Extreme Compression Research Articles

Multistep Dissociation of Fluorine Molecules under Extreme Compression.

All elements that form diatomic molecules, such as H_{2}, N_{2}, O_{2}, Cl_{2}, Br_{2}, and I_{2}, are destined to become atomic solids under sufficiently high pressure. However, as revealed by many experimental and theoretical studies, these elements show very different propensity and transition paths due to the balance of reduced volume, lone pair electrons, and interatomic bonds. The study of F under pressure can illuminate this intricate behavior since F, owing to its unique position on the periodic table, can be compared with H, with N and O, and also with other halogens. Nevertheless, F remains the only element whose solid structure evolution under pressure has not been thoroughly studied. Using a large-scale crystal structure search method based on first principles calculations, we find that, before reaching an atomic phase, F solid transforms first into a structure consisting of F_{2} molecules and F polymer chains and then into a structure consisting of F polymer chains and F atoms, a distinctive evolution with pressure that has not been seen in any other elements. Both intermediate structures are found to be metallic and become superconducting, a result that adds F to the elemental superconductors.

A model of lung surfactant dynamics based on intrinsic interfacial compressibility

A minimum model for the description of lung surfactant dynamics during consecutive compression/relaxation cycles is proposed. The model is based on Frumkin/Langmuir equilibrium and on an equation of state that includes rigorously the intrinsic compressibility of the densely packed monolayer. Adsorption/desorption dynamics is taken to be kinetically-limited, and film collapse during extreme compression is accounted for by a sublayer reservoir and a simple kinetic expression for monolayer replenishment during re-expansion. The model is validated and found to agree quantitatively with independent data in the literature, taken at physiologically relevant conditions. The best-fit values of the key model parameters are discussed and found to be physically meaningful. Finally, the characteristics of dilatational elasticity, as predicted by the model, are considered.

Recent local geodynamic processes in the Penola Strait_Lemaire Channel fault area (West Antarctica)

We present the crustal deformation field in the Penola Strait – Lemaire Channel fault area (West Antarctica), based on the analysis of the 5 seasonal cycles of static GNSS survey. This 5 GNSS campaigns were conducted with approximately a 16-year interval from 2003 to 2019. The analyses indicate that average linear velocities of horizontal movements are multidirectional but no larger than 1 – 2 mm/yr. Average linear velocities of vertical movements are no larger than ±3 mm/yr. In the present work scheme of vertical and horizontal movements has been drawn out. The obtained results correlate well with the movements of the surrounding GNSS stations. Based on the analysis of spatial distribution of the Earth’s surface dilatation velocity the zones of extreme compression and expansion values were revealed. The analyses of spatial distribution of the Earth’s surface total shear velocity indicate that the studied region is horizontally heterogeneous. Based on the analysis of obtained results, a new kinematic model of fault area was developed. The possibility of using static GNSS survey to study recent local geodynamic processes in Antarctica has been demonstrated.

A flexural design methodology for composite heterogeneous and homogeneous UHPC bridge beams prestressed with bonded strands

A non-iterative flexural design methodology for composite, heterogeneous, and homogeneous ultra-high performance concrete (UHPC) bridge beams prestressed with bonded strands is presented. One key feature of the proposed methodology is the development of closed-form equations for calculating strain in concrete at the most extreme compression fiber at the ultimate limit state, εc, as a function of various parameters. Separate formulations for predicting εc are provided for homogeneous and composite cross-sections. The predicted concrete strain, together with the maximum usable tensile strain for UHPC, εtu, at the most extreme tension fiber are used to calculate cross-sectional curvature and the distribution of strains and stresses. Force equilibrium is then used to determine the depth to the neutral axis and the nominal moment capacity of the beam. The flexural failure mode for the majority of beams considered is a fiber tension controlled failure. From a beam flexural strength perspective, the compressive strength of the deck or top flange for composite and heterogeneous beams, respectively, does not need to exceed 28 MPa. Any excess compressive strength will remain either unutilized or will result in marginal or negligible increases in moment capacities. The magnitude of the cracking strength of UHPC plays an important role in the contribution of UHPC to the moment capacity of the beam and determines whether this contribution is higher or smaller than that provided by the prestressing strands. The strand stress at the ultimate limit state, fps, varied from 1688 MPa to 1743 MPa and was past the linear elastic branch of the assumed stress-strain curve. The parameter that had the highest influence on fps was εtu. The proposed methodology is validated using test data as well as results from validated nonlinear finite element models and strain compatibility analysis.

Calculation and interpretation of classical turning surfaces in solids

Classical turning surfaces of Kohn–Sham potentials separate classically allowed regions (CARs) from classically forbidden regions (CFRs). They are useful for understanding many chemical properties of molecules but need not exist in solids, where the density never decays to zero. At equilibrium geometries, we find that CFRs are absent in perfect metals, rare in covalent semiconductors at equilibrium, but common in ionic and molecular crystals. In all materials, CFRs appear or grow as the internuclear distances are uniformly expanded. They can also appear at a monovacancy in a metal. Calculations with several approximate density functionals and codes confirm these behaviors. A classical picture of conduction suggests that CARs should be connected in metals, and disconnected in wide-gap insulators, and is confirmed in the limits of extreme compression and expansion. Surprisingly, many semiconductors have no CFR at equilibrium, a key finding for density functional construction. Nonetheless, a strong correlation with insulating behavior can still be inferred. Moreover, equilibrium bond lengths for all cases can be estimated from the bond type and the sum of the classical turning radii of the free atoms or ions.

Probing Medium-Range Order in Oxide Glasses at High Pressure.

Densification in glassy networks has traditionally been described in terms of short-range structures, such as how atoms are coordinated and how the coordination polyhedron is linked in the second coordination environment. While changes in medium-range structures beyond the second coordination shells may play an important role, experimental verification of the densification beyond short-range structures is among the remaining challenges in the physical sciences. Here, a correlation NMR experiment for prototypical borate glasses under compression up to 9 GPa offers insights into the pressure-induced evolution of proximity among cations on a medium-range scale. Whereas amorphous networks at ambient pressure may favor the formation of medium-range clusters consisting primarily of similar coordination species, such segregation between distinct coordination environments tends to decrease with increasing pressure, promoting a more homogeneous distribution of dissimilar structural units. Together with an increase in the average coordination number, densification of glass accompanies a preferential rearrangement toward a random distribution, which may increase the configurational entropy. The results highlight the direct link between the pressure-induced increase in medium-range disorder and the densification of glasses under extreme compression.

Extreme matter compression caused by radiation cooling effect in gigabar shock wave driven by laser-accelerated fast electrons

Heating a solid material with laser-accelerated fast electrons is a particularly useful method for generating a plane powerful shock wave with a pressure of several hundred or even thousands of Mbar in the laboratory. Behind the front of such a powerful shock wave, dense plasma is heated to a temperature of several keV. Then, a high rate of radiation energy loss occurs even in low-Z plasmas. In this paper, the strong compression of matter due to radiation cooling in a Gbar shock wave driven by fast electrons is studied using both computational and theoretical approaches. It is shown that the effect of radiation cooling leads to compression of matter in the peripheral region of the shock wave to a density several times greater than the density at its front. Heating a solid material by a petawatt flux of laser-accelerated fast electrons offers the opportunity to surpass the gigabar pressure level of plane shock waves generated by the impact of laser-accelerated pellets. Higher pressures of about 100 Gbar can be achieved under laboratory conditions only when a spherical target is imploded under the action of a terawatt laser pulse.

Bioinspired design and assembly of a multilayer cage-shaped sensor capable of multistage load bearing and collapse prevention

Flexible bioinspired mesostructures and electronic devices have recently attracted intense attention because of their widespread application in microelectromechanical systems (MEMS), reconfigurable electronics, health-monitoring systems, etc. Among various geometric constructions, 3D flexible bioinspired architectures are of particular interest, since they can provide new functions and capabilities, compared to their 2D counterparts. However, 3D electronic device systems usually undergo complicated mechanical loading in practical operation, resulting in complex deformation modes and elusive failure mechanisms. The development of mechanically robust flexible 3D electronics that can undergo extreme compression without irreversible collapse or fracture remains a challenge. Here, inspired by the multilayer mesostructure of Enhydra lutris fur, we introduce the design and assembly of multilayer cage architectures capable of multistage load bearing and collapse prevention under large out-of-plane compression. Combined in situ experiments and mechanical modeling show that the multistage mechanical responses of the developed bionic architectures can be fine-tuned by tailoring the microstructural geometries. The integration of functional layers of gold and piezoelectric polymer allows the development of a flexible multifunctional sensor that can simultaneously achieve the dynamic sensing of compressive forces and temperatures. The demonstrated capabilities and performances of fast response speed, tunable measurement range, excellent flexibility, and reliability suggest potential uses in MEMS, robotics and biointegrated electronics.

Current and New Approaches to Predict the Deflections of One-Way Flexural Members with a Focus on Composite Steel Deck Slabs Voided by Circular Tubes.

