generalization of the Unified Analytic Melt-Shear Model to Multi-Phase Materials: Molybdenum as an Example

The unified analytic melt-shear model that we introduced a decade ago is generalized to multi-phase materials. A new scheme for calculating the values of the model parameters for both the cold ( T = 0 ) shear modulus ( G ) and the melting temperature at all densities ( ρ ) is developed. The generalized melt-shear model is applied to molybdenum, a multi-phase material with a body-centered cubic (bcc) structure at low ρ which loses its dynamical stability with increasing pressure (P) and is therefore replaced by another (dynamically stable) solid structure at high ρ . One of the candidates for the high- ρ structure of Mo is face-centered cubic (fcc). The model is compared to (i) our ab initio results on the cold shear modulus of both bcc-Mo and fcc-Mo as a function of ρ , and (ii) the available theoretical results on the melting of bcc-Mo and our own quantum molecular dynamics (QMD) simulations of one melting point of fcc-Mo. Our generalized model of G ( ρ , T ) is used to calculate the shear modulus of bcc-Mo along its principal Hugoniot. It predicts that G of bcc-Mo increases with P up to ∼240 GPa and then decreases at higher P. This behavior is intrinsic to bcc-Mo and does not require the introduction of another solid phase such as Phase II suggested by Errandonea et al. Generalized melt-shear models for Ta and W also predict an increase in G followed by a decrease along the principal Hugoniot, hence this behavior may be typical for transition metals with ambient bcc structure that dynamically destabilize at high P. Thus, we concur with the conclusion reached in several recent papers (Nguyen et al., Zhang et al., Wang et al.) that no solid-solid phase transition can be definitively inferred on the basis of sound velocity data from shock experiments on Mo. Finally, our QMD simulations support the validity of the phase diagram of Mo suggested by Zeng et al