A5028559746- Enzyme Structure and Function
- Advanced X-ray Imaging Techniques
- Photosynthetic Processes and Mechanisms
- Advanced Electron Microscopy Techniques and Applications
- Protein Structure and Dynamics
- Spectroscopy and Quantum Chemical Studies
- Scientific Computing and Data Management
- Astronomy and Astrophysical Research
- X-ray Diffraction in Crystallography
- X-ray Spectroscopy and Fluorescence Analysis
- Medical Imaging Techniques and Applications
- Machine Learning in Materials Science
- Nuclear Physics and Applications
- Quantum, superfluid, helium dynamics
- Spectroscopy Techniques in Biomedical and Chemical Research
- Cell Image Analysis Techniques
- Radiomics and Machine Learning in Medical Imaging
- Atomic and Subatomic Physics Research
- Mass Spectrometry Techniques and Applications
- Algal biology and biofuel production
- Spectroscopy and Chemometric Analyses
- Genetics, Bioinformatics, and Biomedical Research
- Gaussian Processes and Bayesian Inference
- Ion-surface interactions and analysis
- Advanced Chemical Physics Studies
Lawrence Berkeley National Laboratory
2014-2024
Research Applications (United States)
2018-2024
Berkeley College
2015
United States Department of Energy
2010
Institut Langevin
2010
Arkema (France)
2010
Brookhaven National Laboratory
2004
European Molecular Biology Laboratory
2003
European Molecular Biology Laboratory
2003
Intense femtosecond x-ray pulses produced at the Linac Coherent Light Source (LCLS) were used for simultaneous diffraction (XRD) and emission spectroscopy (XES) of microcrystals photosystem II (PS II) room temperature. This method probes overall protein structure electronic Mn4CaO5 cluster in oxygen-evolving complex PS II. XRD data are presented from both dark state (S1) first illuminated (S2) Our XRD-XES study shows that crystals intact during our measurements LCLS, not only with respect to...
Helium nanodroplets are considered ideal model systems to explore quantum hydrodynamics in self-contained, isolated superfluids. However, exploring the dynamic properties of individual droplets is experimentally challenging. In this work, we used single-shot femtosecond x-ray coherent diffractive imaging investigate rotation single, superfluid helium-4 containing ~10(8) 10(11) atoms. The formation vortex lattices inside confirmed by observing characteristic Bragg patterns from xenon clusters...
An electrospun liquid microjet has been developed that delivers protein microcrystal suspensions at flow rates of 0.14–3.1 µl min −1 to perform serial femtosecond crystallography (SFX) studies with X-ray lasers. Thermolysin microcrystals flowed 0.17 and diffracted beyond 4 Å resolution, producing 14 000 indexable diffraction patterns, or four per second, from 140 µg protein. Nanoflow electrospinning extends SFX biological samples necessitate minimal sample consumption.
The photoprotective processes of photosynthetic organisms involve the dissipation excess absorbed light energy as heat. Photoprotection in cyanobacteria is mechanistically distinct from that plants; it involves orange carotenoid protein (OCP), a water-soluble containing single carotenoid. OCP new member family blue light-photoactive proteins; blue-green triggers OCP-mediated response. Here we report structural and functional characterization wild type two mutant forms OCP, model organism...
Most of the dioxygen on earth is generated by oxidation water photosystem II (PS II) using light from sun. This light-driven, four-photon reaction catalyzed Mn 4 CaO 5 cluster located at lumenal side PS II. Various X-ray studies have been carried out cryogenic temperatures to understand intermediate steps involved in mechanism. However, necessity for collecting data room temperature, especially studying transient during O–O bond formation, requires development new methodologies. In this...
The ultrabright femtosecond X-ray pulses provided by free-electron lasers open capabilities for studying the structure and dynamics of a wide variety systems beyond what is possible with synchrotron sources. Recently, this “probe-before-destroy” approach has been demonstrated atomic determination serial diffraction microcrystals. There question whether similar can be extended to probe local electronic spectroscopy. To address this, we have carried out emission spectroscopy (XES) at Linac...