A new type of composite voided slab, the TUBEDECK (TD), which utilizes the structural function of profiled steel decks, has recently been proposed. Previous studies have confirmed that the flexural strength of TD slabs can be calculated based on the full composite contribution of the steel deck, but for long-span flexural members, the deflection serviceability requirement is often dominant. Herein, we derived a novel deflection prediction approach using the results of flexural tests on slab specimens, focusing on TD slabs. First, deflection prediction based on modifications of the current code was proposed. Results revealed that TD slabs exhibited smaller long-term deflections and at least 10% longer maximum span lengths than solid slabs, indicating their greater efficiency. Second, a novel rational method was derived for predicting deflections without computing the effective moment of inertia. The ultimate deflections predicted by the proposed method correlated closely with the deflection under maximum bending moments. To calculate immediate deflections, variation functions for the concrete strain at the extreme compression fiber and neutral axis depth were assumed with predictions in good agreement with experiments. The proposed procedure has important implications in highlighting a new perspective on the deflection prediction of reinforced concrete and composite flexural members.

Stability of continuous welded rails: A state-of-the-art review of structural modeling and nondestructive evaluation

Continuous welded rails (CWR) are track segments welded together to form a continuous miles-long track. With respect to mechanically-jointed rails, CWR are stronger, smoother, require less maintenance, and can be traveled at higher speeds. Despite these advantages, CWR are prone to fracture during cold seasons and to instability during warm seasons when the increase in the steel temperature induces extreme compression. To better understand buckling mechanism, engineers studied the structural behavior of rails under static and dynamic loads. Some of these models represent the basis of noninvasive methods to measure longitudinal stress. Both structural analyses and nondestructive evaluation methods are tools to predict the temperatures and the field conditions at which rails experience extreme tensile or compressive stress. This article reviews the last three decades of research and development on the structural analysis and nondestructive evaluation of CWR. The scope of this document is to provide a holistic view of the developments in rail engineering and nondestructive evaluation relevant to the problem of thermal buckling. Advantages and limitations of the analyses and of the nondestructive methods are discussed based upon the information available in the scientific literature. Additionally, any knowledge gap to be addressed by the scientific community in the years to come is identified and discussed.

Nanomaterials Based Nanoplasmonic Accelerators and Light-Sources Driven by Particle-Beams

Unprecedented tens of TVm−1 fields are modeled to be realizable using novel nanoplasmonic surface crunch-in modes in nanomaterials. These relativistic nonlinear surface modes are accessible due to advances in nanofabrication and quasi-solid density sub-micron particle bunch compression. Proof of principle of TVm−1 plasmonics is provided using three-dimensional computational and analytical modeling of GeV scale energy gain in sub-millimeter long tubes having nanomaterial walls with controllable free-electron densities, $n_{\mathrm t}\sim 10^{22-24}\mathrm {cm^{-3}}$ and hundreds of nanometer core radius driven by quasi-solid electron beams, $n_{\mathrm b}\sim 0.01n_{\mathrm t}$ . Besides the tens of TeVm−1 acceleration gradients, equally strong transverse fields lead to self-focusing and nanomodulation of the beam which drive extreme beam compression to ultra-solid peak densities increasing the crunch-in field strength. Apart from ultra-solid particle beams, extreme focusing also opens up a nano-wiggler like tunable coherent $\mathrm {\mathcal {O}(100MeV)}$ ultra-dense photon source.

Optimization of the Composition of Standards in Recognition and Compression Algorithms of Hyperspectral Images

The paper proposes a solution to the problem of minimizing the number of standards in order to increase both the compression coefficient of hyperspectral images (HSI) and the speed of correlation extreme compression methods (CEM). As modifications of the CEM, randomized and differential compression algorithms are offered. The randomized and difference algorithms are based on the hypothesis of spatial compactness of pixels located in local regions of the image matrix. This means that when a new template is formed based on an unrecognized pixel, there is a high probability of using a pixel that lies near the boundaries of the coverage areas of the existing templates, which leads to their increase. In order to reduce the influence of spatial compactness of pixels on the formation of standards, a methodology based on changing the sequence of recognized pixels is proposed. In a randomized algorithm, a row of the matrix is randomly determined for this, on the basis of which a sequence of recognized pixels is generated by a random column generator. In the difference algorithm of compression, the row number of the matrix is determined by the rule for finding the members of an arithmetic progression with a given difference. For the selected line a sequence of recognizable pixels is formed on the same principle. It should be noted that line-by-line pixel recognition in the self-learning mode allows compressing HSI of almost any volume. The effectiveness of the created algorithms is demonstrated on two fragments of real HSI. A comparative analysis of all three compression algorithms in terms of the quantitative composition of the obtained standards is presented.

