Importance of electronic self-consistency in the TDDFT based treatment of nonadiabatic molecular dynamics

A mixed quantum-classical approach to simulate the coupled dynamics of electrons and nuclei in nanoscale molecular systems is presented. The method relies on a second order expansion of the Lagrangian in time-dependent density functional theory (TDDFT) around a suitable reference density. We show that the inclusion of the second order term renders the method a self-consistent scheme and improves the calculated optical spectra of molecules by a proper treatment of the coupled response. In the application to ion-fullerene collisions, the inclusion of self-consistency is found to be crucial for a correct description of the charge transfer between projectile and target. For a model of the photoreceptor in retinal proteins, nonadiabatic molecular dynamics simulations are performed and reveal problems of TDDFT in the prediction of intra-molecular charge transfer excitations.Comment: 9 pages, 8 figures. Minor changes in content wrt older versio

Single molecule quantitation and sequencing of rare translocations using microfluidic nested digital PCR

Cancers are heterogeneous and genetically unstable. New methods are needed that provide the sensitivity and specificity to query single cells at the genetic loci that drive cancer progression, thereby enabling researchers to study the progression of individual tumors. Here, we report the development and application of a bead-based hemi-nested microfluidic droplet digital PCR (dPCR) technology to achieve ‘quantitative’ measurement and single-molecule sequencing of somatically acquired carcinogenic translocations at extremely low levels (<10−6) in healthy subjects. We use this technique in our healthy study population to determine the overall concentration of the t(14;18) translocation, which is strongly associated with follicular lymphoma. The nested dPCR approach improves the detection limit to 1 × 10−7 or lower while maintaining the analysis efficiency and specificity. Further, the bead-based dPCR enabled us to isolate and quantify the relative amounts of the various clonal forms of t(14;18) translocation in these subjects, and the single-molecule sensitivity and resolution of dPCR led to the discovery of new clonal forms of t(14;18) that were otherwise masked by the conventional quantitative PCR measurements. In this manner, we created a quantitative map for this carcinogenic mutation in this healthy population and identified the positions on chromosomes 14 and 18 where the vast majority of these t(14;18) events occur.Trans-National Institutes of Health Genes, Environment and Health Initiative, Biological Response Indicators of Environmental Systems Center Grant [U54 ES016115-01 to M.T.S. and R.A.M.] and National Institute of Environmental Health Sciences Superfund Basic Research Program Grant [P42 ES004705 to M.T.S.]; Canary Foundation and ACS Postdoctoral Fellowship Award in Early Detection [116373-PFTED-08-251-01-SIED to J.S.] from the American Cancer Society; New faculty start-up funds from the University of Kansas (in part to Y.Z.). National Science Foundation Graduate Research Fellowship (to R.N.). Funding for open access charge: National Institutes of Health [U54 ES016115-01]

Combinatorial inkjet printing for compositional tuning of metal halide perovskite thin films

To accelerate the materials discovery and development process for a sustainable technology advancement it is imperative to explore and develop combined high throughput material synthesis and analysis workflows. In this work, we investigate a method of combinatorial inkjet printing to tune the composition of the inorganic cesium lead mixed halide perovskite solid solution, CsPb BrxI1 amp; 8722;x 3. The compositional variation is achieved by simultaneous printing of different precursor inks with multiple printheads and controlled by varying the number of droplets printed by each printhead throughout the sample. The droplet placement is optimised through an algorithm that allows maximum mixing of the combined inks. The local compositional homogeneity of thin film samples was investigated as a function of the printing resolution by micrometer resolution X ray fluorescence and synchrotron based grazing incidence wide angle X ray scattering. We show that a combinatorial library of ten compositions between CsPbI3 and CsPbBr2I, printed using the developed algorithm, is locally homogeneous for the optimised printing parameters. An implementation of the algorithm in the high level programming language Python is provided for easy use in other system

Infrared spectroscopy of phytochrome and model pigments

Fourier-transform infrared difference spectra between the red-absorbing and far-red-absorbing forms of oat phytochrome have been measured in H2O and 2H2O. The difference spectra are compared with infrared spectra of model compounds, i.e. the (5Z,10Z,15Z)- and (5Z,10Z,15E)-isomers of 2,3,7,8,12,13,17,18-octaethyl-bilindion (Et8-bilindion), 2,3-dihydro-2,3,7,8,12,13,17,18-octaethyl-bilindion (H2Et8-bilindion), and protonated H2Et8-bilindion in various solvents. The spectra of the model compounds show that only for the protonated forms can clear differences between the two isomers be detected. Since considerable differences are present between the spectra of Et8-bilindion and H2Et8-bilindion, it is concluded that only the latter compound can serve as a model system of phytochrome. The 2H2O effect on the difference spectrum of phytochrome supports the view that the chromophore in red-absorbing phytochrome is protonated and suggests, in addition, that it is also protonated in far-red-absorbing phytochrome. The spectra show that protonated carboxyl groups are influenced. The small amplitudes in the difference spectra exclude major changes of protein secondary structure

An in-situ cell for characterization of solids by soft X-rayabsorption

An in-situ cell using ''lab-on-a-chip'' technologies has been designed and tested for characterization of catalysts and environmental materials using soft X-ray absorption spectroscopy and spectromicroscopy at photon energies above 250 eV. The sample compartment is 1.0 mm in diameter with a gas path length of 0.8 mm to minimize X-ray absorption in the gas phase. The sample compartment can be heated to 533 K by an Al resistive heater and gas flows up to 5.0 cm{sup 3} min{sup -1} can be supplied to the sample compartment through microchannels. The performance of the cell was tested by acquiring Cu L{sub 3}-edge XANES data during the reduction and oxidation of a silica-supported Cu catalyst using the beam line 11.0.2 Scanning Transmission X-ray Microscope (STXM) at the Advanced Light Source of LBNL. Two-dimensional images of individual catalyst particles were recorded at photon energies between 926 eV and 937 eV, the energy range in which the Cu(II) and Cu(I) L{sub 3} absorption edges are observed. Oxidation state specific images of the catalyst clearly show the disappearance of Cu(II) species during the exposure of the oxidized sample to 4% CO in He while increasing the temperature from 308 K to 473 K. Reoxidation restores the intensity of the image associated with Cu(II). L-edge XANES spectra obtained from stacks of STXM images show that with increasing temperature the Cu(II) peak intensity decreases as the Cu(I) peak intensity increases

An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences

An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42, 400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences. © 2021, The Author(s)

An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences