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The entanglement entropy of selected quantum Hall states in the presence of short-range random disorder is calculated using direct diagonalization.
Pd-intercalated ErTe 3 is studied as a model system to explore the effect of "intertwined" superconducting and charge density wave (CDW) orders. Despite the common wisdom that superconductivity emerges only when CDW is suppressed, we present data from STM and AC susceptibility measurements that show no direct competition between CDW order and superconductivity. Both coexist over most of the intercalation range, with uniform superconductivity over length scales that exceed the superconducting coherence length. This is despite persisting short-range CDW order and increased scattering from the Pd intercalation. While superconductivity is insensitive to local defects in either of the bi-directional CDWs, vestiges of the Fermi-level distortions are observed in the properties of the superconducting state.
We introduce the fermionized time-dependent Hartree–Fock (fTDHF), a real-time quantum dynamics method for spin-1/2 Hamiltonians following their mapping to fermions via the Jordan-Wigner transformation. fTDHF is formally equivalent to exact dynamics in the case of free fermions, and can efficiently handle non-local string operators arising from long-range interactions via transition matrix elements between non-orthogonal Slater determinants. We show that the fTDHF method can be implemented on a classical computer with a cost that scales polynomially with system size, and linearly with the time steps. We benchmark fTDHF against exact dynamics on three separate spin-1/2 models, representing adiabatic preparation of states with long-range correlations, disorder-driven observation of many-body localization, and particle production in the Schwinger model. For each of these systems, fTDHF is shown to reproduce the qualitative dynamics generated by the exact evolutions, while maintaining a simple physical picture due to its mean-field nature.
C–C coupling reactions are of great importance in the synthesis of numerous organic compounds, where Pd nanoparticle catalyzed systems represent new materials to efficiently drive these reactions. Despite their pervasive utility, the catalytic mechanism of these particle-based reactions remains highly contested. Herein we present evidence of an atom leaching mechanism for Stille coupling under aqueous conditions using peptide-capped Pd nanoparticles. EXAFS analysis revealed Pd coordination changes in the nanoparticle consistent with Pd atom abstraction, where sizing analysis by SAXS confirmed particle size changes associated with a leaching process. It is likely that recently discovered highly disordered surface Pd atoms are the favored catalytic active sites and are leached during oxidative addition, resulting in smaller particles. Thus, probing the mechanism of nanoparticle-driven C–C coupling reactions through structural analyses provides fundamental information concerning these active sites and their reactivity at the atomic-scale, which can be used to improve catalytic performance to meet important sustainability goals.
Two-step nucleation pathways in which disordered, amorphous, or dense liquid states precede the appearance of crystalline phases have been reported for a wide range of materials, but the dynamics of such pathways are poorly understood. Moreover, whether these pathways are general features of crystallizing systems or a consequence of system-specific structural details that select for direct versus two-step processes is unknown. Using atomic force microscopy to directly observe crystallization of sequence-defined polymers, we show that crystallization pathways are indeed sequence dependent. When a short hydrophobic region is added to a sequence that directly forms crystalline particles, crystallization instead follows a two-step pathway that begins with the creation of disordered clusters of 10–20 molecules and is characterized by highly non-linear crystallization kinetics in which clusters transform into ordered structures that then enter the growth phase. The results shed new light on non-classical crystallization mechanisms and have implications for the design of self-assembling polymer systems.
This pilot study suggests relatively short (median 12 days long) low-Earth orbit (LEO) spaceflight induces changes in circulating plasma small extracellular vesicle (sEV) microRNA expression. Normalization of small RNA sequencing (sRNAseq) data and quantitative polymerase chain reaction (qPCR) validation confirmed miR-4732-3p is significantly upregulated up to 3 days post-landing, and enrichment analysis suggests this miRNA is expressed in various central nervous system tissues and hematopoietic cells and may be linked to different organ disorders.
