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According to the Hunter–Sanders model, geometries in π–π systems arise from competition between quadrupolar electrostatics (favoring an edge-to-face geometry) and London dispersion (favoring stacking), but this model misrepresents the molecular physics.
Predicting the structural properties of water and simple fluids confined in nanometer scale pores and channels is essential in, for example, energy storage and biomolecular systems. Classical continuum theories fail to accurately capture the interfacial structure of fluids. In this work, we develop a deep learning-based quasi-continuum theory (DL-QT) to predict the concentration and potential profiles of a Lennard-Jones (LJ) fluid and water confined in a nanochannel. The deep learning model is built based on a convolutional encoder–decoder network (CED) and is applied for high-dimensional surrogate modeling to relate the fluid properties to the fluid–fluid potential. The CED model is then combined with the interatomic potential-based continuum theory to determine the concentration profiles of a confined LJ fluid and confined water. Further, we show that the DL-QT model exhibits robust predictive performance for a confined LJ fluid under various thermodynamic states and for water confined in a nanochannel of different widths. The DL-QT model seamlessly connects molecular physics at the nanoscale with continuum theory by using a deep learning model.
Electrolytes mediate interactions between the cathode and anode and determine performance characteristics of batteries. Mixtures of multiple solvents are often used in electrolytes to achieve desired properties, such as viscosity, dielectric constant, boiling point, and melting point. Conventionally, multi-component electrolyte properties are approximated with linear mixing, but in practice, significant deviations are observed. Excess quantities can provide insights into the molecular behavior of the mixture and could form the basis for designing high-performance electrolytes. Here we investigate the excess density of commonly used Li-ion battery solvents such as cyclic carbonates, linear carbonates, ethers, and nitriles with molecular dynamics simulations. We additionally investigate electrolytes consisting of these solvents and a salt. The results smoothly vary with mole percent and are fit to permutation-invariant Redlich-Kister polynomials. Mixtures of similar solvents, such as cyclic-cyclic carbonate mixtures, tend to have excess properties that are lower in magnitude compared to mixtures of dissimilar substances, such as carbonate-nitrile mixtures. We perform experimental testing using our automated test stand, Clio, to provide validation to the observed simulation trends. We quantify the structure similarity using SOAP fingerprints to create a descriptor for excess density, enabling the design of electrolyte properties. To a first approximation, this will allow us to estimate the deviation of a mixture from ideal behavior based solely upon the structural dissimilarity of the components.
Ultrafast time-resolved x-ray scattering (TRXS) from a photoexcited molecular ensemble measures a distribution $S(Q, τ)$ of the x-ray momentum transfer Q and pump-probe delay τ in which all modes of motion induced by the excitation overlap. Frequency-resolved x-ray scattering (FRXS) based on $\tilde {S}\left(Q,\omega \right)$ separates each oscillation and dissociation channel in the TRXS data, enabling measurements of vibrational frequencies and phases, and dissociation velocities and time shifts. In this work, we extend FRXS analysis to study early-time accelerations as well. We show how these appear as diffuse scattering patterns with characteristic phase evolution in FXRS and we develop a set of transformations that isolate individual channels to measure the early-time accelerated motion. This procedure is used to analyze diatomic iodine x-ray scattering data with multiple dissociations, and the ability of this technique to characterize early-time accelerations of one dissociation channel even in the presence of another dissociation is demonstrated.
We present momentum-resolved coincidence measurements of strong-field single and double ionization of deuterated water (D 2 O) using intense few-cycle laser pulses. We measure the vector momentum of electrons and ions resulting from the laser-molecule interaction. This enables us to measure the photoelectron spectrum for electrons in coincidence with fragment ions having different momenta, which can be related to different final states of the cation and dication. The photoelectron spectra for different fragment ion momenta show striking differences, which can be interpreted in terms of the removal of electrons from different molecular orbitals, including the highest occupied molecular orbital (HOMO), as well as more deeply bound ones (e.g., HOMO-2). Here, we discuss our measurements in light of calculations which model the strong-field light matter interaction.
