Seeing Beyond the Surface -- Structural Dynamics Identification through Multi-View Radiographic Imaging
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Rohe, Daniel Peter [Sandia National Laboratories (↗
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Seeing Beyond the Surface -- Structural Dynamics Identification through Multi-View Radiographic Imaging
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Rohe, Daniel Peter [Sandia National Laboratories (↗
Exploiting correlations in multi-coincidence Coulomb explosion patterns for differentiating molecular structures using machine learning
Coulomb explosion imaging (CEI) is a powerful technique for capturing the real-time motion of individual atoms during ultrafast photochemical reactions. CEI generates high-dimensional data with naturally embedded correlations that allow mapping the coordinated motion of nuclei in molecules. This enables reliable separation of competing reaction pathways and makes this approach uniquely suited for characterizing weak reaction channels. However, rich information contained in experimental CEI patterns remains largely underexploited due to challenges in visualizing correlations between multiple observables in multi-dimensional parameter space. Here we present a new approach to CEI of intermediate-sized polyatomic molecules, detecting up to eight ionic fragments in coincidence and leveraging machine-learning-based analysis to identify patterns and correlations in the resulting high-dimensional momentum-space data, enabling robust molecular structure identification and differentiation. Our approach provides high-dimensional background-free data encoding exceptionally rich structural information and establishes an automated, scalable framework for extracting insightful information from the data. As a demonstration, we apply this method to image and distinguish dichloroethylene isomers, showcasing its potential for broader applications in molecular imaging. Our results pave the way for channel-specific analysis of ultrafast structural dynamics in chemically relevant systems, particularly for disentangling mixed reaction pathways and detecting contributions from weak channels and minority species.
Chemical Physics (physics.chem-ph)↗
Structure Perception in 3D Point Clouds
Understanding human perception is critical to the design of effective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the literature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projections of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rotation, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under rotation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns perceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.
data analysis↗
Time-resolved atomic-resolution Brownian tomography of single nanocrystals reveals size-dependent dynamics
Atomic-resolution structure identification of nanocrystals by graphene liquid cell electron microscopy (GLC-EM) has revealed that small, solubilized platinum nanocrystals consist of an ordered crystalline core surrounded by mobile surface atoms, which dissociate during oxidative etching, resulting in distinct temporal structural states. Requirements imposed by the 3D reconstruction algorithm limit the number of structural states that can be resolved. We introduce a regularized 3D reconstruction algorithm that exploits the redundancy inherent in the experimental data, allowing us to improve the time resolution. Our developments provide a comprehensive molecular picture at unprecedented spatial and temporal resolution of the nonlinear, linear, and fluctuating dynamic phenomena that single nanocrystals undergo during the GLC-EM experiment. We determined atomic structures of 66 temporal structural states, extracted from 15 time trajectories of individual nanocrystals. Large (478 to 698 atoms) and small (<300 atoms) nanocrystals show etching that preserves a stable core, whereas mid-sized (351 to 571 atoms) nanocrystals present dynamics that change the coordination of the core.
Meana-Pañeda, Rubén↗
Structure Perception in 3D Point Clouds: Preprint
Understanding human perception is critical to the design of ef- fective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the liter- ature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projec- tions of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rota- tion, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under ro- tation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns per- ceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.
