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At least 685 records · Page 38

Coherent soft X-ray pulses from an echo-enabled harmonic generation free-electron laser

It is known that X-ray free-electron lasers (FELs), which amplify light emitted by a relativistic electron beam, are extending nonlinear optical techniques to shorter wavelengths, adding element specificity by exciting and probing electronic transitions from core levels. These techniques would benefit tremendously from having a stable FEL source, generating spectrally pure and wavelength-tunable pulses. Here, we show that such requirements can be met by operating the FEL in the so-called echo-enabled harmonic generation (EEHG) configuration. Here, two external conventional lasers are used to precisely tailor the longitudinal phase space of the electron beam before emission of X-rays. We demonstrate high-gain EEHG lasing producing stable, intense, nearly fully coherent pulses at wavelengths as short as 5.9 nm (~211 eV) at the FERMI FEL user facility. Low sensitivity to electron-beam imperfections and observation of stable, narrow-band, coherent emission down to 2.6 nm (~474 eV) make the technique a prime candidate for generating laser-like pulses in the X-ray spectral region, opening the door to multidimensional coherent spectroscopies at short wavelengths.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Quantum coherence tomography of light-controlled superconductivity

The coupling between superconductors and oscillation cycles of light pulses, i.e., lightwave engineering, is an emerging control concept for superconducting quantum electronics. Although progress has been made towards terahertz-driven superconductivity and supercurrents, the interactions able to drive non-equilibrium pairing are still poorly understood, partially due to the lack of measurements of high-order correlation functions. In particular, the sensing of exotic collective modes that would uniquely characterize light-driven superconducting coherence, in a way analogous to the Meissner effect, is very challenging but much needed. Here we report the discovery of parametrically driven superconductivity by light-induced order-parameter collective oscillations in iron-based superconductors. The time-periodic relative phase dynamics between the coupled electron and hole bands drives the transition to a distinct parametric superconducting state out-of-equalibrium. This light-induced emergent coherence is characterized by a unique phase–amplitude collective mode with Floquet-like sidebands at twice the Higgs frequency. We measure non-perturbative, high-order correlations of this parametrically driven superconductivity by separating the terahertz-frequency multidimensional coherent spectra into pump–probe, Higgs mode and bi-Higgs frequency sideband peaks. We find that the higher-order bi-Higgs sidebands dominate above the critical field, which indicates the breakdown of susceptibility perturbative expansion in this parametric quantum matter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Probing inhomogeneous cuprate superconductivity by terahertz Josephson echo spectroscopy

Abstract Inhomogeneities crucially influence the properties of quantum materials, yet methods that can measure them remain limited and can access only a fraction of relevant observables. For example, local probes such as scanning tunnelling microscopy have documented that the electronic properties of cuprate superconductors are inhomogeneous over nanometre length scales. However, complementary techniques that can resolve higher-order correlations are needed to elucidate the nature of these inhomogeneities. Furthermore, local tunnelling probes are often effective only far below the critical temperature. Here we develop a two-dimensional terahertz spectroscopy method to measure Josephson plasmon echoes from an interlayer superconducting tunnelling resonance in a near-optimally doped cuprate. The technique allows us to study the multidimensional optical response of the interlayer Josephson coupling in the material and disentangle intrinsic lifetime broadening from extrinsic inhomogeneous broadening for interlayer superconducting tunnelling. We find that inhomogeneous broadening persists up to a substantial fraction of the critical temperature, above which this is overcome by the thermally increased lifetime broadening.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Chemical screening by time-resolved X-ray scattering to discover allosteric probes

Abstract Drug discovery relies on efficient identification of small-molecule leads and their interactions with macromolecular targets. However, understanding how chemotypes impact mechanistically important conformational states often remains secondary among high-throughput discovery methods. Here, we present a conformational discovery pipeline integrating time-resolved, high-throughput small-angle X-ray scattering (TR-HT-SAXS) and classic fragment screening applied to allosteric states of the mitochondrial import oxidoreductase apoptosis-inducing factor (AIF). By monitoring oxidized and X-ray-reduced AIF states, TR-HT-SAXS leverages structure and kinetics to generate a multidimensional screening dataset that identifies fragment chemotypes allosterically stimulating AIF dimerization. Fragment-induced dimerization rates, quantified with time-resolved SAXS similarity analysis ( k VR ), capture structure–activity relationships (SAR) across the top-ranked 4-aminoquinoline chemotype. Crystallized AIF–aminoquinoline complexes validate TR-SAXS-guided SAR, supporting this conformational chemotype for optimization. AIF–aminoquinoline structures and mutational analysis reveal active site F482 as an underappreciated allosteric stabilizer of AIF dimerization. This conformational discovery pipeline illustrates TR-HT-SAXS as an effective technology for targeting chemical leads to important macromolecular states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerated cryo-EM-guided determination of three-dimensional RNA-only structures

