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At least 703 records · Page 39

Resolving length-scale-dependent transient disorder through an ultrafast phase transition

Abstract Material functionality can be strongly determined by structure extending only over nanoscale distances. The pair distribution function presents an opportunity for structural studies beyond idealized crystal models and to investigate structure over varying length scales. Applying this method with ultrafast time resolution has the potential to similarly disrupt the study of structural dynamics and phase transitions. Here we demonstrate such a measurement of CuIr 2 S 4 optically pumped from its low-temperature Ir-dimerized phase. Dimers are optically suppressed without spatial correlation, generating a structure whose level of disorder strongly depends on the length scale. The redevelopment of structural ordering over tens of picoseconds is directly tracked over both space and time as a transient state is approached. This measurement demonstrates the crucial role of local structure and disorder in non-equilibrium processes as well as the feasibility of accessing this information with state-of-the-art XFEL facilities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Machine learning sheds light on microbial dark proteins

In this article, metagenomics projects have revealed more than 8 billion non-redundant microbial protein sequences from across the Earth’s biosphere. Of these, 1.17 billion proteins do not have recognizable homologues in any of the more than 100,000 reference genomes available1. Understanding the function of these microbial proteins is a daunting task. Fortunately, machine learning has recently achieved unprecedented accuracy in modelling complex biological data and making predictions. At the forefront of these advancements are machine learning-based approaches that can confidently predict atomic-level protein structures for many (but not all) amino acid sequences.

59 BASIC BIOLOGICAL SCIENCES↗

Structural basis for dimerization quality control

Most quality control pathways target misfolded proteins to prevent toxic aggregation and neurodegeneration 1 . Dimerization quality control further improves proteostasis by eliminating complexes of aberrant composition 2 , but how it detects incorrect subunits remains unknown. Here we provide structural insight into target selection by SCF-FBXL17, a dimerization-quality-control E3 ligase that ubiquitylates and helps to degrade inactive heterodimers of BTB proteins while sparing functional homodimers. We find that SCF-FBXL17 disrupts aberrant BTB dimers that fail to stabilize an intermolecular β-sheet around a highly divergent β-strand of the BTB domain. Furthermore, complex dissociation allows SCF-FBXL17 to wrap around a single BTB domain, resulting in robust ubiquitylation. SCF-FBXL17 therefore probes both shape and complementarity of BTB domains, a mechanism that is well suited to establish quality control of complex composition for recurrent interaction modules.

59 BASIC BIOLOGICAL SCIENCES↗

Improved AlphaFold modeling with implicit experimental information

Machine-learning prediction algorithms such as AlphaFold and RoseTTAFold can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy. We hypothesized that by implicitly including new experimental information such as a density map, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt on the basis of experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We show that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for interpretation of crystallographic and electron cryo-microscopy maps.

59 BASIC BIOLOGICAL SCIENCES↗

A large expert-curated cryo-EM image dataset for machine learning protein particle picking

Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structures of biological macromolecular complexes. Picking single-protein particles from cryo-EM micrographs is a crucial step in reconstructing protein structures. However, the widely used template-based particle picking process is labor-intensive and time-consuming. Though machine learning and artificial intelligence (AI) based particle picking can potentially automate the process, its development is hindered by lack of large, high-quality labelled training data. To address this bottleneck, we present CryoPPP, a large, diverse, expert-curated cryo-EM image dataset for protein particle picking and analysis. It consists of labelled cryo-EM micrographs (images) of 34 representative protein datasets selected from the Electron Microscopy Public Image Archive (EMPIAR). The dataset is 2.6 terabytes and includes 9,893 high-resolution micrographs with labelled protein particle coordinates. The labelling process was rigorously validated through 2D particle class validation and 3D density map validation with the gold standard. The dataset is expected to greatly facilitate the development of both AI and classical methods for automated cryo-EM protein particle picking.

42 ENGINEERING↗

Site specific N- and O-glycosylation mapping of the spike proteins of SARS-CoV-2 variants of concern