Estimating a quantum phase is a necessary task in a wide range of fields of quantum science. To accomplish this task, two well-known methods have been developed in distinct contexts, namely, Ramsey interferometry (RI) in atomic and molecular physics and quantum phase estimation (QPE) in quantum computing. We demonstrate that these canonical examples are instances of a larger class of phase estimation protocols, which we call reductive quantum phase estimation (RQPE) circuits. Here, we present an explicit algorithm that allows one to create an RQPE circuit. This circuit distinguishes an arbitrary set of phases with a smaller number of qubits and unitary applications, thereby solving a general class of quantum hypothesis testing to which RI and QPE belong. We further demonstrate a tradeoff between measurement precision and phase distinguishability, which allows one to tune the circuit to be optimal for a specific application. Published by the American Physical Society 2024
SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training) is a comprehensive data visualization and analysis application focused on working with COLTRIMS (COLd Target Recoil Ion Momentum Spectroscopy) data, which is used in atomic and molecular physics experiments. The application offers several powerful features: - Data uploading and processing capabilities for COLTRIMS files - Multiple visualization methods using UMAP (Uniform Manifold Approximation and Projection) for dimensionality reduction - Interactive selection of data points across multiple views - Feature engineering through various methods: - Manual feature selection from calculated physics parameters - Deep autoencoder for dimension reduction - Genetic programming for discovering meaningful features - Mutual information-based feature selection - Multiple clustering approaches (DBSCAN, KMeans, Agglomerative) - Quality metrics for evaluating clustering results - Export capabilities for selections and generated features
X-ray Free Electron Lasers (X-FELs) operate in a wide range of lasing configurations for a broad variety of scientific applications at ultrafast time-scales such as structural biology, materials science, and atomic and molecular physics. Shot-by-shot characterization of the X-FEL pulses is crucial for analysis of many experiments as well as tuning the X-FEL performance. However, for the weak pulses found in advanced configurations, e.g. those needed for coherent, two-pulse studies of quantum materials, there is no current method for reliably resolving pulse profiles. Here we show that a physics-based U-net model can reconstruct the individual pulse power profiles for sub-picosecond pulse separation without the need for simulations. Using experimental data from weak X-FEL pulse pairs, we demonstrate we can learn the pulse characteristics on a shot-by-shot basis when conventional methods fail.
As Lawrence Livermore National Laboratory’s (LLNL’s) Laboratory Directed Research and Development (LDRD) program enters its fifth decade of leading-edge research and development, its impact and importance have never been stronger. The program continues to advance strategic investments in pioneering science, technology, and engineering, ensuring LLNL will be ready to deliver on our mission as it evolves over the coming decades. Investing in LDRD research, and the people who perform this critical work, gives LLNL the ability to sustain our role as a leader in the Department of Energy and National Nuclear Security Administration enterprise. The LDRD program enables high-risk, high-payoff research that anticipates emerging threats and future mission needs. By nurturing the ingenuity of the Lab’s greatest asset, its people, LDRD funding advances not only our research but also grows and nurtures our workforce: engaging future innovators with student mentoring, challenging postdoctoral researchers to apply their skills to support national security, and strengthening the leadership skills of early career staff. This annual report documents how LDRD investments advance LLNL’s science, technology, and engineering across our mission space. To assess LDRD’s impact we track both short and long-term metrics such as peer-reviewed publications, number of students, or professional fellows. In addition to reviewing these metrics, I encourage you to delve deeper into the breadth of science and technology that illustrate the strategic value of this research portfolio. For instance, a recent exploratory research project used advanced manufacturing to construct miniaturized three-dimensional ion traps for a quantum computer with reduced quantum error rates to enable applications that address national security missions and support basic science. Another project has delved into studying detonation by examining deflagration to enhance the safety and security of the nuclear weapons stockpile. LDRD researchers are also deploying AI agents on two of the world’s most powerful supercomputers to automate and accelerate inertial confinement fusion experiments. Other teams are delivering more accurate optical constants to enable improved validation for aluminum to advance atomic and molecular physics models. LDRD-driven discoveries of how metals deform under extreme conditions strengthen our ability to model and design materials for demanding national security environments. National security challenges are increasingly complex and continuously evolving. LDRD focuses our most innovative science and technology on these challenges, ensuring the Laboratory is developing creative, forward-leaning solutions for our nation and the world. The following pages feature highlights of published scientific advances, patents, and honors that stem from LDRD investments. As you read this report, I hope you will understand how these investments position the Laboratory, and our partners, to meet the demands of the decades ahead.