The discovery and design of biologically important RNA molecules is outpacing three-dimensional structural characterization. In this work, we demonstrate that cryo-electron microscopy can routinely resolve maps of RNA-only systems and that these maps enable subnanometer-resolution coordinate estimation when complemented with multidimensional chemical mapping and Rosetta DRRAFTER computational modeling. Furthermore ,this hybrid ‘Ribosolve’ pipeline detects and falsifies homologies and conformational rearrangements in 11 previously unknown 119- to 338-nucleotide protein-free RNA structures: full-length Tetrahymena ribozyme, hc16 ligase with and without substrate, full-length Vibrio cholerae and Fusobacterium nucleatum glycine riboswitch aptamers with and without glycine, Mycobacterium SAM-IV riboswitch with and without S-adenosylmethionine, and the computer-designed ATP-TTR-3 aptamer with and without AMP. Simulation benchmarks, blind challenges, compensatory mutagenesis, cross-RNA homologies and internal controls demonstrate that Ribosolve can accurately resolve the global architectures of RNA molecules but does not resolve atomic details. These tests offer guidelines for making inferences in future RNA structural studies with similarly accelerated throughput.

59 BASIC BIOLOGICAL SCIENCES↗

Automated Interpretation and Extraction of Topographic Information from Time of Flight Secondary Ion Mass Spectrometry Data

Time of flight secondary ion mass spectrometry (ToF SIMS) is one of the most powerful characterization tools allowing imaging of the chemical properties of various systems and materials. It allows precise studies of the chemical composition with sub-100-nm lateral and nanometer depth spatial resolution. However, comprehensive interpretation of ToF SIMS results is challengeable, because of the data volume and its multidimensionality. Furthermore, investigation of the samples with pronounced topographical features are complicated by the spectral shift. In this work we developed approach for the comprehensive ToF SIMS data interpretation based on the data analytics and automated extraction of the sample topography based on time of flight shift. We further applied this approach to investigate correlation between biological function and chemical composition in Arabidopsis roots.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗

A comprehensive simulation framework for imaging single particles and biomolecules at the European X-ray Free-Electron Laser

The advent of newer, brighter, and more coherent X-ray sources, such as X-ray Free-Electron Lasers (XFELs), represents a tremendous growth in the potential to apply coherent X-rays to determine the structure of materials from the micron-scale down to the Angstrom-scale. There is a significant need for a multi-physics simulation framework to perform source-to-detector simulations for a single particle imaging experiment, including (i) the multidimensional simulation of the X-ray source; (ii) simulation of the wave-optics propagation of the coherent XFEL beams; (iii) atomistic modelling of photon-material interactions; (iv) simulation of the time-dependent diffraction process, including incoherent scattering; (v) assembling noisy and incomplete diffraction intensities into a three-dimensional data set using the Expansion-Maximisation-Compression (EMC) algorithm and (vi) phase retrieval to obtain structural information. Furthermore, we demonstrate the framework by simulating a single-particle experiment for a nitrogenase iron protein using parameters of the SPB/SFX instrument of the European XFEL. This exercise demonstrably yields interpretable consequences for structure determination that are crucial yet currently unavailable for experiment design.

42 ENGINEERING↗

Visualizing Surface Plasmons with Photons, Photoelectrons, and Electrons

Both photons and electrons may be used to excite surface plasmon polaritons, the collective charge density fluctuations at the surface of metal nanostructures. By virtue of their nanoscopic and dissipative nature, a detailed characterization of surface plasmon (SP) eigenmodes in real space-time ultimately requires joint sub-nanometer spatial and sub-femtosecond temporal resolution. The latter realization has driven significant developments in the past few years, aimed at interrogating both localized and propagating SP modes over the relevant length and time scales. In this mini-review, we briefly highlight different techniques we employ to visualize the enhanced electric fields associated with SPs. Specifically, we discuss recent hyperspectral optical microscopy, tip-enhanced Raman nano-spectroscopy, nonlinear photoemission electron microscopy, as well as correlated scanning transmission electron microscopy-electron energy loss spectroscopy measurements targeting prototypical plasmonic nanostructures and constructs. Through selected practical examples, we examine the information content in multidimensional images recorded by taking advantage of each of the aforementioned techniques. In effect, we illustrate how SPs can be visualized at the ultimate limits of space and time.