Abstract The glycosylation on the spike (S) protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, modulates the viral infection by altering conformational dynamics, receptor interaction and host immune responses. Several variants of concern (VOCs) of SARS-CoV-2 have evolved during the pandemic, and crucial mutations on the S protein of the virus have led to increased transmissibility and immune escape. In this study, we compare the site-specific glycosylation and overall glycomic profiles of the wild type Wuhan-Hu-1 strain (WT) S protein and five VOCs of SARS-CoV-2: Alpha, Beta, Gamma, Delta and Omicron. Interestingly, both N- and O-glycosylation sites on the S protein are highly conserved among the spike mutant variants, particularly at the sites on the receptor-binding domain (RBD). The conservation of glycosylation sites is noteworthy, as over 2 million SARS-CoV-2 S protein sequences have been reported with various amino acid mutations. Our detailed profiling of the glycosylation at each of the individual sites of the S protein across the variants revealed intriguing possible association of glycosylation pattern on the variants and their previously reported infectivity. While the sites are conserved, we observed changes in the N- and O-glycosylation profile across the variants. The newly emerged variants, which showed higher resistance to neutralizing antibodies and vaccines, displayed a decrease in the overall abundance of complex-type glycans with both fucosylation and sialylation and an increase in the oligomannose-type glycans across the sites. Among the variants, the glycosylation sites with significant changes in glycan profile were observed at both the N -terminal domain and RBD of S protein, with Omicron showing the highest deviation. The increase in oligomannose-type happens sequentially from Alpha through Delta. Interestingly, Omicron does not contain more oligomannose-type glycans compared to Delta but does contain more compared to the WT and other VOCs. O-glycosylation at the RBD showed lower occupancy in the VOCs in comparison to the WT. Our study on the sites and pattern of glycosylation on the SARS-CoV-2 S proteins across the VOCs may help to understand how the virus evolved to trick the host immune system. Our study also highlights how the SARS-CoV-2 virus has conserved both N - and O - glycosylation sites on the S protein of the most successful variants even after undergoing extensive mutations, suggesting a correlation between infectivity/ transmissibility and glycosylation.

60 APPLIED LIFE SCIENCES↗

Impact of gas background on XFEL single-particle imaging

Abstract Single-particle imaging (SPI) using X-ray free-electron Lasers (XFELs) offers the potential to determine protein structures at high spatial and temporal resolutions without the need for crystallization or vitrification. However, the technique faces challenges due to weak diffraction signals from single proteins and significant background scattering from gases used for sample delivery. A recent observation of a diffraction pattern from an isolated GroEL protein complex Ekeberg T et al. (Light Sci Appl 13:15, 2024.https://doi.org/10.1038/274s41377-023-01352-7) had similar numbers of signal and background photons. Ongoing efforts aim to reduce the background created by sample delivery, with one approach replacing most of the used gas with helium Yenupuri T et al. (Sci Rep 14:4401, 2024.https://doi.org/10.1038/s41598-024-54605-9). In this study, we investigate the effects of a reduced background on the resolution limits for SPI of isolated proteins under different experiment conditions. As a test case, we used GroEL, and we used experimentally derived parameters for our simulations. We observe that background significantly impacts the achievable resolution, particularly when the signal strength is comparable to the background. This is best exemplified at 6.0 keV, where a background reduction by a factor of 10 leads to a resolution improvement from 1.9 to 1.2 nm, for a dataset of$$10^4$$patterns.

Science & Technology - Other Topics↗

Structural basis of inhibition of a transporter from Staphylococcus aureus, NorC, through a single-domain camelid antibody

Transporters play vital roles in acquiring antimicrobial resistance among pathogenic bacteria. In this study, we report the X-ray structure of NorC, a 14-transmembrane major facilitator superfamily member that is implicated in fluoroquinolone resistance in drug-resistant Staphylococcus aureus strains, at a resolution of 3.6 Å. The NorC structure was determined in complex with a single-domain camelid antibody that interacts at the extracellular face of the transporter and stabilizes it in an outward-open conformation. The complementarity determining regions of the antibody enter and block solvent access to the interior of the vestibule, thereby inhibiting alternating-access. NorC specifically interacts with an organic cation, tetraphenylphosphonium, although it does not demonstrate an ability to transport it. The interaction is compromised in the presence of NorC-antibody complex, consequently establishing a strategy to detect and block NorC and related transporters through the use of single-domain camelid antibodies.

59 BASIC BIOLOGICAL SCIENCES↗

A stable and highly selective metalloporphyrin based framework for the catalytic oxidation of cyclohexene

A new metalloporphyrin framework of molybdenum Mo 2 O 4 (C 48 H 28 N 4 O 8 )·(CH 3 ) 2 NH·5H 2 O·2DMF (Mo 2 TCPP) was synthesized from tetrakis(4-carboxyphenyl)porphyrin (H 4 TCPP) and sodium molybdate dihydrate by a hydrothermal method. Mo 2 TCPP is a 3D network with two sub-units, in which both TCPP ligands and each Mo 2 dimer act as four connection nodes. The crystal structure was determined by single crystal analysis and further characterized by FTIR, SEM, EDX, PXRD, XPS and TGA. Here cumene hydrogen peroxide and hydrogen peroxide were used as oxidants to study the catalytic activity of new metalloporphyrins in the oxidation of cyclohexene at different temperatures. The conversion rate of cyclohexene and the selectivity of epoxycyclohexane were both higher than 99%, which was better than the previously published research results. The stability of the catalyst before and after the reaction was further tested for 10 runs without obvious degradation. The catalyst was stable in different solutions such as acidic, water and alkaline. These results shed light on the future development of new catalytic materials based on metalloporphyrin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advances in the electron diffraction characterization of atomic clusters and nanoparticles

