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Atomic and micro-structure features of nanoporous aluminosilicate glasses from reactive molecular dynamics simulations
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Nuclear deformation as a source of the nonlinearity of the King plot in the Yb + ion
We perform atomic relativistic many-body calculations of the field isotope shifts and calculations of corresponding nuclear parameters for all stable even-even isotopes of the Yb + ion. We demonstrate that if we take nuclear parameters of the Yb isotopes from a range of the state of the art nuclear models, which all predict strong quadrupole nuclear deformation, and then calculate nonlinearity of the King plot caused by the difference in the deformation in different isotopes, the result is consistent with the nonlinearity observed in the experiment. In conclusion, the changes of nuclear rms radius between isotopes extracted from experiment are consistent with those obtained in the nuclear calculations.
Laser Spectroscopy of Exotic Atoms and Molecules Containing Octupole-Deformed Nuclei
This project investigated the nuclear, atomic, and molecular structure of exotic atoms and molecules containing actinide isotopes. These short-lived radioactive systems are challenging to produce and study in the laboratory, yet they offer unique opportunities for fundamental science. These nuclei are predicted to exhibit pear-shaped (octupole) deformation, a rare collective nuclear behavior that dramatically enhances their sensitivity to fundamental physics phenomena such as time-reversal- and parity-violating effects. Such enhancements make them ideal probes for exploring open questions in our understanding of the universe such as the origin of the matter–antimatter asymmetry of the universe. To realize these measurements, the project led the development of a new laser spectroscopy experiment at MIT, and later commissioned at the Facility for Rare Isotope Beams (FRIB) at Michigan State University: the Resonance Ionization Spectroscopy Experiment (RISE). RISE combines the spectroscopic precision of collinear laser spectroscopy with the sensitivity of particle-detection techniques, enabling measurements of rare isotopes produced at rates as low as a few ions per second. The beamline was designed, built, and installed, and was successfully commissioned at FRIB during the grant period. RISE is now a permanent capability of the FRIB facility, and has produced several results on the study of rare atoms and molecules for nuclear structure and fundamental symmetries. In parallel with the FRIB program, the project contributed to the first precision laser-spectroscopy measurements of short-lived radioactive molecules. Working with international collaborators at CERN's ISOLDE facility, the team conducted pioneering experiments on radium monofluoride (RaF) and actinium monofluoride (AcF). The results from this work have been published in major journals of science, including Nature, Science, Nature Physics, Nature Communications, and Physical Review Letters. These findings have guided future experiments on the laser cooling of radioactive molecules, opening a new platform for precision tests of fundamental symmetries.
The General Atomic and Molecular Electronic Structure System (GAMESS): Novel Methods on Novel Architectures
The primary focus of GAMESS over the last 5 years has been the development of new high-performance codes that are able to take effective and efficient advantage of the most advanced computer architectures, both CPU and accelerators. These efforts include employing density fitting and fragmentation methods to reduce the high scaling of well-correlated (e.g., coupled-cluster) methods as well as developing novel codes that can take optimal advantage of graphical processing units and other modern accelerators. Because accurate wave functions can be very complex, an important new functionality in GAMESS is the quasi-atomic orbital analysis, an unbiased approach to the understanding of covalent bonds embedded in the wave function. Finally, best practices for the maintenance and distribution of GAMESS are also discussed.