New procedures are outlined that enable ARP/wARP to automatically build protein models with diffraction data extending about 2.5 A. An overview of ongoing research is given and possible future advances discussed.
DLSIA (Deep Learning for Scientific Image Analysis) is a Python-based machine learning library that empowers scientists and researchers across diverse scientific domains with range of customizable convolutional neural network (CNN) architectures wide variety tasks in image analysis to be used downstream data processing. features easy-to-use architectures, such as autoencoders, tunable U-Nets parameter-lean mixed-scale dense networks (MSDNets). Additionally, this article introduces sparse...
A method of simultaneously probing the electronic structure multiple metal centers using wavelength-dispersive X-ray emission spectroscopy was developed.
X-ray diffraction patterns from still crystals are inherently difficult to process because the crystal orientation is not uniquely determined by measuring Bragg spot positions. Only one of three rotational degrees freedom directly coupled positions; other two rotations move spots in and out reflecting condition but do change direction diffracted rays. This hinders ability recover accurate structure factors experiments that dependent on single-shot exposures, such as femtosecond...
Significance Fluctuation X-ray scattering is a biophysical structural characterization technique that overcomes low data-to-parameter ratios encountered in traditional methods used for studying noncrystalline samples. By collecting series of ultrashort exposures on an ensemble particles at free-electron laser, information-dense experimental data can be extracted ultimately result structures with greater level detail than obtained using methods. In this article we demonstrate the practical...
Hyperspectral imaging provides a powerful tool for analyzing above-ground plant characteristics in fabricated ecosystems, offering rich spectral information across diverse wavelengths. This study presents an efficient workflow hyperspectral data segmentation and subsequent analytics, minimizing the need user annotation through use of ensembles sparse mixed scale convolution neural networks. The process leverages diversity to achieve high accuracy with minimal labeled data, reducing...
This study introduces a novel labeling pipeline to accelerate the process of scientific data sets by using artificial intelligence (AI)-guided tagging techniques. includes set interconnected web-based graphical user interfaces (GUIs), where Data Clinic and MLCoach enable preparation machine learning (ML) models for reduction classification, respectively, while Label Maker is used label assignment. Throughout this pipeline, can be accessed through direct connection file system or Tiled access...
In scientific imaging, deep learning has become a pivotal tool for image analytics. However, handling large volumetric datasets, which often exceed the memory capacity of standard GPUs, require special attention when subjected to efforts. This paper introduces qlty, toolkit designed address these challenges through tensor management techniques. qlty offers robust methods subsampling, cleaning, and stitching large-scale spatial data, enabling effective training inference even in...
A detailed analysis of radiation-damage-induced structural and intensity changes is presented on the model protein thaumatin. Changes in reflection intensities induced by irradiation display a parabolic character. The most pronounced observed were disulfide-bond breakage associated main-chain side-chain movements as well decarboxylation aspartate glutamate residues. sulfur atoms successfully used to obtain high-quality phase estimates via an RIP procedure. Results obtained with ACORN suggest...
X-ray scattering images collected on timescales shorter than rotation diffusion times using a (partially) coherent beam result in significant increase information content the scattered data. These measurements, named fluctuation (FXS), are typically performed an free-electron laser (XFEL) and can provide fundamental insights into structure of biological molecules, engineered nanoparticles or energy-related mesoscopic materials beyond what be obtained with standard techniques. In order to...
The implementation is proposed of image inpainting techniques for the reconstruction gaps in experimental X-ray scattering data. methods use deep learning neural network architectures, such as convolutional autoencoders, tunable U-Nets, partial convolution networks and mixed-scale dense networks, to reconstruct missing information images. In particular, recovered pixel intensities are evaluated against their corresponding ground-truth values using mean absolute error correlation coefficient...
Abstract We propose the combination of k-means clustering with Gaussian Process (GP) regression in analysis and exploration 4D angle-resolved photoemission spectroscopy (ARPES) data. Using cluster labels as driving metric on which GP is trained, this method allows us to reconstruct experimental phase diagram from low 12% original dataset size. In addition diagram, able spectra energy-momentum space minimal set data points. These findings suggest that methodology can be used improve...