Nanoparticles and metallic clusters continue to make a remarkable impact on novel and emerging technologies. In recent years, there have been impressive advances in the controlled synthesis of clusters and their advanced characterization. One of the most common ways to determine the structures of nanoparticles and clusters is by means of X-ray diffraction methods. However, this requires the clusters to crystallize in a similar way to those used in protein studies, which is not possible in many cases. Novel methods based on electron diffraction have been used to efficiently study individual nanoparticles and clusters and these can overcome the obstacles commonly encountered during X-ray diffraction methods without the need for large crystals. These novel methodologies have improved with advances in electron microscopy instrumentation and electron detection. Here, we review advanced methodologies for characterizing metallic nanoparticles and clusters using a variety of electron diffraction procedures. These include selected area electron diffraction, nanobeam diffraction, coherent electron diffraction, precession electron diffraction, scanning transmission electron microcopy diffraction, and high throughput data analytics, which leverage deep learning to reduce the propensity for data errors and translate nanometer and atomic scale measurements into material data.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Aggregation-induced phosphorescence sensitization in two heptanuclear and decanuclear gold–silver sandwich clusters

The strategy of aggregation-induced emission enhancement (AIEE) has been proven to be efficient in wide areas and has recently been adopted in the field of metal nanoclusters. Furthermore, the relationship between atomically precise clusters and AIEE is still unclear. Herein, we have successfully obtained two few-atom heterometallic gold–silver hepta-/decanuclear clusters, denoted Au 6 Ag and Au 9 Ag, and determined their structures by X-ray diffraction and mass spectrometry. The nature of the AuI…AgI interactions thereof is demonstrated through energy decomposition analysis to be far-beyond typical closed-shell metal–metal interaction dominated by dispersion interaction. Furthermore, a positive correlation has been established between the particle size of the nanoaggregates and the photoluminescence quantum yield for Au 6 Ag, manifesting AIEE control upon varying the stoichiometric ratio of Au : Ag in atomically-precise clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Charge state-dependent ion condensation near conjugated polymer backbones

Despite the technological appeal of polymeric organic mixed ionic/electronic conductors (OMIECs) for diverse applications, a deep understanding of the fundamentals of mixed charge transport in these materials, especially regarding the complex interplay between polymer, ion and solvent structure in determining transport, is lacking. Herein, extensive molecular dynamics (MD) simulations of a model OMIEC representing various electrochemically gated states are reported that reveal charge state-dependent counterion condensation. X-ray diffraction simulations based on the MD data predict a measurable change in the scattering intensity at the counterion absorption edge, indicative of counterion repositioning with charging. We leverage an operando resonant X-ray scattering technique to experimentally corroborate the simulated scattering and report excellent agreement between predicted and experimental data, confirming that counterions preferentially reside in the lamellar mid-plane of crystallites at low doping, and near the polymer backbone at higher doping. Driving forces for ion type-dependent spatial repositioning and implications thereof are discussed.

36 MATERIALS SCIENCE↗

Chapter 15: Summary and Outlook

In the various chapters of this book, numerous characterization techniques are presented that can be applied to thin-film solar cells to determine (micro)structural, compositional, electrical, and optoelectronic properties. What has yet to be more fully elucidated is to what extent these characterization techniques can be combined, in a correlative way, to enhance the information gathered on materials and devices. Indeed, it is valuable to consider combining techniques to verify the relevance of the measured materials properties or to obtain them on different length scales-to compare surface with bulk properties, or to correlate structure and composition of materials with electrical and optoelectronic properties.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Crystallography of low Z material at ultrahigh pressure: Case study on solid hydrogen

Diamond anvil cell techniques have been improved to allow access to the multimegabar ultrahigh-pressure region for exploring novel phenomena in condensed matter. However, the only way to determine crystal structures of materials above 100 GPa, namely, X-ray diffraction (XRD), especially for low Z materials, remains nontrivial in the ultrahigh-pressure region, even with the availability of brilliant synchrotron X-ray sources. In this work,we perform a systematic study, choosing hydrogen (the lowest X-ray scatterer) as the subject, to understand how to better perform XRD measurements of low Z materials at multimegabar pressures. The techniques that we have developed have been proved to be effective in measuring the crystal structure of solid hydrogen up to 254 GPa at room temperature [C. Ji et al.,Nature 573, 558–562 (2019)]. We present our discoveries and experiences with regard to several aspects of this work, namely, diamond anvil selection, sample configuration for ultrahigh-pressure XRD studies,XRD diagnostics for low Z materials, and related issues in data interpretation and pressure calibration.We believe that these methods can be readily extended to other low Z materials and can pave the way for studying the crystal structure of hydrogen at higher pressures, eventually testing structural models of metallic hydrogen.