Introduction: Pulled or dislodged gastrostomy catheters represent a common complication associated with percutaneous gastrostomy and are a common cause of recurrent visits in patients with altered mental status. We intended to perform an experiment to compare the pull forces required to dislodge different commonly used gastrostomy catheters. Materials and Methods: We used a digital force gauge device to measure the pull forces required to dislodge three types of 20 French gastrostomy catheters in double-layer skin models. These included the Flow 20 Pull Method (Cook Medical, Bloomington, IN, USA), Entuit Gastrostomy BR Balloon Retention feeding tube (Cook Medical, Bloomington, IN, USA), and Ponsky Non-Balloon Replacement Gastrostomy Tube (CR Bard Inc, Salt Lake City, Utah, USA). The catheters were inserted into the skin model using the same technique as would be utilized in a patient. Results: The mean forces measured to dislodge the per-oral Flow 20 Pull Method, Entuit Thrive Balloon Retention, and button-type retention Ponsky replacement catheters were 35.6, 22.8, and 20.6 Newtons, respectively. The pull method per-oral gastrostomy catheter required significantly more pull force to dislodge than both the Ponsky button-type retention catheter and the Entuit balloon retention catheters. There was no significant difference in the pull force required to dislodge the Ponsky replacement catheter and the Entuit balloon retention catheter. Conclusions: Per-oral image-guided gastrostomy with pull-method button-type retention catheters may be the ideal choice in patients at high risk of tube dislodgment.
A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multi-scale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multi-scale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multi-scale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical techniques employed for multi-scale modeling approaches used in pharmacology and present several examples illustrating the current state-of-the-art regarding drug development for: Excitable Systems (Heart); Cancer (Metastasis and Differentiation); Cancer (Angiogenesis and Drug Targeting); Metabolic Disorders; and Inflammation and Sepsis. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multi-scale models.
Thermoelectric energy converters offer a promising solution to generate electrical power using heat in the nuclear reactor core. Despite significant improvements in thermoelectric efficiency of nanostructured materials, the performance of these advanced materials has yet to be demonstrated in the harsh radiation environment of a reactor core. Herein, we demonstrate a thermoelectric generator (TEG) made from nanostructured bulk half-Heusler (HH) materials generating stable electrical power density > 1140 W/m 2 after 30 days in the MIT Nuclear Research Reactor under an unprecedented fast-neutron (>1 MeV) fluence of 1.5 × 10 20 n/cm 2 . Despite an initial degradation due to irradiation damage when operating under relatively low temperatures, our TEG showed a 20-fold increase in power output when operating under high temperature due to in-situ annealing and resulting thermoelectric property recovery. First-principles modeling indicates that a chemically disordered metallic phase was formed under irradiation at lower temperatures, resulting in a drastic degradation in thermoelectric properties, while at sufficiently high temperatures the system returned to the initial chemically ordered HH phase and the thermoelectric properties recovered. Transmission electron microscopy and electron diffraction demonstrated that the chemically disordered phase was formed upon ion irradiation, confirming the prediction from first-principles simulations. Furthermore, the results suggest that with proper control over the TEG operating temperatures, the nanostructured bulk TEGs could produce stable electrical power and operate indefinitely in the core of a nuclear reactor.
La 3 Co 4 Sn 13 and La 3 Ru 4 Sn 13 were categorized as BCS superconductors. In a plot of the critical field H c2 vs T, La 3 Ru 4 Sn 13 displays a second superconducting phase at the higher critical temperature T c *, characteristic of inhomogeneous superconductors, while La 3 Co 4 Sn 13 shows bulk superconductivity below T c . We observe a decrease in critical temperatures with external pressure and magnetic field for both compounds. Additionally, for La 3 Ru 4 Sn 13 we find that T c */dP>dT c /dP. The pressure dependences of T c are interpreted according to the McMillan theory and understood to be a consequence of lattice stiffening. The investigation of the superconducting state of La 3 Co x Ru 4–x Sn 13 shows a T c * that is larger then T c for x < 4. Furthermore, this unique and unexpected observation is discussed as a result of the local disorder and/or the effect of chemical pressure when Ru atoms are partially replaced by smaller Co atoms.
