Hyperfine structure and isotope shifts of xenon measured for near-infrared transitions with Doppler-free saturated absorption spectroscopy
Explore the source record for details and available documents.
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
The electronic properties and optical response of ice and water are intricately shaped by their molecular structure, including the quantum mechanical nature of the hydrogen atoms. Despite numerous previous studies, a comprehensive understanding of the nuclear quantum effects (NQEs) on the electronic structure of water and ice at finite temperatures remains elusive. Here, we utilize molecular simulations that harness efficient machine-learning potentials and many-body perturbation theory to assess how NQEs impact the electronic bands of water and hexagonal ice. By comparing path-integral and classical simulations, we find that NQEs lead to a larger renormalization of the fundamental gap of ice, compared to that of water, ultimately yielding similar bandgaps in the two systems, consistent with experimental estimates. Our calculations suggest that the increased quantum mechanical delocalization of protons in ice, relative to water, is a key factor leading to the enhancement of NQEs on the electronic structure of ice.
Abstract The electronic, optical, and magnetic properties of graphene nanoribbons (GNRs) can be engineered by controlling their edge structure and width with atomic precision through bottom‐up fabrication based on molecular precursors. This approach offers a unique platform for all‐carbon electronic devices but requires careful optimization of the growth conditions to match structural requirements for successful device integration, with GNR length being the most critical parameter. In this work, the growth, characterization, and device integration of 5‐atom wide armchair GNRs (5‐AGNRs) are studied, which are expected to have an optimal bandgap as active material in switching devices. 5‐AGNRs are obtained via on‐surface synthesis under ultrahigh vacuum conditions from Br‐ and I‐substituted precursors. It is shown that the use of I‐substituted precursors and the optimization of the initial precursor coverage quintupled the average 5‐AGNR length. This significant length increase allowed the integration of 5‐AGNRs into devices and the realization of the first field‐effect transistor based on narrow bandgap AGNRs that shows switching behavior at room temperature. The study highlights that the optimized growth protocols can successfully bridge between the sub‐nanometer scale, where atomic precision is needed to control the electronic properties, and the scale of tens of nanometers relevant for successful device integration of GNRs.
Peptoids (N-substituted glycines) are a group of highly controllable peptidomimetic polymers. Amphiphilic diblock peptoids have been engineered to assemble crystalline nanospheres, nanofibrils, nanosheets, and nanotubes with biochemical, biomedical, and bioengineering applications. The mechanical properties of peptoid nanoaggregates and their relationship to the emergent self-assembled morphologies have been relatively unexplored and are critical for the rational design of peptoid nanomaterials. In this work, we consider a family of amphiphilic diblock peptoids consisting of a prototypical tube-former (Nbrpm6Nc6, a NH 2 -capped hydrophobic block of six N-((4-bromophenyl)methyl)glycine residues conjugated to a polar NH 3 (CH 2 ) 5 CO tail), a prototypical sheet-former (Nbrpe6Nc6, where the hydrophobic block comprises six N-((4-bromophenyl)ethyl)glycine residues), and an intermediate sequence that forms mixed structures ((NbrpeNbrpm)3Nc6). We combine all-atom molecular dynamics simulations and atomic force microscopy to determine the mechanical properties of the self-assembled 2D crystalline nanosheets and relate these properties to the observed self-assembled morphologies. We find good agreement between our computational predictions and experimental measurements of Young’s modulus of crystalline nanosheets. A computational analysis of the bending modulus along the two axes of the planar crystalline nanosheets reveals bending to be more favorable along the axis in which the peptoids stack by interdigitation of the side chains compared to that in which they form columnar crystals with π-stacked side chains. Here, we construct molecular models of nanotubes of the Nbrpm6Nc6 tube-forming peptoid and predict a stability optimum in good agreement with experimental measurements. A theoretical model of nanotube stability suggests that this optimum is a free energy minimum corresponding to a “Goldilocks” tube radius at which capillary wave fluctuations in the tube wall are minimized.
