Adsorption energies of benzene on close packed transition metal surfaces using the random phase approximation

The authors acknowledge financial support from the Scottish Funding Council (through EaStCHEM and SRD-Grant HR07003) and from EPSRC (PhD studentship for JAGT, EP/M506631/1). Funding by the Austrian Science Fund (FWF): F41 (SFB ViCoM) is grateful acknowledged.The adsorption energy of benzene on various metal substrates is predicted using the random phase approximation (RPA) for the correlation energy. Agreement with available experimental data is systematically better than 10% for both coinage and reactive metals. The results are also compared with more approximate methods, including vdW-density functional theory (DFT), as well as dispersion corrected DFT functionals. Although dispersion corrected DFT can yield accurate results, for instance, on coinage metals, the adsorption energies are clearly overestimated on more reactive transition metals. Furthermore, coverage dependent adsorption energies are well described by the RPA. This shows that for the description of aromatic molecules on metal surfaces further improvements in density functionals are necessary, or more involved many body methods such as the RPA are required.PostprintPeer reviewe

Overcoming the Size Limit of First Principles Molecular Dynamics Simulations with an In-Distribution Substructure Embedding Active Learner

Large-scale first principles molecular dynamics are crucial for simulating complex processes in chemical, biomedical, and materials sciences. However, the unfavorable time complexity with respect to system sizes leads to prohibitive computational costs when the simulation contains over a few hundred atoms in practice. We present an In-Distribution substructure Embedding Active Learner (IDEAL) to enable efficient simulation of large complex systems with quantum accuracy by maintaining a machine learning force field (MLFF) as an accurate surrogate to the first principles methods. By extracting high-uncertainty substructures into low-uncertainty atom environments, the active learner is allowed to concentrate on and learn from small substructures of interest rather than carrying out intractable quantum chemical computations on large structures. IDEAL is benchmarked on various systems and shows sub-linear complexity, accelerating the simulation thousands of times compared with conventional active learning and millions of times compared with pure first principles simulations. To demonstrate the capability of IDEAL in practical applications, we simulated a polycrystalline lithium system composed of one million atoms and the full ammonia formation process in a Haber-Bosch reaction on a 3-nm Iridium nanoparticle catalyst on a computing node comprising one single A100 GPU and 24 CPU cores

Elucidation of temperature-programmed desorption of high-coverage hydrogen on Pt(211), Pt(221), Pt(533) and Pt(553) based on density functional theory calculations

Publisher's version (útgefin grein)In this work we compute high-coverage hydrogen adsorption energies and geometries on the stepped platinum surfaces Pt(211) and Pt(533) which contain a (100)-step type and the Pt(221) and Pt(553) surface with a (111) step edge. We discuss these results in relation to ultra-high-vacuum temperature programmed desorption (TPD) data to elucidate the origin of the desorption features. Our results indicated that on surfaces with a (100)-step type, two distinct ranges of adsorption energy for the step and terrace are observed, which mirrors the TPD spectra for which we find a clear separation of the desorption peaks. For the (111) step type, the TPD spectra show much less separation of the step and terrace features, which we assign to the low individual adsorption energies for H atoms on this step edge. From our results we obtain a much clearer understanding of the surface-hydrogen bonding at high coverages and the origin of the different TPD features present for the two step types studied.We gratefully acknowledge financial support from the Netherlands Organization for Scientific Research (NWO) as a TOP grant awarded to LBFJ and MTMK. This work was sponsored also by the NWO Exacte Wetenschappen, EW (NWO Physical Sciences Division) for the use of supercomputer facilities, with financial support from the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organisation for Scientific Research, NWO). Furthermore, we would like to thank the Nordic High Performance Computing Center (NHPC) and the New Zealand eScience Infrastructure (NeSi), funded jointly by NeSI’s collaborator institutions and through the Ministry of Business, Innovation and Employment’s research infrastructure programme. JAGT acknowledges the support of the U.S. Department of Energy, Chemical Sciences, Geosciences, and Biosciences (CSGB) Division of the Office of Basic Energy Sciences, via Grant DE-AC02-76SF00515 to the SUNCAT Center for Interface Science and Catalysis.Peer Reviewe