Can Zoos Ever Be Big Enough for Large Wild Animals? A Review Using an Expert Panel Assessment of the Psychological Priorities of the Amur Tiger (Panthera tigris altaica) as a Model Species.

Simple SummaryThe reduction in space available to wild animals in zoos and aquariums is widely perceived to be detrimental to their welfare by scientists and the general public alike. Evidence suggests that naturally wide-ranging carnivores are more likely to suffer in captivity than those that travel less widely. Using the Amur tiger as a representative for wide-ranging species frequently held in zoos, an expert panel assessment was undertaken to identify psychological priorities in order to see how the negative welfare impacts of reduced ranging opportunities might be most effectively overcome. This assessment highlights that whilst reduced access to space may be central to compromised welfare for many species, there may be more effective strategies in safeguarding welfare than simply making captive habitats marginally bigger. Central to this for Amur tigers is providing appropriate mental stimulation rather than focusing only on behaviours linked to hunting. Various strategies intended to safeguard welfare are discussed for Amur tigers, which can also be considered for other wide-ranging species.The ecology of large, wide-ranging carnivores appears to make them vulnerable to conservation challenges in the wild and welfare challenges in captivity. This poses an ethical dilemma for the zoo community and supports the case that there is a need to reconsider prevailing management paradigms for these species in captivity. Whilst the welfare challenges wide ranging carnivores face have been attributed to reduced ranging opportunities associated with the decreased size of captive habitats, attempts to augment wild carnivore welfare in captivity typically focus on behaviours linked to hunting. Thus far, this has yet to result in the systematic elimination of signs of compromised welfare amongst captive carnivores. Here an assessment is carried out to identify the likely welfare priorities for Amur tigers, which, as one of the widest ranging terrestrial carnivores, serves as an excellent exemplar for species experiencing extreme compression of their ranging opportunities in captivity. These priorities are then used to consider novel strategies to address the welfare challenges associated with existing management paradigms, and in particular, attempt to overcome the issue of restricted space. The insights generated here have wider implications for other species experiencing substantive habitat compression in captivity. It is proposed here that the impact of habitat compression on captive carnivore welfare may not be a consequence of the reduction in habitat size per se, but rather the reduction in cognitive opportunities that likely covary with size, and that this should inform strategies to augment welfare.

Extreme data compression while searching for new physics

ABSTRACT Bringing a high-dimensional data set into science-ready shape is a formidable challenge that often necessitates data compression. Compression has accordingly become a key consideration for contemporary cosmology, affecting public data releases, and reanalyses searching for new physics. However, data compression optimized for a particular model can suppress signs of new physics, or even remove them altogether. We therefore provide a solution for exploring new physics during data compression. In particular, we store additional agnostic compressed data points, selected to enable precise constraints of non-standard physics at a later date. Our procedure is based on the maximal compression of the MOPED algorithm, which optimally filters the data with respect to a baseline model. We select additional filters, based on a generalized principal component analysis, which are carefully constructed to scout for new physics at high precision and speed. We refer to the augmented set of filters as MOPED-PC. They enable an analytic computation of Bayesian Evidence that may indicate the presence of new physics, and fast analytic estimates of best-fitting parameters when adopting a specific non-standard theory, without further expensive MCMC analysis. As there may be large numbers of non-standard theories, the speed of the method becomes essential. Should no new physics be found, then our approach preserves the precision of the standard parameters. As a result, we achieve very rapid and maximally precise constraints of standard and non-standard physics, with a technique that scales well to large dimensional data sets.

How Can Protons Migrate in Extremely Compressed Liquid Water?

Compression of liquid water up to multi-kbar pressures is known to perturb dramatically its local structure required for charge defects to migrate as topological defects in the hydrogen-bonded network. Our abinitio simulations show that the migration of excess protons is not much affected at 10kbar, whereas that of proton holes is significantly reduced. Non-Markovian analyses show that this is not due to modifying the free energy barriers of both charge transfer and migration. It is rather pressure-induced modifications of the population of activated states, depending on interstitial water, which rules charge migration at extreme compression.