The non-additive kinetic potential $v^{\text{NAD}}$ is a key quantity in density-functional theory (DFT) embedding methods, such as frozen density embedding theory and partition DFT. $v^{\text{NAD}}$ is a bi-functional of electron densities $\rho_{\rm B}$ and $\rho_{\rm tot} = \rho_{\rm A} + \rho_{\rm B}$. It can be evaluated using approximate kinetic-energy functionals, but accurate approximations are challenging. The behavior of $v^{\text{NAD}}$ in the vicinity of the nuclei has long been questioned, and singularities were seen in some approximate calculations. In this article, the existence of singularities in $v^{\text{NAD}}$ is analyzed analytically for various choices of $\rho_{\rm B}$ and $\rho_{\rm tot}$, using the nuclear cusp conditions for the density and Kohn-Sham potential. It is shown that no singularities arise from smoothly partitioned ground-state Kohn-Sham densities. We confirm this result by numerical calculations on diatomic test systems HeHe, HeLi$^+$, and H$_2$, using analytical inversion to obtain a numerically exact $v^{\rm NAD}$ for the local density approximation. We examine features of $v^{\rm NAD}$ which can be used for development and testing of approximations to $v^{\rm NAD}[\rho_{\rm B},\rho_{\rm tot}]$ and kinetic-energy functionals.
In this work, we report on the nonlinear ionization of argon atoms in the short wavelength regime using ultraintense x rays from the European XFEL. After sequential multiphoton ionization, high charge states are obtained. For photon energies that are insufficient to directly ionize a 1s electron, a different mechanism is required to obtain ionization to Ar 17+ . We propose this occurs through a two-color process where the second harmonic of the FEL pulse resonantly excites the system via a 1s→2p transition followed by ionization by the fundamental FEL pulse, which is a type of x-ray resonance-enhanced multiphoton ionization (REMPI). This resonant phenomenon occurs not only for Ar 16+ , but also through lower charge states, where multiple ionization competes with decay lifetimes, making x-ray REMPI distinctive from conventional REMPI. With the aid of state-of-the-art theoretical calculations, we explain the effects of x-ray REMPI on the relevant ion yields and spectral profile.
Graph-based linear scaling electronic structure theory for quantum-mechanical molecular dynamics simulations [A. M. N. Niklasson et al., J. Chem. Phys. 144, 234101 (2016)] is adapted to the most recent shadow potential formulations of extended Lagrangian Born–Oppenheimer molecular dynamics, including fractional molecular-orbital occupation numbers [A. M. N. Niklasson, J. Chem. Phys. 152, 104103 (2020) and A. M. N. Niklasson, Eur. Phys. J. B 94, 164 (2021)], which enables stable simulations of sensitive complex chemical systems with unsteady charge solutions. The proposed formulation includes a preconditioned Krylov subspace approximation for the integration of the extended electronic degrees of freedom, which requires quantum response calculations for electronic states with fractional occupation numbers. For the response calculations, we introduce a graph-based canonical quantum perturbation theory that can be performed with the same natural parallelism and linear scaling complexity as the graph-based electronic structure calculations for the unperturbed ground state. Further, the proposed techniques are particularly well-suited for semi-empirical electronic structure theory, and the methods are demonstrated using self-consistent charge density-functional tight-binding theory both for the acceleration of self-consistent field calculations and for quantum-mechanical molecular dynamics simulations. Graph-based techniques combined with the semi-empirical theory enable stable simulations of large, complex chemical systems, including tens-of-thousands of atoms.
