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At least 109 records · Page 6

Angle-Resolved Polarized Raman Study of Layered Cr 2 Se 3

The polarization-resolved Raman spectra of two-dimensional Cr 2 Se 3 synthesized via chemical vapor deposition (CVD) and chemical vapor transport (CVT) techniques were investigated in detail. The samples were characterized using X-ray diffraction (XRD), transmission electron microscopy (TEM), and energy-dispersive X-ray spectroscopy (EDS). A distinct polarization dependence was observed in the Raman intensity of all the Cr-Cr, Cr-Se, and Se-Se modes in both samples. The observed angle-dependent Raman intensities of each peak could be related to the crystal structure-specific Raman tensor. XRD results of the bulk Cr 2 Se 3 sample synthesized via CVT confirm its trigonal crystal structure, and the Raman peaks can be fitted using the Raman tensors for the A g and E g modes for both the parallel and crossed polarizations. However, for the Cr 2 Se 3 samples directly grown on Si/SiO 2 substrates by CVD, it was necessary to assume the triclinic crystal structure in order to explain the polarized Raman dependence of all the peaks in both parallel and crossed polarization directions. Furthermore, this is the first experimental result suggesting the existence of triclinic Cr 2 Se 3 crystal structure, which has been theoretically predicted in the Materials Project database.

36 MATERIALS SCIENCE↗

Structural basis for a highly conserved RNA-mediated enteroviral genome replication

Abstract Enteroviruses contain conserved RNA structures at the extreme 5′ end of their genomes that recruit essential proteins 3CD and PCBP2 to promote genome replication. However, the high-resolution structures and mechanisms of these replication-linked RNAs (REPLRs) are limited. Here, we determined the crystal structures of the coxsackievirus B3 and rhinoviruses B14 and C15 REPLRs at 1.54, 2.2 and 2.54 Å resolution, revealing a highly conserved H-type four-way junction fold with co-axially stacked sA-sD and sB-sC helices that are stabilized by a long-range A•C•U base-triple. Such conserved features observed in the crystal structures also allowed us to predict the models of several other enteroviral REPLRs using homology modeling, which generated models almost identical to the experimentally determined structures. Moreover, our structure-guided binding studies with recombinantly purified full-length human PCBP2 showed that two previously proposed binding sites, the sB-loop and 3′ spacer, reside proximally and bind a single PCBP2. Additionally, the DNA oligos complementary to the 3′ spacer, the high-affinity PCBP2 binding site, abrogated its interactions with enteroviral REPLRs, suggesting the critical roles of this single-stranded region in recruiting PCBP2 for enteroviral genome replication and illuminating the promising prospects of developing therapeutics against enteroviral infections targeting this replication platform.

Biochemistry & Molecular Biology↗

Synthesis, structural, and magnetic properties of Heusler-type Mn 2-x Fe 1+x Ge (0.0 ≤ x ≤ 1.0) alloys

Bulk Mn 2-x Fe 1+x Ge (0.0 ≤ x ≤ 1.0) alloys have been synthesized by arc-melting followed by a low temperature homogenization thermal annealing, whereas for comparison purposes the Mn 2 FeGe alloy was also produced in ribbon form by rapid solidification. Here, a study of the structural and magnetic properties is presented. Contrary to theoretical predictions, Mn 2 FeGe crystallizes in a hexagonal DO 19 crystal structure (space group P63/mmc) and orders ferromagnetically with a saturation magnetization (M S ) value of ~1.7 µB/f.u. in the ground state. With the substitution of Fe for Mn in bulk Mn 2-x Fe 1+x Ge, we observed an increase in the FM interactions with a maximum MS value of 5.1 µ B /f.u. for x = 1.0, and a significant progressive increase in the Curie temperature (T C ) in a wide range spanning ~200 K to over 400 K.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Crystal structure of silver pentazolates AgN 5 and AgN 6