Machine Learning for Prediction of Thermodynamic Descriptors
Our objective is to apply machine learning (ML) algorithms for the prediction of molecular catalysis descriptors from geometric properties derived from experimental crystallographic databases. Catalysis is often considered a “low-data” discipline that is poorly suited for ML methods. An exception is the extensive structural information that is available for molecular catalysts through the Cambridge Structural Database (CSD), which contains atomically precise molecular structures from X-ray diffraction analysis for >600K metal complexes. As a proof-of-principle, we targeted the prediction of hydricity, a thermodynamic property that provides understanding and control of catalytic hydride transfer. We built a training set composed of ~100 molecular complexes with a known hydricity and structural information from the CSD. This data set was converted into a machine-readable format using the smooth overlap of atomic positions (SOAP) representation and further labeled with simple electronic descriptors for the metal centers. Multiple different neural networks were trained on this data set, and the accuracy of the hydricity predictions ranged from < 2 kcal/mol to 20 kcal/mol. The accuracy of each model was highly sensitive to which compounds were in the train versus test set, underscoring the challenges associated with small and chemically diverse data sets. Finally, to further augment the data set, we attempted to experimentally measure several new hydricity values, however these experiments were unsuccessful due to undesired chemical reactivity of the selected complexes.
Tin resonance-ionization schemes for atomic- and nuclear-structure studies
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THEORETICAL STUDY OF ATOMIC AND MOLECULAR GASES AND THEIR REACTIONS IN THE UPPER ATMOSPHERE. SUMMARY OF WORK DONE IN THE PERIOD NOV. 1, 1960 TO APR. 30, 1961
In the previous report it was stated that the major mathematical problems of computations were nearly solved and an attempt is being made to start application of "Tables of Integrals" to the computation of the different states of atoms and molecules. In this respect I like to report that the computation of a number of states of atoms and molecules has been carried out. The results are so far confined only to the equilibrium distance of molecules. We are extending the calculation to other distances so as to compute potential energy curves of different states of molecules. We are also developing Thomas Fermi Statistical model of the atom to verify our results of more accurate calculation. The results so far have been very encouraging and I hope to report some of these results in the next paper.
Autonomous Molecular Structure Imaging with High-Resolution Atomic Force Microscopy for Molecular Mixture Discovery
Due to its single-molecule sensitivity, high-resolution atomic force microscopy (HR-AFM) has proved to be a valuable and uniquely advantageous tool to study complex molecular mixtures, which hold promise for developing clean energy and achieving environmental sustainability. However, significant challenges remain to achieve the full potential of the sophisticated and time-consuming experiments. Automation combined with machine learning (ML) and artificial intelligence (AI) is key to overcoming these challenges. Here we present Auto-HR-AFM, an AI tool to automatically collect HR-AFM images of petroleum-based mixtures. In this study, we trained an instance segmentation model to teach Auto-HR-AFM how to recognize features in HR-AFM images. Auto-HR-AFM then uses that information to optimize the imaging by adjusting the probe-molecule distance for each molecule in the run. Auto-HR-AFM is the initial tool that will lead to fully automated scanning probe microscopy (SPM) experiments, from start to finish. This automation will allow SPM to become a mainstream characterization technique for complex mixtures, an otherwise unattainable target.
Characterizing electronic and atomic structures for amorphous and molecular metal oxide catalysts at functional interfaces by combining soft X-ray spectroscopy and high-energy X-ray scattering
Amorphous thin film materials and heterogenized molecular catalysts supported on electrode and other functional interfaces are widely investigated as promising catalyst formats for applications in solar and electrochemical fuels catalysis. However the amorphous character of these catalysts and the complexity of the interfacial architectures that merge charge transport properties of electrode and semiconductor supports with discrete sites for multi-step catalysis poses challenges for probing mechanisms that activate and tune sites for catalysis. This minireview discusses advances in soft X-ray spectroscopy and high-energy X-ray scattering that provide opportunities to resolve interfacial electronic and atomic structures, respectively, that are linked to catalysis. This review discusses how these techniques can be partnered with advances in nanostructured interface synthesis for combined soft X-ray spectroscopy and high-energy X-ray scattering analyses of thin film and heterogenized molecular catalysts. Further, these combined approaches enable opportunities for the characterization of both electronic and atomic structures underlying fundamental catalytic function, and that can be applied under conditions relevant to device applications.