Statistical and epidemiological data imply temperature sensitivity of the SARS-CoV2 coronavirus. However, the molecular level understanding of the virus structure at different temperature is still not clear. Spike protein is the outermost structural protein of the SARS-CoV-2 virus which interacts with the Angiotensin Converting Enzyme 2 (ACE2), a human receptor, and enters the respiratory system. In this study, we performed an all atom molecular dynamics simulation to study the effect of temperature on the structure of the Spike protein. After 200 ns of simulation at different temperatures, we came across some interesting phenomena exhibited by the protein. We found that the solvent exposed domain of Spike protein, namely S1, is more mobile than the transmembrane domain, S2. Structural studies implied the presence of several charged residues on the surface of N-terminal Domain of S1 which are optimally oriented at 10– 30°C. Bioinformatics analyses indicated that it is capable of binding to other human receptors and should not be disregarded. Additionally, we found that receptor binding motif (RBM), present on the receptor binding domain (RBD) of S1, begins to close around temperature of 40°C and attains a completely closed conformation at 50°C. We also found that the presence of glycan moieties did not influence the observed protein dynamics. Nevertheless, the closed conformation disables its ability to bind to ACE2, due to the burying of its receptor binding residues. Our results clearly show that there are active and inactive states of the protein at different temperatures. This would not only prove beneficial for understanding the fundamental nature of the virus, but would be also useful in the development of vaccines and therapeutics.
Scalable solar-energy conversion requires photoactive materials that combine the efficiency of natural photosynthetic systems with the stability and processability needed for practical applications. Achieving reliable charge transport in soft, self-assembled organic materials remains challenging, as structural fluctuations and environmental effects strongly influence charge-transfer (CT) rates. Here, we present a broadly applicable computational framework for evaluating CT rates in the condensed phase, combining Fermi’s golden rule rate theory with inputs from all-atom molecular dynamics (MD) simulations and first-principles electronic-structure calculations. The approach does not rely on system-specific parametrization and is applicable to a wide range of soft and disordered materials. We demonstrate the applicability and usefulness of the framework on redox-active peptoids functionalized with iron–porphyrin (Fe–P) complexes, a bioinspired platform with programmable donor–acceptor units and tunable three-dimensional organization. The calculated CT rates exhibit strong sensitivity to molecular conformation, with variations spanning several orders of magnitude. This dependence is shown to arise from the pronounced variation in diabatic electronic coupling with the relative orientations and separations of the Fe–P complexes across the conformational ensemble. The framework provides a consistent route for connecting atomistic structure to CT kinetics in the condensed phase and enables analysis of structure–rate relations in organic semiconducting systems.
Abstract The challenge of targeting RNA with small molecules necessitates a better understanding of RNA–ligand interaction mechanisms. However, the dynamic nature of nucleic acids, their ligand‐induced stabilization, and how conformational changes influence gene expression pose significant difficulties for experimental investigation. This work employs a combination of computational and experimental methods to address these challenges. By integrating structure‐informed design, crystallography, and machine learning‐augmented all‐atom molecular dynamics simulations (MD), we synthesized, biophysically and biochemically characterized, and studied the dissociation of a library of small molecule activators of the 5‐aminoimidazole–4–carboxamide ribonucleotide triphosphate (ZTP) riboswitch, a ligand‐binding RNA motif that regulates bacterial gene expression. We uncovered key interaction mechanisms, revealing valuable insights into the role of ligand binding kinetics on riboswitch activation. Further, we established that ligand on‐rates determine activation potency as opposed to binding affinity and elucidated RNA structural differences, which provide mechanistic insights into the interplay of RNA structure on riboswitch activation.
Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.
Abstract Motivation The state-of-art protein structure prediction methods such as AlphaFold are being widely used to predict structures of uncharacterized proteins in biomedical research. There is a significant need to further improve the quality and nativeness of the predicted structures to enhance their usability. In this work, we develop ATOMRefine, a deep learning-based, end-to-end, all-atom protein structural model refinement method. It uses a SE(3)-equivariant graph transformer network to directly refine protein atomic coordinates in a predicted tertiary structure represented as a molecular graph. Results The method is first trained and tested on the structural models in AlphaFoldDB whose experimental structures are known, and then blindly tested on 69 CASP14 regular targets and 7 CASP14 refinement targets. ATOMRefine improves the quality of both backbone atoms and all-atom conformation of the initial structural models generated by AlphaFold. It also performs better than two state-of-the-art refinement methods in multiple evaluation metrics including an all-atom model quality score—the MolProbity score based on the analysis of all-atom contacts, bond length, atom clashes, torsion angles, and side-chain rotamers. As ATOMRefine can refine a protein structure quickly, it provides a viable, fast solution for improving protein geometry and fixing structural errors of predicted structures through direct coordinate refinement. Availability and implementation The source code of ATOMRefine is available in the GitHub repository (https://github.com/BioinfoMachineLearning/ATOMRefine). All the required data for training and testing are available at https://doi.org/10.5281/zenodo.6944368.