Silver pentazolate, a high energy density compound containing the cyclo-N 5 – anion, has recently been synthesized under ambient conditions. However, due to high sensitivity to irradiation, its crystal structure has not been determined. In this work, silver–nitrogen crystalline compounds under ambient conditions and at high pressures, up to 100 GPa, are predicted and characterized by performing first-principles evolutionary crystal structure searching with variable stoichiometry. It is found that newly discovered AgN 5 and AgN 6 are the only thermodynamically stable silver–nitrogen compounds at pressures between 42 and 80 GPa. In contrast to AgN 5 , the pentazolate AgN 6 compound contains N 2 diatomic molecules in addition to cyclo-N 5 – . These AgN 5 and AgN 6 crystals are metastable under ambient conditions with positive formation enthalpies of 54.95 kJ mol –1 and 46.24 kJ mol –1 , respectively. Here, the underlying cause of the stability of cyclo-N 5 – silver pentazolates is the enhanced aromaticity enabled by the charge transfer from silver atoms to nitrogen rings. To aid in the experimental identification of these materials, calculated Raman spectra are reported at ambient pressure: the frequencies of N 5 – vibrational modes of AgN 5 are in good agreement with those measured in the experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards Efficient Uncertainty estimation in deep learning for robust energy prediction in crystal materials

In material science, recent studies have started to explore the potential of using deep learning to improve property prediction from high-fidelity simulations, e.g, density functional theory (DFT). However, the design spaces are sometimes too large and intractable to sample completely. This results in a critical question that is how to evaluate the confidence and robustness of the prediction. In this paper, we propose an efficient approach to estimate uncertainty in deep learning using a single forward pass and then apply it for robust prediction of the total energy in crystal lattice structures. Our approach is built upon the deep kernel learning (DKL) that originally introduces to leverage the expressiveness of deep neural networks as input with a probabilistic prediction of Gaussian processes (GPs) as output. Existing DKL methods have difficulties in the accuracy of predictive uncertainty, training stability, and scaling to large datasets, which lead to significant barriers in real-world applications. We propose to address these challenges by using an inducing point approximate GP in feature space combined with spectral normalization as a regularization. We finally demonstrate our robust performance on an artificial example and a real-world application from materials chemistry.

Bi, Sirui↗

A unified understanding of minimum lattice thermal conductivity

Here, we propose a first-principles model of minimum lattice thermal conductivity ($κ^{min}_L$) based on a unified theoretical treatment of thermal transport in crystals and glasses. We apply this model to thousands of inorganic compounds and find a universal behavior of $κ^{min}_L$ in crystals in the high-temperature limit: The isotropically averaged $κ^{min}_L$ is independent of structural complexity and bounded within a range from ~0.1 to ~2.6 W/(m K), in striking contrast to the conventional phonon gas model which predicts no lower bound. We unveil the underlying physics by showing that for a given parent compound, $κ^{min}_L$ is bounded from below by a value that is approximately insensitive to disorder, but the relative importance of different heat transport channels (phonon gas versus diffuson) depends strongly on the degree of disorder. Moreover, we propose that the diffuson-dominated $κ^{min}_L$ in complex and disordered compounds might be effectively approximated by the phonon gas model for an ordered compound by averaging out disorder and applying phonon unfolding. With these insights, we further bridge the knowledge gap between our model and the well-known Cahill–Watson–Pohl (CWP) model, rationalizing the successes and limitations of the CWP model in the absence of heat transfer mediated by diffusons. Finally, we construct graph network and random forest machine learning models to extend our predictions to all compounds within the Inorganic Crystal Structure Database (ICSD), which were validated against thermoelectric materials possessing experimentally measured ultralow κ L . Our work offers a unified understanding of $κ^{min}_L$, which can guide the rational engineering of materials to achieve .

42 ENGINEERING↗

High-precision predictions of properties of chemically disordered crystals

Multiple scattering theory (MST) combined with density functional theory (DFT) allows to predict properties of chemically disordered materials from the first principles. However, such predictions often suffer from the systematic errors, which depend on crystal geometry. Each computed property of a particular crystal structure typically has a relatively small random error and a larger systematic error. Cancellation of systematic errors allows more accurate predictions. We propose a computational methodology based on the subtraction of the systematic errors in MST. To exemplify it, we apply it to the precipitated alloys. Considering precipitation strengthening in Ni superalloys, we compute the relative enthalpies of the competing Ni3(Al,Ti)1 crystal structures with a chemical disorder on the Al+Ti sublattice. Such predicted composition-structure-property dependencies are useful for the guided design of the next-generation alloys with improved strength. Our predictions are validated by comparison with the results of other DFT methods (having a higher computational cost) and with experiment. We acknowledge funding of the guided design of stronger superalloys for airspace by NASA Aeronautics Research Mission Directorate (ARMD) via Transformational Tools and Technologies (TTT) Project.