Environmental Molecular Sciences Laboratory↗

Structural elucidation of a mononuclear titanium methylidene

The first example of a structurally characterized titanium methylidene, (PN) 2 Ti=CH 2 , has been prepared via one-electron oxidation of (PN) 2 Ti(CH 3 ) followed by deprotonation or by H-atom abstraction using an aryloxyl radical. The Ti=C distance was found to be 1.939(3) Å, and variable temperature, multinuclear, and multidimensional NMR spectroscopic experiments revealed the methylidene to engage in long range interactions with protons on the ligand framework. Here, computational studies showed that the Ti=C bond, which until now has eluded structural studies, displays all the hallmarks of a prototypical Schrock-carbene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A structural examination and collision cross section database for over 500 metabolites and xenobiotics using drift tube ion mobility spectrometry

The confident identification of metabolites and xenobiotics in biological and environmental studies is an analytical challenge due to their immense dynamic range, vast chemical space and structural diversity. Ion mobility spectrometry (IMS) is widely used for small molecule analyses since it can separate isomeric species and be easily coupled with front end separations and mass spectrometry for multidimensional characterizations. However, to date IMS metabolomic and exposomic studies have been limited by an inadequate number of accurate collision cross section (CCS) values for small molecules, causing features to be detected but not confidently identified. In this work, we utilized drift tube IMS (DTIMS) to directly measure CCS values for over 450 small molecules including primary metabolites, secondary metabolites and xenobiotics. Since DTIMS measurements do not need calibrates, they avoid calibration errors which can cause CCS accuracy problems and difficulties identifying structurally similar molecules. Furthermore, all measurements were performed in triplicate in both positive and negative polarities with nitrogen gas and seven different electric fields, so that relative standard deviations (RSD) could be assessed for each molecule and structural differences studied. The primary metabolites selected for the database are from key metabolism pathways such as glycolysis, the pentose phosphate pathway, and the tricarboxylic acid (TCA) cycle, while the secondary metabolites consist of classes such as terpenes and flavonoids, and the xenobiotics represent a range of molecules from antibiotics to polycyclic aromatic hydrocarbons. Different CCS trends were observed for several of the diverse small molecule classes, allowing insight in their separations and a possible why of classifying unknowns. This CCS database and structural information are freely available for download at http://panomics.pnnl.gov/metabolites/ with new molecules being added monthly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiple pulse coherent dynamics and wave packet control of the N 2 a" 1 Σ$^+_g$ dark state by attosecond four-wave mixing

Nonlinear multidimensional spectroscopy is ubiquitous in the optical and radio frequency regions as a powerful tool to access structure and dynamics. The extension of this technique into the extreme ultraviolet (XUV) region with attosecond pulses holds promise for probing electronic dynamics and correlations with unprecedented time and spatial resolution. In this work, we use noncollinear four-wave mixing of a weak XUV attosecond pulse train (11–17 eV) and few-femtosecond NIR pulses (800 nm) to spectroscopically and dynamically probe the dipole-forbidden double-well potential of the a" 1 Σ + g electronic state of nitrogen. The results demonstrate optical coupling of the inner and outer limits of the initial XUV-prepared vibrational wave packet in the valence character b' 1 Σ + u state to the inner and outer wells, respectively, of the a" 1 Σ + g double well state by 800 nm light. Two four-wave mixing schemes with different pulse timing sequences and noncollinear beam geometries are used (one NIR pulse collinear and one NIR pulse noncollinear versus both NIR pulses noncollinear to the XUV beam) to measure the a" dark state energetic structure and to control the dynamical preparation and motion of a dark state wave packet by selective population of either the inner Rydberg or outer valence-character potential well. Finally, experimental measurements of the a" 1 Σ + g outer well vibrational spacing and anharmonicity closely match the values theoretically predicted for this previously unobserved state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Theoretical H + O 3 rate coefficients from ring polymer molecular dynamics on an accurate global potential energy surface: assessing experimental uncertainties

Thermal rate coefficients and kinetic isotope effects have been calculated for an important atmospheric reaction H/D + O 3 → OH/OD + O2 based on an accurate permutation invariant polynomial-neural network potential energy surface, using ring polymer molecular dynamics (RPMD), quasi-classical trajectory (QCT) and variational transition-state theory (VTST) with multidimensional tunneling. The RPMD approach yielded results that are generally in better agreement with experimental rate coefficients than the VTST and QCT ones, especially at low temperatures, attributable to its capacity to capture quantum effects such as tunneling and zero-point energy. Additionally, the theoretical results support one group of existing experiments over the other. In addition, rate coefficients for the D + O 3 → OD + O 2 reaction are also reported using the same methods, which will allow a stringent assessment of future experimental measurements, thus helping to reduce the uncertainty in the recommended rate coefficients of this reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncovering phase transformation, morphological evolution, and nanoscale color heterogeneity in tungsten oxide electrochromic materials