In oxygenic photosynthetic organisms, the light reactions are performed by protein complexes embedded in the lipid bilayer of thylakoid membranes (TMs). The organization of the bulk lipid molecules into bilayer structures provide optimal conditions for the build-up of the proton motive force (pmf) and its utilization for ATP synthesis. However, the lipid composition of TMs is dominated by the non-bilayer lipid species monogalactosyl diacylglycerol (MGDG), and functional plant TMs, besides the bilayer, contain large amounts of non-bilayer lipid phases. Bulk lipids have been shown to be associated with lumenal, stromal-side and marginal-region proteins and proposed to play roles in the self-assembly and photoprotection of the photosynthetic machinery. Furthermore, it has recently been pointed out that the generation and utilization of pmf for ATP synthesis according to the ‘protet’ or protonic charge transfer model Kell (Biochim Biophys Acta Bioenerg 1865(4):149504, 2024), requires high MGDG content Garab (Physiol Plant 177(2):e70230, 2025). In this study, to gain better insight into the structural and functional roles of MGDG, we employed all atom and coarse-grained molecular dynamics simulations to explore how temperature, hydration levels and varying MGDG concentrations affect the structural and dynamic properties of bilayer membranes constituted of plant thylakoid lipids. Our findings reveal that MGDG promotes increased membrane fluidity and dynamic fluctuations in membrane thickness. MGDG-rich stacked bilayers spontaneously formed inverted hexagonal phases; these transitions were enhanced at low hydration levels and at elevated but physiologically relevant temperatures. It can thus be inferred that MGDG plays important roles in heat and drought stress mechanisms.
This Final Technical Report briefly summarizes the achievements during the lifetime of our DOE BES grant DE-FG02-97ER45623. The long-term goal of this project has been the development of quantitative theories of the interaction between radiation and matter, with a focus on x-ray spectroscopies. X-ray spectra have long been among the most important probes of atomic-scale structure and properties of matter, ranging from atoms and molecular systems to condensed matter and exotic states. These spectroscopies are widely used in investigations at the major DOE synchrotron x-ray facilities and related centers world-wide. In addition to fundamental theory, a major goal of our project has been the development of computational software that implements the theory for calculations of x-ray spectra of various materials throughout the periodic table. Due to the complex nature of x-ray spectra, quantitative theory is essential for its interpretation. The theory is challenging since it involves excited state electronic structure and many-body correlation effects that go beyond independent particle approximations like DFT or Hartree-Fock. Moreover, the experimental investigations typically involve a broad range of energy, time, and temperature scales, from the UV-Vis to hard x-ray energies of order 10 4 eV, and temperatures T from ambient up to the warm-dense-matter regime where the Fermi energy kBTF is of order a few eV, i.e., temperatures of order 105 Kelvin. This broad range of experimental conditions has fostered many novel theoretical approaches and computational techniques, many of which we have developed systematically over the duration of the grant. In contrast to the traditional wave-function approach of quantum theory and electronic structure methods, our theoretical approach is based on modern Green's function techniques. This approach is better suited for aperiodic structures, excited states, and broad spectral ranges, since it avoids the computational bottlenecks of sum-over-states approaches, as in the Fermi golden rule. This theoretical framework has been incorporated into efficient, user-friendly x-ray spectroscopy software which is now used routinely worldwide to simulate and analyze spectra. These theoretical tools provide an essential complement to synchrotron and next-generation light sources, which are used to investigate complex materials with ever increasing precision. Moreover, the synergism between theory, computation and experiment contributed by our research enhances scientific understanding and creates opportunities for innovations in materials and energy science and in many fields. As documented in this Report, this research grant has been remarkably successful in achieving these goals. In particular, this grant has supported the development of the x-ray spectroscopy software suite known as FEFF (named for an effective scattering amplitude f eff in the theory). The FEFF codes have become one of the premier tools for quantitative simulations of x-ray spectra as documented by many thousands of citations in the Web of Science and Google-Scholar.