Computational↗

High-precision predictions of properties of chemically disordered crystals

Multiple scattering theory (MST) combined with density functional theory (DFT) allows to predict properties of chemically disordered materials from the first principles. However, such predictions often suffer from the systematic errors, which depend on crystal geometry. Each computed property of a particular crystal structure typically has a relatively small random error and a larger systematic error. Cancellation of systematic errors allows more accurate predictions. We propose a computational methodology based on the subtraction of the systematic errors in MST. To exemplify it, we apply it to the precipitated alloys. Considering precipitation strengthening in Ni superalloys, we compute the relative enthalpies of the competing Ni_3(Al_{1-x}Ti_x)_1 crystal structures with a chemical disorder on the Al+Ti sublattice. Such predicted composition-structure-property dependencies are useful for the guided design of the next-generation alloys with improved strength. Our predictions are validated by comparison with the results of other DFT methods (having a higher computational cost) and with experiment.

density functional theory↗

Formation of iron sulphide in solar nebula

Noting that the iron sulfide in the Orgueil carbonaceous meteorite is an Fe-deficient monosulfide (pyrrhotite), it is suggested that such mineral chemistry is inconsistent with equilibrium condensation of the solar nebula and that the course of condensation may have been modified by kinetic effects. The effect of Ni on the reaction between Fe and S to produce FeS is examined, and possible reasons are considered for the fact that the cited meteorite differs in both crystal structure and Ni content from the predictions of equilibrium condensation. It is proposed that sulfide formation in the solar nebula may have been inhibited by sluggish diffusion, so that sulfur began to react with previously condensed troilite to form pyrrhotite. On this basis, observations of the Orgueil sulfides are shown to suggest that the course of solar-system condensation was modified by kinetic effects below about 700 K and that equilibrium may not have been achieved.

Kerridge, J. F.↗

Prediction of L⁢i 3 ⁢F⁡e 8 ⁢B 8 compound with rapid one-dimensional ion diffusion channels

Using a computational crystal structure search in the Li-Fe-B ternary system, we predict a stable phase of L⁢i 3 ⁢F⁡e 8 ⁢B 8 , featuring 1D channels that enable rapid Li-ion transport. Ab initio molecular dynamics simulations show that the Li-ion diffusion coefficient in L⁢i 3 ⁢F⁡e 8⁢ B 8 surpasses that of common electrode and conductive additive materials by several orders of magnitude. The high diffusion in L⁢i 3 ⁢F⁡e 8 ⁢B 8 can be explained by the Frenkel–Kontorova model, which describes an incommensurate state between the Li diffusion chain and the periodic potential field caused by the FeB backbone structure. The favorable lithium-ion diffusivity and mechanical properties of L⁢i 3 ⁢F⁡e 8 ⁢B 8 make it a promising conductive additive for battery materials. Furthermore, an external magnetic field can further manipulate the properties of this material due to its predicted itinerant ferromagnetism, which also offers a platform for exploring spin-dependent phenomena.

1-dimensional systems↗

Multiscale Modeling of Structurally-Graded Materials Using Discrete Dislocation Plasticity Models and Continuum Crystal Plasticity Models

A multiscale modeling methodology that combines the predictive capability of discrete dislocation plasticity and the computational efficiency of continuum crystal plasticity is developed. Single crystal configurations of different grain sizes modeled with periodic boundary conditions are analyzed using discrete dislocation plasticity (DD) to obtain grain size-dependent stress-strain predictions. These relationships are mapped into crystal plasticity parameters to develop a multiscale DD/CP model for continuum level simulations. A polycrystal model of a structurally-graded microstructure is developed, analyzed and used as a benchmark for comparison between the multiscale DD/CP model and the DD predictions. The multiscale DD/CP model follows the DD predictions closely up to an initial peak stress and then follows a strain hardening path that is parallel but somewhat offset from the DD predictions. The difference is believed to be from a combination of the strain rate in the DD simulation and the inability of the DD/CP model to represent non-monotonic material response.

Saether, Erik↗

The crystal structures of Fe-bearing MgCO 3 sp 2 - and sp 3 -carbonates at 98 GPa from single-crystal X-ray diffraction using synchrotron radiation

The crystal structure of MgCO 3 -II has long been discussed in the literature where DFT-based model calculations predict a pressure-induced transition of the carbon atom from the sp 2 to the sp 3 type of bonding. We have now determined the crystal structure of iron-bearing MgCO 3 -II based on single-crystal X-ray diffraction measurements using synchrotron radiation. We laser-heated a synthetic (Mg 0.85 Fe 0.15 )CO 3 single crystal at 2500 K and 98 GPa and observed the formation of a monoclinic phase with composition (Mg 2.53 Fe 0.47 )C 3 O 9 in the space group C 2/ m that contains tetrahedrally coordinated carbon, where CO 4 4- tetrahedra are linked by corner-sharing oxygen atoms to form three-membered C 3 O 9 6- ring anions. The crystal structure of (Mg 0.85 Fe 0.15 )CO 3 (magnesium iron carbonate) at 98 GPa and 300 K is reported here as well. In comparison with previous structure-prediction calculations and powder X-ray diffraction data, our structural data provide reliable information from experiments regarding atomic positions, bond lengths, and bond angles.