Temperature-induced structural evolution in liquid Ag-Ga alloys
Temperature-dependent atomic structural evolutions of liquid Ag 60 Ga 40 and Ag 70 Ga 30 alloys have been studied by in situ high-energy x-ray-diffraction (HEXRD) experiments combined with ab initio molecular-dynamics simulations. The experimental data show a reversible structural crossover at about 1050 ~ 1100 (± 50) K in both liquid Ag 60 Ga 40 and Ag 70 Ga 30 alloys. Obvious changes of the electrical resistivity, absolute thermoelectric power, and atomic diffusivity around the similar temperature range for both Ag-Ga liquids strongly support the HEXRD results. The origin of the liquid-to-liquid crossover in both Ag-Ga liquids was suggested to link with the rearrangements of Ag and Ga atoms, i.e., Ag and Ga atoms prefer to associate with themselves in the higher temperature range above 1100 K, consistent with the accelerated increase of the strong covalently bonded Ga–Ga dimers in both Ag-Ga liquids. In addition, more studies from the energy aspect are still desirable to understand the rearrangements of Ag and Ga atoms in the higher temperature range in both Ag-Ga liquids.
Fermi-Löwdin-orbital self-interaction correction using the optimized-effective-potential method within the Krieger-Li-Iafrate approximation
Perdew-Zunger self-interaction correction (PZ-SIC) offers a route to remove self interaction errors on an orbital-by-orbital basis. A recent formulation of PZ-SIC by Pederson, Ruzsinszky and Perdew proposes restricting the unitary transformation to localized orbitals called Fermi-Löwdin orbitals. This formulation, called the FLOSIC method, simplifies PZ-SIC calculations and was implemented self-consistently using a Jacobi-like (FLOSIC-Jacobi) iteration scheme. In this work we implement the FLOSIC approach using the Krieger-Li-Iafrate (KLI) approximation to the optimized effective potential (OEP). We compare the results of present FLOSIC-KLI approach with FLOSIC-Jacobi scheme for atomic energies, atomization energies, ionization energies, barrier heights, polarizability of chains of hydrogen molecules etc. to validate the FLOSIC-KLI approach. The FLOSICKLI approach, which is within the realm of Kohn-Sham theory, predicts smaller energy gaps between frontier orbitals due to the lowering of eigenvalues of the lowest unoccupied orbitals. Results show that atomic energies, atomization energies, ionization energy as an absolute of highest occupied orbital eigenvalue, and polarizability of chains of hydrogen molecules between the two methods agree within 2%. Lastly the FLOSIC-KLI approach is used to determine the vertical ionization energies of water clusters.
Towards C P -violation studies on superheavy molecules: Theoretical and experimental perspectives
Molecules containing superheavy atoms can be artificially created to serve as sensitive probes to study symmetry-violating phenomena. Here, we provide detailed theoretical studies of quantities relevant to the electron electric dipole moment (eEDM) and nucleus-electron scalar-pseudoscalar interactions in diatomic molecules containing superheavy lawrencium nuclei. The sensitivity to parity and time (or, equivalently, CP) reversal violating properties is studied for different neutral and ionic molecules. The effective electric fields in these systems are found to be about 3–4 times larger than other known molecules on which eEDM experiments are being performed. Similarly, these superheavy molecules exhibit an enhancement of more than 3 times for CP-violating scalar-pseudoscalar nucleus-electron interactions. Our preliminary analysis using the Woods-Saxon nuclear model also demonstrates that these results are sensitive to the diffuse surface interactions inside the Lr nucleus. We also briefly comment on some experimental aspects by discussing the production of these systems.