Resolving the electronic structure of a single atom within a molecule is of fundamental importance for understanding and predicting chemical and physical properties of functional molecules such as molecular catalysts. However, the observation of the orbital signature of an individual atom is challenging. We report here the direct identification of two adjacent transition-metal atoms, Fe and Co, within phthalocyanine molecules using high-resolution noncontact atomic force microscopy (HR-AFM). HR-AFM imaging reveals that the Co atom is brighter and presents four distinct lobes on the horizontal plane whereas the Fe atom displays a “square” morphology. Pico-force spectroscopy measurements show a larger repulsion force of about 5 pN on the tip exerted by Co in comparison to Fe. Our combined experimental and theoretical results demonstrate that both the distinguishable features in AFM images and the variation in the measured forces arise from Co’s higher electron orbital occupation above the molecular plane. The ability to directly observe orbital signatures using HR-AFM should provide a promising approach to characterizing the electronic structure of an individual atom in a molecular species and to understand mechanisms of certain chemical reactions.
Amorphous solids such as glass, plastics and amorphous thin films are ubiquitous in our daily life and have broad applications ranging from telecommunications to electronics and solar cells 1-4 . However, owing to the lack of long-range order, the three-dimensional (3D) atomic structure of amorphous solids has so far eluded direct experimental determination 5-15 . Here we develop an atomic electron tomography reconstruction method to experimentally determine the 3D atomic positions of an amorphous solid. Using a multi-component glass-forming alloy as proof of principle, we quantitatively characterize the short- and medium-range order of the 3D atomic arrangement. We observe that, although the 3D atomic packing of the short-range order is geometrically disordered, some short-range-order structures connect with each other to form crystal-like superclusters and give rise to medium-range order. We identify four types of crystal-like medium-range order-face-centred cubic, hexagonal close-packed, body-centred cubic and simple cubic-coexisting in the amorphous sample, showing translational but not orientational order. These observations provide direct experimental evidence to support the general framework of the efficient cluster packing model for metallic glasses 10,12-14,16 . Finally, we expect that this work will pave the way for the determination of the 3D structure of a wide range of amorphous solids, which could transform our fundamental understanding of non-crystalline materials and related phenomena.
The configurational entropy of high entropy alloys (HEAs) plays little role in the stabilization of one particular crystal structure over another. We show that disorder-induced atomic displacements help stabilize body centered cubic (bcc) structure HEAs with average valences <4.7. These disorder-induced atomic displacements mimic the temperature-induced vibrations that stabilize the bcc structure of group IV elemental metals at high temperatures. The static displacements are significantly larger than for face centered cubic HEAs, approaching values associated with the Lindemann criterion for melting. Chemical disorder in high entropy alloys have a previously unidentified, nonentropic energy contribution that stabilizes a particular crystalline ground state.
Confined atomic systems are of great importance owing a multitude of possible applications in various areas of science and technology. Of particular interest are atoms encaged in the C 60 molecule, A@C 60 , since the near-spherical symmetry of C 60 simplifies theoretical studies, and the stability of C 60 renders it amenable to experimental examination. Herein a review of investigations of the electronic structure and dynamics of A@C 60 is presented in this manuscript focusing on developments in the last decade. Addressed mainly are how the confinement affects electronic structure properties such as ionization potentials, localization of atomic electrons, Shannon entropy, correlation effects, relativistic interactions, and others. In the area of dynamics, photoionization and e-A@C 60 scattering are reviewed and summarized, and the major effects of confinement on the dynamical properties, e.g., confinement resonances, hybridization, Wigner time delay, are delineated.