Controlling the electrochemical interfacial processes that govern the durability of electrochromic devices represents a key challenge in developing sustainable and cost-effective smart windows. Here, we revisit the classical tungsten trioxide (WO 3 ) materials as a platform to uncover the previously unknown interrelationship between phase transformation, morphological evolution, and nanoscale color heterogeneity in these materials. Through synchrotron/electron spectroscopic and imaging analyses, we report that the WO 3 –electrolyte interface is influenced by the tungsten dissolution and redeposition during the electrochemical cycling. The tungsten redeposition provokes the in situ crystal growth, which ultimately leads to the phase transformation from the semicrystalline WO 3 to a nanoflake-shaped, proton-trapped tungsten trioxide dihydrate (H x WO 3 · 2 H 2 O). The multidimensional quantification of the electronic structure reveals that the tungsten reduction caused by the proton trapping is heterogeneous at the nanometric scale and is responsible for the nanoscale color heterogeneity. The interplay between phase transformation, morphological evolution, and nanoscale color heterogeneity results in degraded optical modulation, switching kinetics, coulombic efficiency, and bleached-state transparency. Our results highlight that the high interfacial reactivity near the electrode surface may be the underlying mechanism for undesired bulk structural changes of electrochromic materials, and calls for fundamental studies in probing and controlling the electrode–electrolyte interfacial processes in electrochromic devices.

36 MATERIALS SCIENCE↗

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗

Metadynamics investigation of lanthanide solvation free energy landscapes and insights into separations energetics

Lanthanide ion solvation chemistry in nonaqueous phases is key to understanding and developing effective separation processes for these critical materials. Due to the complexity and inherent disorder of the solution phase, a comprehensive picture of the solvated metal ion is often difficult to generate solely from conventional spectroscopic approaches and electronic structure calculations, particularly in the extractant phase. In this work, we use classical molecular dynamics (MD) simulation with an advanced sampling technique, metadynamics, supplemented by experimental spectroscopy and speciation analysis, to measure lanthanide solvation free energy landscapes. We define coordination-based collective variables to probe the entire range of solvation configurations in the organic phase of lanthanum (La), europium (Eu), and lutetium (Lu) nitrate salts bound with a commonly used extractant, N,N′-dimethyl, N,N′-dioctylhexylethoxymalonamide (DMDOHEMA). The known lanthanide extraction trend of La ≈ Eu > Lu is readily explained by the measured free energy surfaces, which show consistent DMDOHEMA coordination from La to Eu, followed by loss of DMDOHEMA coordination from Eu to Lu. These simulations suggest how ligand crowding at the metal center can control selectivity, in this case resulting in the opposite extraction trend as observed with other conventional extractants, where the enthalpic contribution from increasing lanthanide charge density across the series dominates the extraction energetics. We also find that the presence of inner-sphere water, verified by time-resolved fluorescence, diversifies the accessible solvation structures. As a result, understanding solvation requires consideration of an entire thermodynamic ensemble, rather than the single dominant lowest-energy structure, as is often considered out of necessity in interpretation of spectroscopic data or in electronic structure-based ligand design approaches. In general, we demonstrate how metadynamics uniquely enables investigation of complex, multidimensional solvation energetic landscapes, and how it can explain selectivity trends where extraction is controlled by more complex mechanisms than simple charge density-based selectivity.

Wang, Xiaoyu↗

Experimental trends and theoretical descriptors for electrochemical reduction of carbon dioxide to formate over Sn-based bimetallic catalysts

The electrochemical carbon dioxide reduction reaction (CO 2 RR) using renewable energy sources is a promising solution for mitigating CO 2 emissions. In particular, CO 2 RR to formate represents a commercially profitable target. However, a comprehensive understanding of the catalytic mechanisms of Sn-based catalysts under reaction conditions, including the real-time structural evolution of catalysts and the role of all key reaction intermediates in influencing the CO 2 RR selectivity, is still lacking. The current study reports a framework to study the selectivity preference of Sn-based bimetallic catalysts using a combination of electrochemical measurements, in situ characterization, and density functional theory (DFT) calculations. The addition of a second metal (Co, Ni, Ag, Zn, Ga, Bi) was found to play a vital role in affecting the CO 2 RR performance. In situ X-ray absorption near edge structure (XANES) measurements revealed a dynamic evolution in the Sn valence state induced by different secondary metals. A multidimensional descriptor involving all the key reaction intermediates was developed to assess formate selectivity using a 2-dimensional volcano plot. Finally, this research offers an effective framework for understanding CO 2 RR catalytic selectivity by considering both the real-time structural evolution of catalysts and all the key intermediates involved.

58 GEOSCIENCES↗