Shear Capacity N-M Interaction Envelope for RC Beam-Column Joints with Transverse Reinforcement: A Concept Derived from Strength Hierarchy

ABSTRACT Strength hierarchy assessment method is a capacity analysis procedure that can be used to identify the sequence of failures likely to occur within reinforced concrete (RC) frame buildings under lateral actions such as earthquakes or wind loads. Previous publication on this method mainly focused on the application of this method to (a) the vulnerable RC beam-column joints without any joint shear reinforcement where principal tensile stresses were considered critical, (b) modern RC beam-column joints with joint shear reinforcement where extreme principal compression stresses were considered critical. In this paper, joint shear capacity representation for modern RC beam-column joints (with transverse reinforcements in the joint) is generalized to include both critical components: principal tensile and principal compression stresses. Using strength hierarchy assessment, the investigation showed that it is possible to express the joint shear capacity as an N-M interaction envelope analogous to the N-M interaction of columns. The resulting joint shear capacity N-M interaction concept is validated using a database of 22 external and 22 internal RC beam-column joint tests with joint shear reinforcement at their joint core which resulted in joint shear failure in their tests. Considering the importance of axial load levels on the expected performance of RC beam-column joints, the proposed concept can be used for the general assessment of the joint shear capacity or for beam-column joint modeling purposes, which can be practically used by the design engineers.

Minimax isometry method: A compressive sensing approach for Matsubara summation in many-body perturbation theory

We present a compressive sensing approach for the long-standing problem of Matsubara summation in many-body perturbation theory. By constructing low-dimensional, almost isometric subspaces of the Hilbert space we obtain optimum imaginary time and frequency grids that allow for extreme data compression of fermionic and bosonic functions in a broad temperature regime. The method is applied to the random phase and self-consistent $GW$ approximation of the grand potential. Integration and transformation errors are investigated for Si and ${\mathrm{SrVO}}_{3}$.

Experimental and Simulation Insights into Local Structure and Luminescence Evolution in Eu3+-Doped Nanocrystals under High Pressure.

Tremendous effort has been devoted to tailoring structure-correlated properties, especially for the luminescence of lanthanide nanocrystals (NCs). High pressure has been demonstrated as a decent way to tune the performance of lanthanide NCs; however, little attention has been paid to the local structure evolution accompanied by extreme compression and its effect on luminescence. Here, we tailor the local structure around lanthanide ions with pressure in β-NaGdF4 NCs, in which Eu3+ ions were doped as optical probes for local structure for the sensitive electric dipole transition. As the pressure increases, the intensity ratio of the 5D0 → 7F2 to 5D0 → 7F1 transition decreases monotonically from 2.04 to 0.81, implying a higher local symmetry around Eu3+ ions from compression. In situ X-ray diffraction demonstrates that the sample maintains the hexagonal structure up to 33.5 GPa, and density functional theory calculations reveal the tendency of the local structure to vary under high pressure.

Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio

Deep neural network compression is important and increasingly developed especially in resource-constrained environments, such as autonomous drones and wearable devices. Basically, we can easily and largely reduce the number of weights of a trained deep model by adopting a widely used model compression technique, e.g., pruning. In this way, two kinds of data are usually preserved for this compressed model, i.e., non-zero weights and meta-data, where meta-data is employed to help encode and decode these non-zero weights. Although we can obtain an ideally small number of non-zero weights through pruning, existing sparse matrix coding methods still need a much larger amount of meta-data (may several times larger than non-zero weights), which will be a severe bottleneck of the deploying of very deep models. To tackle this issue, we propose a layerwise sparse coding (LSC) method to maximize the compression ratio by extremely reducing the amount of meta-data. We first divide a sparse matrix into multiple small blocks and remove zero blocks, and then propose a novel signed relative index (SRI) algorithm to encode the remaining non-zero blocks (with much less meta-data). In addition, the proposed LSC performs parallel matrix multiplication without full decoding, while traditional methods cannot. Through extensive experiments, we demonstrate that LSC achieves substantial gains in pruned DNN compression (e.g., 51.03x compression ratio on ADMM-Lenet) and inference computation (i.e., time reduction and extremely less memory bandwidth), over state-of-the-art baselines.

Degree of Permanent Densification in Oxide Glasses upon Extreme Compression up to 24 GPa at Room Temperature.

During the decompression of plastically deformed glasses at room temperature, some aspects of irreversible densification may be preserved. This densification has been primarily attributed to topological changes in glass networks. The changes in short-range structures like cation coordination numbers are often assumed to be relaxed upon decompression. Here the NMR results for aluminosilicate glass upon permanent densification up to 24 GPa reveal noticeable changes in the Al coordination number under pressure conditions as low as ∼6 GPa. A drastic increase in the highly coordinated Al fraction is evident over only a relatively narrow pressure range of up to ∼12 GPa, above which the coordination change becomes negligible up to 24 GPa. In contrast, Si coordination environments do not change, highlighting preferential coordination transformation during deformation. The observed trend in the coordination environment shows a remarkable similarity to the pressure-induced changes in the residual glass density, yielding a predictive relationship between the irreversible densification and the detailed structures under extreme compression. The results open a way to access the nature of plastic deformation in complex glasses at room temperature.