36 MATERIALS SCIENCE↗

Stochastic density functional theory: Real- and energy-space fragmentation for noise reduction

Stochastic density functional theory (sDFT) is becoming a valuable tool for studying ground-state properties of extended materials. The computational complexity of describing the Kohn-Sham orbitals is replaced by introducing a set of random (stochastic) orbitals leading to linear and often sub-linear scaling of certain ground-state observables at the account of introducing a statistical error. Schemes to reduce the noise are essential, for example, for determining the structure using the forces obtained from sDFT. Recently, we have introduced two embedding schemes to mitigate the statistical fluctuations in the electron density and resultant forces on the nuclei. Both techniques were based on fragmenting the system either in real space or slicing the occupied space into energy windows, allowing for a significant reduction in the statistical fluctuations. For chemical accuracy, further reduction of the noise is required, which could be achieved by increasing the number of stochastic orbitals. However, the convergence is relatively slow as the statistical error scales as 1 / N χ according to the central limit theorem, where N χ is the number of random orbitals. In this paper, we combined the embedding schemes mentioned above and introduced a new approach that builds on overlapped fragments and energy windows. The new approach significantly lowers the noise for ground-state properties, such as the electron density, total energy, and forces on the nuclei, as demonstrated for a G-center in bulk silicon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metal–ceramic composite structures for fabrication of high power density plasmonic devices

The recent decade brought many advances to plasmonics, but high power density plasmonic antennas designed to behave as heaters or operate in high temperature environments are still facing material stability challenges preventing their ultimate use. Gold has been the optimal choice among plasmonic materials but experiences morphology changes at temperature that result in device efficiency reduction and failure. Bulk titanium nitride has been explored as a solution but has deal-breaking tradeoffs in device quality factor. In this paper, we explore via proof-of-concept the use of a metal–ceramic composite structure to determine whether a bulk Au nanorod can provide strong plasmonic resonances while coated with an ultrathin conformal layer of titanium nitride or silica to provide morphological stability and sufficient plasmonic activity without excessive resonance quality degradation. We show SEM-level morphological stability for temperatures up to 500 °C with coatings below 4 nm. Computer modeling suggests the ultrathin titanium nitride has detrimental effects on the strong plasmonic resonances of a Au nanorod. Here, we then looked into other possible coatings for solutions to stabilize high power density plasmonic antennas including plasmonic oxides, metal adhesion layers, and silica, the latter appearing to be the best option while lowering the overall peak electric field intensity, the silica increases the electric field intensity at its boundary.

36 MATERIALS SCIENCE↗

Characterizing the multi-dimensional reaction dynamics of dihalomethanes using XUV-induced Coulomb explosion imaging

Site-selective probing of iodine 4d orbitals at 13.1 nm was used to characterize the photolysis of CH 2 I 2 and CH 2 BrI initiated at 202.5 nm. Time-dependent fragment ion momenta were recorded using Coulomb explosion imaging mass spectrometry and used to determine the structural dynamics of the dissociating molecules. Correlations between these fragment momenta, as well as the onset times of electron transfer reactions between them, indicate that each molecule can undergo neutral three-body photolysis. For CH 2 I 2 , the structural evolution of the neutral molecule was simultaneously characterized along the C–I and I–C–I coordinates, demonstrating the sensitivity of these measurements to nuclear motion along multiple degrees of freedom.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High pressure melt line of nickel using a generalized embedded atomic method potential

As the second most abundant metal in the Earth's core, nickel plays an important role in determining the structure and temperature of the Earth's core. Yet, the melt line of Ni at pressures corresponding to the Earth's core has not been explored in the literature. Many previous experimental and simulation efforts have reported the melting point of Ni at pressures below 100 GPa, but there exist large discrepancies, most of which have persisted due to various experimental and simulation bottlenecks in handling extreme pressure and temperature conditions. We adopted the generalized embedded atom method, which overcomes the limitations of existing interatomic potentials, to probe phase stability and phase boundaries of Ni at pressures between 50 and 500 GPa. Further, the potential was validated by comparing the cold curves, phonon dispersion curves, and enthalpies of fusion with ab initio density functional theory calculations. Our analysis shows that face centered cubic (FCC) is stable, and the hexagonal close packed (HCP) and body centered cubic (BCC) phases are metastable close to the melt line. Melting temperatures at different pressures were obtained from two-phase co-existence simulations and take the following functional form: $T$ m = $1969.23+19.15P-0.012P$ 2 . In contrast to iron, differences between the melting points of the stable and metastable phases of Ni are less than 250 K at 300 GPa, and the difference in melting points of the metastable BCC and HCP phases changes sign at 500 GPa, which implies that the phase transition mechanisms during solidification can be very complex.

36 MATERIALS SCIENCE↗