data analysis↗
Impact of Cosmic Filaments on Galaxy Morphological Evolution and Predictions of Early Cosmic Web Structure for Roman
We leverage the IllustrisTNG cosmological simulations to test how the large-scale cosmic web shapes galaxy morphology and to forecast the early cosmic web structure that the Nancy Grace Roman Space Telescope will reveal. In the hydrodynamic TNG50 and N-body TNG50-Dark runs, we reconstruct the cosmic web at redshifts z = 0, 0.5, 1, 2, 3, and 4 with the Monte Carlo Physarum Machine density estimator and the DisPerSE structure identification framework. We confirm that dark matter halos start out predominantly prolate (elongated), and their shapes are aligned with their nearest filaments; prolate galaxies retain strong shape alignment with their outer halos to later times. At z ≥ 1, the fraction of prolate (spheroidal) halos increases (decreases) toward lower stellar mass, higher redshift, and lower filament density. At z < 1, more spheroidal (oblate) stellar structures preferentially reside in higher-density (lower-density) filaments. We also find that higher-density filaments favor extended rotationally supported disks, whereas lower-density filaments more often host smaller dispersion-supported systems. Then, generating mock galaxy samples from TNG100 and TNG50, we predict the early cosmic web accessible to Roman. We find that the spectroscopic emission-line depth planned for the High-Latitude Wide-Area Survey (HLWAS) yields a highly incomplete galaxy sample that does not accurately trace the z = 1 cosmic web. A survey ≥2.5× deeper over a few square degrees would enable a proper reconstruction and reveal qualitatively correct filament–galaxy morphology relationships. Nevertheless, the planned HLWAS Deep field should still identify most galaxy overdensities; targeted deeper spectroscopy of these regions would efficiently and adequately map the early filamentary structure.
Hasan, Farhanul [Space Telescope Science Institute↗
Direct Observation of Elusive (DTBM‐SEGPHOS)CuH Monomer Enables Mechanistic Insights Into Hydrocupration, Aggregation, and Dynamics of Alkene Functionalization Catalysis
The bulky diphosphine DTBM-SEGPHOS is widely employed in CuH-catalyzed transformations as it provides remarkably active catalyst systems. The transient (DTBM-SEGPHOS)CuH monomer (LCuH) is the often-invoked active species. However, its instability has prevented spectroscopic characterization and mechanistic elucidation, hindering mechanistic understanding. We report low-temperature NMR spectroscopic characterization of LCuH, enabling quantitative kinetic analysis of the stoichiometric hydrocupration and catalytic hydroboration of cyclopentene, as well as the structural identification of two CuH clusters. LCuH inserts cyclopentene at −43°C, reaffirming its high reactivity toward olefins. LCuH deactivates to form L 2 Cu 3 H 3 and L 2 Cu 4 H 4 clusters, in which LCuH dimerization initiates aggregation. Kinetic analysis of reactions of unactivated alkenes indicates that competing on-cycle alkene hydrocupration and LCuH dimerization impact performance, as catalyst deactivation and turnover occur on comparable timescales. Structure–activity analysis using atomistic simulations shows that the steric profile of DTBM-SEGPHOS increases the CuH dimerization barrier by ∼7.7 kcal mol−1 compared to that of SEGPHOS, rationalizing the unique ability of DTBM-SEGPHOS to stabilize a reactive monomer for hydrocupration of broader alkene substrates. These findings illustrate the fundamental design principle that steric control of aggregation governs CuH catalyst performance, explaining both the exceptional activity of (DTBM-SEGPHOS)CuH and the limitations imposed by competing deactivation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Optical Microscopy-Guided Laser Ablation Electrospray Ionization Ion Mobility Mass Spectrometry: Ambient Single Cell Metabolomics with Increased Confidence in Molecular Identification
Single cell analysis is a field of increasing interest as new tools are continually being developed to understand intercellular differences within large cell populations. Laser-ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging technique for single cell metabolomics. Over the years, it has been validated that this ionization technique is advantageous for probing the molecular content of individual cells in situ. Here, we report the integration of a microscope into the optical train of the LAESI source to allow for visually informed ambient in situ single cell analysis. Additionally, we have coupled this ‘LAESI microscope’ to a drift-tube ion mobility mass spectrometer to enable separation of isobaric species and allow for the determination of ion collision cross sections in conjunction with accurate mass measurements. This combined information helps provide higher confidence for structural assignment of molecules ablated from single cells. Here, we show that this system enables the analysis of the metabolite content of Allium cepa epidermal cells with high confidence structural identification together with their spatial locations within a tissue.