Dual-action effect of gallium and silver providing osseointegration and antibacterial properties to calcium titanate coatings on porous titanium implants

Previously, functional coatings on 3D-printed titanium implants were developed to improve their biointegration by separately incorporating Ga and Ag on the biomaterial surface. Now, a thermochemical treatment modification is proposed to study the effect of their simultaneous incorporation. Different concentrations of AgNO3 and Ga(NO3)3 are evaluated, and the obtained surfaces are completely characterized. Ion release, cytotoxicity, and bioactivity studies complement the characterization. The provided antibacterial effect of the surfaces is analyzed, and cell response is assessed by the study of SaOS-2 cell adhesion, proliferation, and differentiation. The Ti surface doping is confirmed by the formation of Ga-containing Ca titanates and nanoparticles of metallic Ag within the titanate coating. The surfaces generated with all combinations of AgNO3 and Ga(NO3)3 concentrations show bioactivity. The bacterial assay confirms a strong bactericidal impact achieved by the effect of both Ga and Ag present on the surface, especially for Pseudomonas aeruginosa, one of the main pathogens involved in orthopedic implant failures. SaOS-2 cells adhere and proliferate on the Ga/Ag-doped Ti surfaces, and the presence of gallium favors cell differentiation. The dual effect of both metallic agents doping the titanium surface provides bioactivity while protecting the biomaterial from the most frequent pathogens in implantology.Peer ReviewedPostprint (published version

A crowdsourcing database for the copy-number variation of the Spanish population

Background: Despite being a very common type of genetic variation, the distribution of copy-number variations (CNVs) in the population is still poorly understood. The knowledge of the genetic variability, especially at the level of the local population, is a critical factor for distinguishing pathogenic from non-pathogenic variation in the discovery of new disease variants. Results: Here, we present the SPAnish Copy Number Alterations Collaborative Server (SPACNACS), which currently contains copy number variation profiles obtained from more than 400 genomes and exomes of unrelated Spanish individuals. By means of a collaborative crowdsourcing effort whole genome and whole exome sequencing data, produced by local genomic projects and for other purposes, is continuously collected. Once checked both, the Spanish ancestry and the lack of kinship with other individuals in the SPACNACS, the CNVs are inferred for these sequences and they are used to populate the database. A web interface allows querying the database with different filters that include ICD10 upper categories. This allows discarding samples from the disease under study and obtaining pseudo-control CNV profiles from the local population. We also show here additional studies on the local impact of CNVs in some phenotypes and on pharmacogenomic variants. SPACNACS can be accessed at: http://csvs.clinbioinfosspa.es/spacnacs/. Conclusion: SPACNACS facilitates disease gene discovery by providing detailed information of the local variability of the population and exemplifies how to reuse genomic data produced for other purposes to build a local reference database

Association of Candidate Gene Polymorphisms With Chronic Kidney Disease: Results of a Case-Control Analysis in the Nefrona Cohort