Highlights: • Rietveld refine XRD pattern confirmed that all samples exhibit ZnO structure. • XANES analysis at Tb L3-edge ascertained the presence of Tb{sup +3}state. • XANES analysis at Zn K-edge confirmed the Zn{sup +2}state. • EXAFS study authenticated the decrease in disorder due to Li co-doping. - Abstract: The presence of lattice distortion and defects in a composition leads towards a significant change in the optical, magnetic and electrical properties of the host material. In the present work, we have investigated the role of Li concentrations (0.25–1.0%) on structural property of Tb (1%) doped zinc oxide nanoparticles. A small concentration of terbium (1%) has been used to get minimum lattice distortion in the original structure of ZnO. To reduce the possible large lattice deformation on doping of Tb ion we have co-doped the material with Li. The crystalline nature of the sample has been confirmed by the XRD, Raman and FTIR studies of the material. The variation of bond length and lattice disorder in ZnO lattice due to the substitution of Tb and Li were studied from the EXAFS analysis at Zn K edge and Tb L3 edge. Interestingly, the study also shows that disorder decreases due to co-doping of Li in the considered system. Moreover, the oxidation states of all the elements present in the prepared samples were ascertained the XANES analysis. The morphology and particle size are calculated by TEM characterization. This work mainly emphasises on the structural property of synthesized compositions using these analyses. The study will also be helpful in exploring the change in optical, magnetic and electrical properties of the doped ZnO nanoparticles.
Muscular dystrophies are a heterogeneous group of monogenic neuromuscular disorders which lead to progressive muscle loss and degeneration of the musculoskeletal system. The genetic causes of muscular dystrophies are well characterized, but no effective treatments have been developed so far. The discovery and application of the CRISPR/Cas system for genome editing offers a new path for disease treatment with the potential to permanently correct genetic mutations. The post-mitotic and multinucleated features of skeletal muscle provide an ideal target for CRISPR/Cas therapeutic genome editing because correction of a subpopulation of nuclei can provide benefit to the whole myofiber. In this review, we provide an overview of the CRISPR/Cas system and its derivatives in genome editing, proposing potential CRISPR/Cas-based therapies to correct diverse muscular dystrophies, and we discuss challenges for translating CRISPR/Cas genome editing to a viable therapy for permanent correction of muscular dystrophies.
The first kinase inhibitor drug approval in 2001 initiated a remarkable decade of tyrosine kinase inhibitor drugs for oncology indications, but a void exists for serine/threonine protein kinase inhibitor drugs and central nervous system indications. Stress kinases are of special interest in neurological and neuropsychiatric disorders due to their involvement in synaptic dysfunction and complex disease susceptibility. Clinical and preclinical evidence implicates the stress related kinase p38αMAPK as a potential neurotherapeutic target, but isoform selective p38αMAPK inhibitor candidates are lacking and the mixed kinase inhibitor drugs that are promising in peripheral tissue disease indications have limitations for neurologic indications. Therefore, pursuit of the neurotherapeutic hypothesis requires kinase isoform selective inhibitors with appropriate neuropharmacology features. Synaptic dysfunction disorders offer a potential for enhanced pharmacological efficacy due to stress-induced activation of p38αMAPK in both neurons and glia, the interacting cellular components of the synaptic pathophysiological axis to be modulated. We report a novel isoform selective p38αMAPK inhibitor, MW01-18-150SRM (= MW150), that is efficacious in suppression of hippocampal-dependent associative and spatial memory deficits in two distinct synaptic dysfunction mouse models. A synthetic scheme for biocompatible product and positive outcomes from pharmacological screens are presented. The high-resolution crystallographic structure of the p38αMAPK:MW150 complex documents active site binding, reveals a potential low energy conformation of the bound inhibitor, and suggests a structural explanation for MW150’s exquisite target selectivity. As far as we are aware, MW150 is without precedent as an isoform selective p38MAPK inhibitor or as a kinase inhibitor capable of modulating in vivo stress related behavior
Introducing mesoporosity to conventional microporous sorbents or catalysts is often proposed as a solution to enhance their mass transport rates. Here, we show that diffusion in these hierarchical materials is more complex and exhibits non-monotonic dependence on sorbate loading. Our atomistic simulations of n-hexane in a model system containing microporous nanosheets and mesopore channels indicate that diffusivity can be smaller than in a conventional zeolite with the same micropore structure, and this observation holds true even if we confine the analysis to molecules completely inside the microporous nanosheets. Only at high sorbate loadings or elevated temperatures, when the mesopores begin to be sufficiently populated, does the overall diffusion in the hierarchical material exceed that in conventional microporous zeolites. Here, our model system is free of structural defects, such as pore blocking or surface disorder, that are typically invoked to explain slower-than-expected diffusion phenomena in experimental measurements. Examination of free energy profiles and visualization of molecular diffusion pathways demonstrates that the large free energy cost (mostly enthalpic in origin) for escaping from the microporous region into the mesopores leads to more tortuous diffusion paths and causes this unusual transport behavior in hierarchical nanoporous materials. This knowledge allows us to re-examine zero-length-column chromatography data and show that these experimental measurements are consistent with the simulation data when the crystallite size instead of the nanosheet thickness is used for the nominal diffusional length.