Chariton, Stella (ORCID:0000000155220498)↗

Discovery of Ternary Antimonides A–Al–Sb (A = Rb or Cs) with Desired Structural Motifs Guided by Machine Learning

Specific structural motifs in inorganic solids are often related to their targeted physical properties. For many classes of solids, such as Zintl phases and polar intermetallics, the crystal structures are diverse and not easy to predict. Various antimonides that are potential thermoelectric materials were proposed to be synthesizable on the basis of their estimated formation energies. Their structures were broadly classified as clathrate, channel, layered, or network through a machine learning model trained on existing ternary phases and features based on elemental properties using the sure independence screening and sparsifying operator algorithm. Through experimental validation, three new ternary antimonides were synthesized and confirmed to form layered structures: tetragonal RbAlSb 2 and CsAlSb 2 , which are isopointal but not isotypic to LiBSi 2 ; and monoclinic Rb 2 Al 2 Sb 3 , which adopts the Na 2 Al 2 Sb 3 -type structure. Finally, reinvestigation of the related compound Cs 2 In 2 Sb 3 revealed a low thermal conductivity and p-type semiconducting behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

S -Adenosylhomocysteine Analogs Selectively Suppress Pan-Coronavirus Replication by Inhibition of nsp14 Methyltransferase

To address the ongoing threat of SARS-CoV-2 and potential emergence of novel coronaviruses, we employed a comprehensive strategy to identify and synthesize inhibitors of coronavirus methyltransferases with chemical analogs of S-adenosylhomocysteine (SAH). Two analogs, designated 4h and 4p, inhibit both mouse hepatitis virus and SARS-CoV-2 replication. Compound 4p was the most potent with half-maximal inhibition of biochemical activity at 0.2 μM and antiviral activity at ∼20 μM. This compound also has low cytotoxicity and preferentially inhibits nsp14 over nsp16 and human methyltransferases. Furthermore, molecular docking based on a newly determined crystal structure of the apo nsp16−nsp10 complex predicts that 4p occupies both the Sadenosylmethione and Gppp binding pockets of nsp14 and nsp16. Selectivity of 4p for nsp14 is likely due to the enhanced structural stability of the nsp14 binding pocket relative to nsp16. These findings highlight SAH analogs as scaffolds for pan-coronavirus therapeutics and underscore the value of structure-guided design in antiviral drug discovery.

Coronavirus↗

Piezoelectricity and pyroelectricity in polyvinylidene fluoride - Influence of the lattice structure

Piezoelectric and pyroelectric responses of beta-phase (Phase I) polyvinylidene fluoride are predicted for a model system of polarizable point dipoles. The model incorporates the influence of the orthorhombic crystal structure by including the dependence of the internal electric field on the lattice parameters. Strong anisotropy in the piezoelectric response under uniaxial stress is predicted as a consequence of the orthorhombic lattice structure. Predictions are found to be in reasonable agreement with room-temperature experimental data.

Purvis, C. K.↗

Structure of the divergent human astrovirus MLB capsid spike

Despite their worldwide prevalence and association with human disease, the molecular bases of human astrovirus (HAstV) infection and evolution remain poorly characterized. Here, we report the structure of the capsid protein spike of the divergent HAstV MLB clade (HAstV MLB). While the structure shares a similar folding topology with that of classical-clade HAstV spikes, it is otherwise strikingly different. We find no evidence of a conserved receptor-binding site between the MLB and classical HAstV spikes, suggesting that MLB and classical HAstVs utilize different receptors for host-cell attachment. We provide evidence for this hypothesis using a novel HAstV infection competition assay. Comparisons of the HAstV MLB spike structure with structures predicted from its sequence reveal poor matches, but template-based predictions were surprisingly accurate relative to machine-learning-based predictions. Our data provide a foundation for understanding the mechanisms of infection by diverse HAstVs and can support structure determination in similarly unstudied systems.

59 BASIC BIOLOGICAL SCIENCES↗