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Atomic number estimation of dual energy cargo radiographs using a semiempirical transparency model
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Global baryon number conservation encoded in net-proton fluctuations measured in Pb–Pb collisions at s NN = 2.76 TeV
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Gauged lepton number, Dirac neutrinos, dark matter, and muon g − 2
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Thermodynamic approach to proton number fluctuations in baryon-rich heavy-ion matter created at moderate collision energies
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Ab initio computations from 78Ni towards 70Ca along neutron number N = 50
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Development of deformed intruder structures along the N=50 magic number: Insights from 83 Se
The 83 Se nucleus was studied in the context of shape coexistence employing a 82 Se(d,p) 83 Se reaction performed in inverse kinematics with the GALILEO-II + SPIDER setup to reach the desired selectivity on the reaction channel of interest via γ -particle coincidences. The lifetimes of the 1/2 + 540-keV and 3/2$^{+}_{3}$ 1100-keV low-lying intruder states of 83 Se were measured for the first time by employing the Recoil Distance Doppler Shift and the Doppler Shift Attenuation Method. The deduced transition probabilities, together with the mixing ratios obtained from a separate neutron-capture experiment performed at ILL with the FIPPS array, are compared and discussed in the framework of shell-model calculations performed with the PFSDG-U Hamiltonian. Large transition probabilities of hundreds of e 2 fm 4 were found for the E 2 decays of the states built on top of the intruders, pointing to the development of quadrupole collectivity and large deformation in the proximity of N = 50 shell closure.
Running the numbers on plant synthetic biology solutions to global problems
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Sensitive Top-Down Proteomics Analysis of a Low Number of Mammalian Cells Using a Nanodroplet Sample Processing Platform
Top-down proteomics is a powerful tool for characterizing genetic variations and post-translational modifications at intact protein level. That being said, one significant technical gap of top-down proteomics is the inability to analyze low amount of biological samples, which limits its access to isolated rare cells, fine-needle aspiration biopsies, and tissue substructures. Herein, we developed an ultrasensitive top-down platform by incorporating a microfluidic sample preparation system, termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples), into a top-down proteomics workflow. A unique combination of a nonionic detergent dodecyl-ß-D-maltopyranoside (DDM) with urea as protein extraction buffer significantly improved both protein extraction efficiency and sample recovery. We hypothesize that the DDM detergent improves protein recovery by efficiently reducing non-specific adsorption of intact proteins on container surfaces, while urea serves as a strong denaturant to disrupt noncovalent complexes and release intact proteins for downstream analysis. The nanoPOTS-based top-down platform reproducibly and quantitatively identified ~170 to ~620 proteoforms from ~70 to ~770 HeLa cells containing ~10 to ~115 ng of total protein. A variety of post-translational modifications including acetylation, myristoylation, and iron binding were identified using only less than 800 cells. We anticipate the nanoPOTS top-down proteomics platform will be broadly applicable in biomedical researches, particularly where clinical specimens are not available in amounts amenable to standard workflows.
Polymer Molecular Weight Distributions: A Tutorial on Transformations between Number Density, Mass Density, and Linear/Logarithmic Axes
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Correction to Benchmarking Coordination Number Prediction Algorithms on Inorganic Crystal Structures
The corrections are typographical errors only and do not alter the results or analysis in the original manuscript.
Lucky Number 13: A 13-Layer Polytype of the Alkyne Hydrogenation Catalyst CaGaGe
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Low-Energy Isomers of the Magic Number H + (H 2 O) 21 Cluster
Electronic structure calculations are used to characterize low-energy isomers of H + (H 2 O) 21 . Eleven different classes of isomers, based on the (H 2 O) 20 pentagonal dodecahedron with the excess proton localized on the surface (as a hydrated hydronium ion) and the “extra” water molecule located in the interior of the cluster, are characterized. In 10 of these classes, the internal water molecule is engaged in six 5-membered rings, but in the remaining class, which is predicted to start at only 0.6 kcal/mol above the global minimum, the internal water is engaged in a 4- membered ring, an additional 6-membered ring, and four 5- membered rings. In addition, isomers with two 4-membered rings and two 6-membered rings on the cluster surface are predicted to start at only ∼1.3 kcal/mol above the lowest-energy dodecahedralbased structure.
First-Principles-Based Study of the Decomposition of Phenol and Hydroquinone on Pt(111) Combined with Quantitative Information from XPS Spectra to Address the Impact of Coverage and Number of Hydroxyl Functional Groups
A combined first-principles-based and experimental X-ray photoelectron spectroscopy approach was used to investigate the thermal decomposition of two model biofuel compounds, phenol and hydroquinone, on Pt(111) at both low and high coverages. The DFT-based approach yields adsorption geometries and energies, activation barriers and core-level binding energy shifts for C 1s and O 1s. Increasing the coverage in the theoretical model leads to slight shifts in core-level binding energies─toward higher values for C 1s and lower values for O 1s. It also alters the energy profiles of the decomposition reaction pathway, resulting in weaker adsorption energies and changes in both reaction and activation barriers. At low temperatures, we observe a multilayer for phenol and hydroquinone upon adsorption, with desorption occurring at 200 and 270 K, respectively. Following desorption of the multilayer, decomposition proceeds via initial O–H bond scission, followed by two parallel pathways involving either C–H or C–C bond scission, whereby in the case of phenol C–H bond scission occurs first. Here, we further provide characteristic core level binding energies by theoretical calculations that are subsequently used in experimental analyses, establishing a reference database for key spectra of phenolic functionalities applicable to a range of catalytic reactions.