59 BASIC BIOLOGICAL SCIENCES↗
Machine learning approaches for crystallographic classification from synthetic 2D X-ray diffraction data
Crystallographic structure identification is crucial for understanding material properties; however, current methodologies often depend on labor-intensive and time-consuming analyses of 2D X-ray diffraction (XRD) patterns. To address these limitations, this study employs synthetic 2D XRD patterns combined with deep learning (DL) techniques to enable automated and high-throughput classification of the seven crystal systems and 230 space groups. We introduce the novel Auto Diffraction Pipeline, designed to generate synthetic 2D XRD spot patterns from crystallographic information files under diverse conditions, including varying zone axes, atomic substitution, atomic depletion and mechanical loading. These conditions enhance the realism of synthetic data, mitigating the scarcity of experimental datasets and enabling the creation of large representative training sets. Convolutional neural networks were trained and validated on these synthetic datasets to classify crystallographic structures across multiple scenarios. Our results demonstrate that integrating synthetic 2D XRD patterns with DL facilitates rapid, accurate and automated crystallographic classification, promoting the wider adoption of data-driven approaches in materials science.
Shahnazari, Ayoub [Univ. of Rochester, NY (United ↗
RNA-Puzzles Round V: blind predictions of 23 RNA structures
RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA three-dimensional structure prediction. With agreement from structural biologists, RNA structures are predicted by modeling groups before publication of the experimental structures. We report a large-scale set of predictions by 18 groups for 23 RNA-Puzzles: 4 RNA elements, 2 Aptamers, 4 Viral elements, 5 Ribozymes and 8 Riboswitches. We describe automatic assessment protocols for comparisons between prediction and experiment. Our analyses reveal some critical steps to be overcome to achieve good accuracy in modeling RNA structures: identification of helix-forming pairs and of non-Watson–Crick modules, correct coaxial stacking between helices and avoidance of entanglements. Three of the top four modeling groups in this round also ranked among the top four in the CASP15 contest.
59 BASIC BIOLOGICAL SCIENCES↗
New Constraints on the Melting Temperature and Phase Stability of Shocked Iron up to 270 GPa Probed by Ultrafast X-Ray Absorption Spectroscopy
Studying the properties and phase diagram of iron at high-pressure and high-temperature conditions has relevant implications for Earth’s inner structure and dynamics and the temperature of the inner core boundary (ICB) at 330 GPa. Also, a hexagonal-closed packed to body-centered cubic (bcc) phase transition has been predicted by many theoretical works but observed only in a few experiments. The recent coupling of high-power laser with advanced x-ray sources from synchrotrons allows for novel approaches to address these issues. Here, we present a study on shock compressed iron up to 270 GPa and 5800 K probed by single-pulse (100 ps FWHM) x-ray absorption spectroscopy (XAS). Based on the analysis of the XAS spectra, we provide structural identification and bulk temperature measurements along the Hugoniot up to the melting. These results rule out the predicted transition to a high-temperature bcc phase and allow one to discriminate among existing equations of state models and melting curves. In particular, we report the first bulk temperature measurement in shock compressed iron on the melting plateau at 240(20) GPa and 5345(600) K. The melting curve resulting from our work extrapolates to a temperature of 6202(514) K at 330 GPa and represents a refined upper bound for the ICB temperature. Published by the American Physical Society 2024
Balugani, S.↗
2D Polyhedral Template Matching for Atomic Resolution Microscopy
SAND2024-13879O The 2D Polyhedral Template Matching for Atomic Resolution Microscopy is a suite of functions for analyzing atomic resolution electron microscopy images using the 2D polyhedral template matching (2D-PTM) method. This software analyzes atomic resolution microscopy data from electron microscopic imaging or scanning probe microscopies. The primary application is for identifying different crystal phases, crystal orientations, and defect structures obtained in such atomic resolution images. Written in MATLAB and starting from an atomic resolution image, the code identifies the positions of atomic intensity peaks. It then matches predefined structural templates to the local atomic environments. Outputs include the local structural identification, the template scaling factor and rotation angle, root-mean-squared deviation (RMSD), and centrosymmetry parameter.
