Hidden Effects of Negative Stacking Fault Energies in Complex Concentrated Alloys.

Negative stacking fault energies (SFEs) are found in face-centered cubic high-entropy alloys with excellent mechanical properties, especially at low temperatures. Their roles remain elusive due to the lack of in situ observation of nanoscale deformation. Here, the polymorphism of Shockley partials is fully explored, assisted by a new method. We show negative SFEs result in novel partial pairs as if they were in hexagonal close-packed alloys. The associated yield stresses are much higher than those for other mechanisms at low temperatures. This generalizes the physical picture for all negative-SFE alloys.

Mesoporous Iron Sulfide for Highly Efficient Electrocatalytic Hydrogen Evolution.

We report a facile synthetic protocol to prepare mesoporous FeS2 without the aid of hard template as an electrocatalyst for the hydrogen evolution reaction (HER). The mesoporous FeS2 materials with high surface area were successfully prepared by a sol-gel method following a sulfurization treatment in an H2S atmosphere. A remarkable HER catalytic performance was achieved with a low overpotential of 96 mV at a current density of 10 mA·cm-2 and a Tafel slope of 78 mV per decade under alkaline conditions (pH 13). The theoretical calculations indicate that the excellent catalytic activity of mesoporous FeS2 is attributed to the exposed (210) facets. The mesoporous FeS2 material might be a promising alternative to the Pt-based electrocatalysts for water splitting.

Mesoporous Manganese Oxide Catalyzed Aerobic Oxidative Coupling of Anilines To Aromatic Azo Compounds.

Herein we introduce an environmentally friendly approach to the synthesis of symmetrical and asymmetrical aromatic azo compounds by using air as the sole oxidant under mild reaction conditions in the presence of cost-effective and reusable mesoporous manganese oxide materials.

A community effort for COVID-19 Ontology Harmonization.

Ontologies have emerged to become critical to support data and knowledge representation, standardization, integration, and analysis. The SARS-CoV-2 pandemic led to the rapid proliferation of COVID-19 data, as well as the development of many COVID-19 ontologies. In the interest of supporting data interoperability, we initiated a community-based effort to harmonize COVID-19 ontologies. Our effort involves the collaborative discussion among developers of seven COVID-19 related ontologies, and the merging of four ontologies. This effort demonstrates the feasibility of harmonizing these ontologies in an interoperable framework to support integrative representation and analysis of COVID-19 related data and knowledge.

Best influential spreaders identification using network global structural properties.

Influential spreaders are the crucial nodes in a complex network that can act as a controller or a maximizer of a spreading process. For example, we can control the virus propagation in an epidemiological network by controlling the behavior of such influential nodes, and amplify the information propagation in a social network by using them as a maximizer. Many indexing methods have been proposed in the literature to identify the influential spreaders in a network. Nevertheless, we have notice that each individual network holds different connectivity structures that we classify as complete, incomplete, or in-between based on their components and density. These affect the accuracy of existing indexing methods in the identification of the best influential spreaders. Thus, no single indexing strategy is sufficient from all varieties of network connectivity structures. This article proposes a new indexing method Network Global Structure-based Centrality (ngsc) which intelligently combines existing kshell and sum of neighbors' degree methods with knowledge of the network's global structural properties, such as the giant component, average degree, and percolation threshold. The experimental results show that our proposed method yields a better spreading performance of the seed spreaders over a large variety of network connectivity structures, and correlates well with ranking based on an SIR model used as ground truth. It also out-performs contemporary techniques and is competitive with more sophisticated approaches that are computationally cost.

A Combined Experimental and First-Principles Based Assessment of Finite-Temperature Thermodynamic Properties of Intermetallic Al3Sc.

We present a first-principles assessment of the finite-temperature thermodynamic properties of the intermetallic Al3Sc phase including the complete spectrum of excitations and compare the theoretical findings with our dilatometric and calorimetric measurements. While significant electronic contributions to the heat capacity and thermal expansion are observed near the melting temperature, anharmonic contributions, and electron-phonon coupling effects are found to be relatively small. On the one hand, these accurate methods are used to demonstrate shortcomings of empirical predictions of phase stabilities such as the Neumann-Kopp rule. On the other hand, their combination with elasticity theory was found to provide an upper limit for the size of Al3Sc nanoprecipitates needed to maintain coherency with the host matrix. The chemo-mechanical coupling being responsible for the coherency loss of strengthening precipitates is revealed by a combination of state-of-the-art simulations and dedicated experiments. These findings can be exploited to fine-tune the microstructure of Al-Sc-based alloys to approach optimum mechanical properties.

The phonon spectra and elastic constants of Pd(x)Fe(1-x): an understanding from inter-atomic interactions.