Abstract Machine learning models with uncertainty quantification have recently emerged as attractive tools to accelerate the navigation of catalyst design spaces in a data-efficient manner. Here, we combine active learning with a dropout graph convolutional network (dGCN) as a surrogate model to explore the complex materials space of high-entropy alloys (HEAs). We train the dGCN on the formation energies of disordered binary alloy structures in the Pd-Pt-Sn ternary alloy system and improve predictions on ternary structures by performing reduced optimization of the formation free energy, the target property that determines HEA stability, over ensembles of ternary structures constructed based on two coordinate systems: (a) a physics-informed ternary composition space, and (b) data-driven coordinates discovered by the Diffusion Maps manifold learning scheme. Both reduced optimization techniques improve predictions of the formation free energy in the ternary alloy space with a significantly reduced number of DFT calculations compared to a high-fidelity model. The physics-based scheme converges to the target property in a manner akin to a depth-first strategy, whereas the data-driven scheme appears more akin to a breadth-first approach. Both sampling schemes, coupled with our acquisition function, successfully exploit a database of DFT-calculated binary alloy structures and energies, augmented with a relatively small number of ternary alloy calculations, to identify stable ternary HEA compositions and structures. This generalized framework can be extended to incorporate more complex bulk and surface structural motifs, and the results demonstrate that significant dimensionality reduction is possible in thermodynamic sampling problems when suitable active learning schemes are employed.
The low-energy ion-bombardment induced surface nanotopography and the nanopatterning of Si has been simulated by atomistic simulations using an approach based on molecular dynamics (MD). In order to speed up simulations a reasonable cutoff in simulation time and increased cooling rates for keeping in hand the system temperature have been used. We get an unexpectedly rich variety of disordered nanopatterns formed by the self-organization of the crater rims and adatoms islands generated by the individual ion impacts. Our results reveal that the low-energy (0.5 keV impact energy) ion-sputtered Si surface is not smooth at the sub-20 nm length scale and deep nanoholes rule the landscape. Moreover substantial nanoporosity is found beneath the surface with the size range of a few nanometer. Scanning tunneling microscopy (STM) images are also shown obtained for low-fluence ion-sputtering of Si at 2 keV impact energy at 30 deg. angle of incidence. STM images reveal similar features obtained by computer simulations: nanoholes can be seen with a few nanometer diameter. The overall topography landscape as well as the rms surface roughness also show similar features for the images obtained by STM or MD at 2 keV impact energy. The applied approach could make it possible the simulation of nanotopographic images at the molecular dynamics level of theory and could help resolve scanning probe microscopy images in the sub-20 nm length scale regime.
Significance In X-ray absorption spectroscopy, an electron–hole excitation probes the local atomic environment. The interpretation of the spectra requires challenging theoretical calculations, particularly in a system like liquid water, where quantum many-body effects and molecular disorder play an important role. Recent advances in theory and simulation make possible new calculations that are in good agreement with experiment, without recourse to commonly adopted approximations. Based on these calculations, the three features observed in the experimental spectra are unambiguously attributed to excitonic effects with different characteristic correlation lengths, which are distinctively affected by perturbations of the underlying H-bond structure induced by temperature changes and/or by isotopic substitution. The emerging picture of the water structure is fully consistent with the conventional tetrahedral model.
Here, in this work, we investigate the softening of the in-plane transverse acoustic phonon driven by electronic nematicity in BaFe 2 (As 1−𝑥 P 𝑥 ) 2 using inelastic x-ray scattering, with a focus on the optimally doped sample (𝑥 = 0.31) sample—a system exhibiting signatures of a putative nematic quantum critical point and minimal disorder among iron pnictides. We observe only a modest softening of the phonon frequency and no evidence of critical damping, suggesting that the nematic quantum critical fluctuations couple only weakly to the lattice from our quantum critical model. Given the close proximity of the structural and magnetic transition temperatures in the underdoped sample—which implies that spin-nematic fluctuations couple strongly to the lattice—we conjecture that the quantum critical nematic fluctuations are predominantly orbital in origin.