Medlin, Douglas↗
What Is the Limit of Quantification for the Minor Phase in Time-of-Flight Neutron Diffraction? A Case Study on Fe and Ni Powder Mixtures at VULCAN
A phase present in small quantities within materials may not simply serve as a secondary component; it can play a crucial role in determining the integrity, properties, and performance of the material. These minor but important phases usually draw attention in material design and processing for fundamental understanding as well as material quality control. Accurately quantifying a minor phase amid a majority phase, especially at extremely low fractions, remains a challenging task. Time-of-flight neutron diffraction, coupled with advanced pattern analysis techniques like Rietveld refinement, is a powerful tool for crystal structure identification and phase quantification. The deep penetrating capability of neutrons enables the detection and quantification of trace phases within materials. In this study, the quantification limits of time-of-flight neutron diffraction were explored using the VULCAN diffractometer at the Spallation Neutron Source, using Fe–Ni powder mixtures as a sample system. By comparing the refinement results to the known weighed values, it was determined that the reliable quantification of a minor Ni phase is achievable down to about 0.1 wt% while a Ni fraction as low as 0.02 wt% is difficult to trace. Effective control of the refinement parameters, especially the profile function parameters, are found to significantly influence the convergence of fittings and the accuracy of phase quantification.
Rietveld refinement↗
Identification of and Structural Insights into Hit Compounds Targeting N -Myristoyltransferase for Cryptosporidium Drug Development
Each year, approximately 50,000 children under 5 die as a result of diarrhea caused by Cryptosporidium parvum, a protozoan parasite. There are currently no effective drugs or vaccines available to cure or prevent Cryptosporidium infection, and there are limited tools for identifying and validating targets for drug or vaccine development. We previously reported a high throughput screening (HTS) of a large compound library against Plasmodium N-myristoyltransferase (NMT), a validated drug target in multiple protozoan parasite species. To identify molecules that could be effective against Cryptosporidium, we counter-screened hits from the Plasmodium NMT HTS against Cryptosporidium NMT. We identified two potential hit compounds and validated them against CpNMT to determine if NMT might be an attractive drug target also for Cryptosporidium. We tested the compounds against Cryptosporidium using both cell-based and NMT enzymatic assays. We then determined the crystal structure of CpNMT bound to Myristoyl-Coenzyme A (MyrCoA) and structures of ternary complexes with MyrCoA and the hit compounds to identify the ligand binding modes. The binding site architectures display different conformational states in the presence of the two inhibitors and provide a basis for rational design of selective inhibitors.
60 APPLIED LIFE SCIENCES↗
Identification and structure-based drug design of cell-active inhibitors of interleukin 17A at a nov
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Goedken, Eric R.↗
Identification, characterization, and structure of a tRNA splicing enzyme RNA 5′-OH kinase from the pathogenic fungi Mucorales
Fungal Trl1 is an essential tRNA splicing enzyme composed of C-terminal cyclic phosphodiesterase and central polynucleotide kinase end-healing domains that convert the 2′,3′-cyclic-PO 4 and 5′-OH ends of tRNA exons into the 3′-OH,2′-PO 4 and 5′-PO 4 termini required for sealing by an N-terminal ATP-dependent ligase domain. Trifunctional Trl1 enzymes are present in most human fungal pathogens and are untapped targets for antifungal drug discovery. Mucorales species, deemed high-priority human pathogens by WHO, elaborate a noncanonical tRNA splicing apparatus in which a stand-alone monofunctional RNA ligase enzyme joins 3′-OH,2′-PO 4 and 5′-PO 4 termini. Here we identify a stand-aloneMucor circinelloidespolynucleotide kinase (MciKIN) and affirm its biological activity in tRNA splicing by genetic complementation in yeast. Recombinant MciKIN catalyzes magnesium-dependent phosphorylation of 5′-OH RNA and DNA ends in vitro. MciKIN displays a strong preference for GTP as the phosphate donor in the kinase reaction, a trait shared with the stand-alone RNA kinase homologs from Mucorales speciesRhizopus azygosporus(RazKIN) andLichtheimia corymbifera(LcoKIN) and with the kinase domains of fungal Trl1 enzymes. We report a 1.65 Å crystal structure of RazKIN in complex with GDP•Mg 2+ that illuminates the basis for guanosine nucleotide specificity.
Biochemistry & Molecular Biology↗