Understanding the role of the inter-atomic force constants in lattice dynamics of random binary alloys is a challenging problem. Addressing these inter-atomic interactions accurately is a necessity to obtain an accurate phonon spectrum and to calculate properties from them. Using a combination of ab initio density functional perturbation theory (DFPT) and the itinerant coherent potential approximation (ICPA), an analytic, self-consistent method for performing configuration averaging in random alloys, we model the inter-atomic force constants for Pd(0.96)Fe(0.04) and Pd(0.9)Fe(0.1) alloys based upon the ab initio results and intuitive arguments. The calculated phonon dispersion curves and elastic constants agree very well with the experimental results. Comparison of our results with those obtained in a model potential scheme is also done. The modeling of inter-atomic interactions in random alloys and their roles regarding the phonon-related properties are also discussed in light of these results.

Lithium promoted mesoporous manganese oxide catalyzed oxidation of allyl ethers.

Herein we report the first example of the catalytic aerobic partial oxidation of allyl ether to its acrylate ester derivative. Many partial oxidations often need an expensive oxidant such as peroxides or other species to drive such reactions. In addition, selective generation of esters using porous catalysts has been elusive. This reaction is catalyzed by a Li ion promoted mesoporous manganese oxide (meso-Mn2O3) under mild conditions with no precious metals, a reusable heterogeneous catalyst, and easy isolation. This process is very attractive for the oxidation of allyl ethers. We report on the catalytic activity, selectivity, and scope of the reaction. In the best cases presented, almost complete conversion of allyl ether with near complete chemo-selectivity towards acrylate ester derivatives is observed. Based on results from controlled experiments, we propose a possible reaction mechanism for the case in which N-hydroxyphthalimide (NHPI) is used in combination with trichloroacetonitrile (CCl3CN).

Trends in Solid Adsorbent Materials Development for CO2 Capture.

A recent report from the United Nations has warned about the excessive CO2 emissions and the necessity of making efforts to keep the increase in global temperature below 2 °C. Current CO2 capture technologies are inadequate for reaching that goal, and effective mitigation strategies must be pursued. In this work, we summarize trends in materials development for CO2 adsorption with focus on recent studies. We put adsorbent materials into four main groups: (I) carbon-based materials, (II) silica/alumina/zeolites, (III) porous crystalline solids, and (IV) metal oxides. Trends in computational investigations along with experimental findings are covered to find promising candidates in light of practical challenges imposed by process economics.

Heterogeneous mesoporous manganese/cobalt oxide catalysts for selective oxidation of 5-hydroxymethylfurfural to 2,5-diformylfuran.

We report a heterogeneous catalytic protocol for the oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-diformylfuran (DFF) using a mesoporous manganese doped cobalt oxide material. The absence of precious metals and additives, use of air as the sole oxidant, and easy isolation of products, along with proper catalyst reusability, make our catalytic protocol attractive for the selective oxidation of HMF to DFF.

Albumin removal from human serum using surface nanopockets on silica-coated magnetic nanoparticles.

Selective removal of albumin from human serum is an essential step prior to proteomic analyses, especially when using mass spectrometry. Here we report stable synthetic nanopockets on magnetic nanoparticle surfaces that bind to human serum albumin (HSA) with high affinity and specificity. The nanopockets are created by templating HSA on 200 nm silica-coated paramagnetic nanoparticles using polymer layers made using 4 organo-silane monomers. These monomers have amino acid-like side chains providing hydrophobic, hydrophilic and H-bonding interactions that closely mimic features of binding sites on antibodies. The binding capacity of the material was 21 mg HSA g-1, and consistently removed ∼88% albumin from human serum in multiple repeated use.

A new first principles approach to calculate phonon spectra of disordered alloys.

The lattice dynamics in substitutional disordered alloys with constituents having large size differences is driven by strong disorder in masses, inter-atomic force constants and local environments. In this paper, a new first principles approach based on special quasirandom structures and an itinerant coherent potential approximation to compute the phonon spectra of such alloys is proposed and applied to Ni0.5Pt0.5 alloy. The agreement between our results and experiments is found to be much better than for previous models of disorder due to an accurate treatment of the interplay of inter-atomic forces among various pairs of chemical species. This new formalism serves as a potential solution to the longstanding problem of a proper microscopic understanding of lattice dynamical behavior of disordered alloys.

Phonon spectra of Pd(x)Fe(1-x) alloys with transferable force constants.

The transferable force constant model of van de Walle et al (2002 Rev. Mod. Phys. 74 11) has been combined with the itinerant coherent potential approximation to calculate the complete phonon spectra and elastic constants in the magnetic type-II alloy Pd(x)Fe(1-x) across the concentration range. The calculated dispersion curves and elastic constants agree very well with the experiments. We discuss the results in the light of the behavior of inter-atomic force constants between various pairs of chemical species. The results demonstrate that the combination of the transferable force constant model and the ICPA method for configuration averaging serve as an efficient and reliable first-principles-based tool to compute the phonon spectra for disordered alloys at any arbitrary concentration.