Dressed Ion-Pair States of an Ultralong-Range Rydberg Molecule
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Ultrathin Boron Growth onto Nanodiamond Surfaces via Electrophilic Boron Precursors
Diamond as a templating substrate is largely unexplored, and the unique properties of diamond, including its large bandgap, thermal conductance, and lack of cytotoxicity, makes it versatile in emergent technologies in medicine and quantum sensing. Surface termination of an inert diamond substrate and its chemical reactivity are key in generating new bonds for nucleation and growth of an overlayer material. Oxidized high-pressure high temperature (HPHT) nanodiamonds (NDs) are largely terminated by alcohols that act as nucleophiles to initiate covalent bond formation when an electrophilic reactant is available. In this work, we demonstrate a templated synthesis of ultrathin boron on ND surfaces using trigonal boron compounds. Boron trichloride (BCl 3 ), boron tribromide (BBr 3 ), and borane (BH 3 ) were found to react with ND substrates at room temperature in inert conditions. BBr 3 and BCl 3 were highly reactive with the diamond surface, and sheet-like structures were produced and verified with electron microscopy. Surface-sensitive spectroscopies were used to probe the molecular and atomic structure of the ND constructs’ surface, and quantification showed the boron shell was less than 1 nm thick after 1–24 h reactions. Observation of the reaction supports a self-terminating mechanism, similar to atomic layer deposition growth, and is likely due to the quenching of alcohols on the diamond surface. X-ray absorption spectroscopy revealed that boron-termination generated midgap electronic states that were originally predicted by density functional theory (DFT) several years ago. DFT also predicted a negative electron surface, which has yet to be confirmed experimentally here. The boron-diamond nanostructures were found to aggregate in dichloromethane and were dispersed in various solvents and characterized with dynamic light scattering for future cell imaging or cancer therapy applications using boron neutron capture therapy (BNCT). The unique templating mechanism based on nucleophilic alcohols and electrophilic trigonal precursors allows for covalent bond formation and will be of interest to researchers using diamond for quantum sensing, additive manufacturing, BNCT, and potentially as an electron emitter.
Isotope Shifts of Radium Monofluoride Molecules
Isotope shifts of 223–226,228 Ra 19 F were measured for different vibrational levels in the electronic transition A 2 II 1/2 ←X 2 Σ + . The observed isotope shifts demonstrate the particularly high sensitivity of radium monofluoride to nuclear size effects, offering a stringent test of models describing the electronic density within the radium nucleus. Ab initio quantum chemical calculations are in excellent agreement with experimental observations. These results highlight some of the unique opportunities that short-lived molecules could offer in nuclear structure and in fundamental symmetry studies.
A continuous symmetry breaking measure for finite clusters using Jensen-Shannon divergence
A quantitative measure of symmetry breaking is introduced that allows the quantification of which symmetries are most strongly broken due to the introduction of some kind of defect in a perfect structure. The method uses a statistical approach based on the Jensen-Shannon divergence. The measure is calculated by comparing the transformed atomic density function with its original. Software code is presented that carries the calculations out numerically using Monte Carlo methods. The behavior of this symmetry breaking measure is tested for various cases including finite size crystallites (where the surfaces break the crystallographic symmetry), atomic displacements from high symmetry positions, and collective motions of atoms due to rotations of rigid octahedra. Finally, the approach provides a powerful tool for assessing local symmetry breaking and offers new insights that can help researchers understand how different structural distortions affect different symmetry operations.
Direct structural retrieval from gas-phase ultrafast diffraction data using a genetic algorithm
Ultrafast scattering techniques such as ultrafast electron diffraction and ultrafast x-ray diffraction have been utilized to elucidate the structural dynamics, reaction intermediates, and final products in molecular reactions following photoexcitation. The time-dependent structures are typically not directly retrieved from the experimental data, but they rely on comparison with calculations. The genetic algorithm (GA), a global optimization strategy, can be used to retrieve the molecular structures directly from diffraction patterns without any theoretical input. However, the robustness of the GA with respect to real experimental conditions such as a limited momentum transfer range, noise, and artifacts has not been studied in detail. In this work, we characterize the performance of the GA with simulated data that mimic realistic experimental conditions. We have developed and implemented a variant of the GA specific to diffraction measurements which performs better in the presence of imperfect data compared to the standard implementation of the GA. We demonstrate this method with both synthetic data and experimental ultrafast electron diffraction data on the UV-induced photodissociation of trifluoroiodomethane (CF 3 I) molecules.