Chronic kidney disease (CKD) is a major risk factor for end-stage renal disease, cardiovascular disease and premature death. Despite classical clinical risk factors for CKD and some genetic risk factors have been identified, the residual risk observed in prediction models is still high. Therefore, new risk factors need to be identified in order to better predict the risk of CKD in the population. Here, we analyzed the genetic association of 79 SNPs of proteins associated with mineral metabolism disturbances with CKD in a cohort that includes 2, 445 CKD cases and 559 controls. Genotyping was performed with matrix assisted laser desorption ionizationtime of flight mass spectrometry. We used logistic regression models considering different genetic inheritance models to assess the association of the SNPs with the prevalence of CKD, adjusting for known risk factors. Eight SNPs (rs1126616, rs35068180, rs2238135, rs1800247, rs385564, rs4236, rs2248359, and rs1564858) were associated with CKD even after adjusting by sex, age and race. A model containing five of these SNPs (rs1126616, rs35068180, rs1800247, rs4236, and rs2248359), diabetes and hypertension showed better performance than models considering only clinical risk factors, significantly increasing the area under the curve of the model without polymorphisms. Furthermore, one of the SNPs (the rs2248359) showed an interaction with hypertension, being the risk genotype affecting only hypertensive patients. We conclude that 5 SNPs related to proteins implicated in mineral metabolism disturbances (Osteopontin, osteocalcin, matrix gla protein, matrix metalloprotease 3 and 24 hydroxylase) are associated to an increased risk of suffering CKD

Symmetry-Resolved CO Desorption and Oxidation Dynamics on O/Ru(0001) Probed at the C K-edge by Ultrafast X-Ray Spectroscopy

We report on carbon monoxide desorption and oxidation induced by 400 nm femtosecond laser excitation on the O/Ru(0001) surface probed by time-resolved x-ray absorption spectroscopy (TR-XAS) at the carbon K-edge. The experiments were performed under constant background pressures of CO (6 × 10−8 Torr) and O2 (3 × 10−8 Torr). Under these conditions, we detect two transient CO species with narrow 2π* peaks, suggesting little 2π* interaction with the surface. Based on polarization measurements, we find that these two species have opposing orientations: (1) CO favoring a more perpendicular orientation and (2) CO favoring a more parallel orientation with respect to the surface. We also directly detect gas-phase CO2 using a mass spectrometer and observe weak signatures of bent adsorbed CO2 at slightly higher x-ray energies than the 2π* region. These results are compared to previously reported TR-XAS results at the O K-edge, where the CO background pressure was three times lower (2 × 10−8 Torr) while maintaining the same O2 pressure. At the lower CO pressure, in the CO 2π* region, we observed adsorbed CO and a distribution of OC–O bond lengths close to the CO oxidation transition state, with little indication of gas-like CO. The shift toward “gas-like” CO species may be explained by the higher CO exposure, which blocks O adsorption, decreasing O coverage and increasing CO coverage. These effects decrease the CO desorption barrier through dipole–dipole interaction while simultaneously increasing the CO oxidation barrier

SARS-CoV-2 Infection in Multiple Sclerosis

To understand COVID-19 characteristics in people with multiple sclerosis (MS) and identify high-risk individuals due to their immunocompromised state resulting from the use of disease-modifying treatments. Retrospective and multicenter registry in patients with MS with suspected or confirmed COVID-19 diagnosis and available disease course (mild = ambulatory; severe = hospitalization; and critical = intensive care unit/death). Cases were analyzed for associations between MS characteristics and COVID-19 course and for identifying risk factors for a fatal outcome. Of the 326 patients analyzed, 120 were cases confirmed by real-time PCR, 34 by a serologic test, and 205 were suspected. Sixty-nine patients (21.3%) developed severe infection, 10 (3%) critical, and 7 (2.1%) died. Ambulatory patients were higher in relapsing MS forms, treated with injectables and oral first-line agents, whereas more severe cases were observed in patients on pulsed immunosuppressors and critical cases among patients with no therapy. Severe and critical infections were more likely to affect older males with comorbidities, with progressive MS forms, a longer disease course, and higher disability. Fifteen of 33 patients treated with rituximab were hospitalized. Four deceased patients have progressive MS, 5 were not receiving MS therapy, and 2 were treated (natalizumab and rituximab). Multivariate analysis showed age (OR 1.09, 95% CI, 1.04-1.17) as the only independent risk factor for a fatal outcome. This study has not demonstrated the presumed critical role of MS therapy in the course of COVID-19 but evidenced that people with MS with advanced age and disease, in progressive course, and those who are more disabled have a higher probability of severe and even fatal diseas