An adaptive learning algorithm coupled with 3D momentum-based feedback is used to identify intense laser pulse shapes that control $H_{3}^{+}$ formation from ethane. Specifically, we controlled the ratio of D 2 H + to $D_{3}^{+}$ produced from the D 3 C-CH 3 isotopologue of ethane, which selects between trihydrogen cations formed from atoms on one or both sides of ethane. We are able to modify the D 2 H + :$D_{3}^{+}$ ratio by a factor of up to three. In addition, two-dimensional scans of linear chirp and third-order dispersion are conducted for a few fourth-order dispersion values while the D 2 H + and $D_{3}^{+}$ production rates are monitored. The optimized pulse is observed to influence the yield, kinetic energy release, and angular distribution of the D 2 H + ions while the $D_{3}^{+}$ ion dynamics remain relatively stable. We subsequently conducted COLTRIMS experiments on C 2 D 6 to complement the velocity map imaging data obtained during the control experiments and measured the branching ratio of two-body double ionization. Two-body $D_{3}^{+}$ + $C_{2}D_{3}^{+}$ is the dominant final channel containing $D_{3}^{+}$ ions, although the three-body D + $D_{3}^{+}$ + $C_{2}D_{2}^{+}$ final state is also observed.
Research activity related to the science of materials is described. The following areas are included: elastic and thermal properties of composite materials, acoustic waves and devices, amorphous materials, crystal structure, synthesis of metal-metal bonds, interactions of solids with solutions, electrochemistry, fatigue damage, superconductivity and molecular physics and phase transition kinetics.
Interface between atomic and molecular physics and atmospheric physics; middle atmospheric research; and atmospheric exchange are discussed. Also included are proposals for research from 1982 through 1985, priorities, and available support.
Dust formation around cool giant and supergiant stars is examined in terms of grain formulation. Optical properties of small clusters, molecular physics of cluster nucleation and growth, circumstellar mass flows, and their application to alpha Ori are discussed.
The conference presents papers on the Milky Way as a galaxy; observations of components of the interstellar medium; interstellar magnetic properties; interstellar processes on a galactic scale; dynamical processes in interstellar clouds; interstellar dust grains; interstellar chemical processes; and heating, cooling, and radiative processes. Attention is given to H2 in the Galaxy, hot interstellar gas in the Galactic disk and halo, interstellar magnetic fields, cloud formation and destruction, theoretical approaches to interstellar turbulence, and infrared absorption and emission characteristics of interstellar PAHs. Other topics include gas phase chemical processes in molecular clouds, the chemical evolution of galaxies, and the atomic and molecular physics of interstellar heating and cooling.
To assist peak assignment in ion mobility spectrometry it is important to have quality reference data. The reference collection should be stored in a database system which is capable of being searched using spectral or substance information. We propose to build such a database customized for ion mobility spectra. To start off with it is important to quickly reach a critical mass of data in the collection. We wish to obtain as many spectra combined with their IMS parameters as possible. Spectra suppliers will be rewarded for their participation with access to the database. To make the data exchange between users and system administration possible, it is important to define a file format specially made for the requirements of ion mobility spectra. The format should be computer readable and flexible enough for extensive comments to be included. In this document we propose a data exchange format, and we would like you to give comments on it. For the international data exchange it is important, to have a standard data exchange format. We propose to base the definition of this format on the JCAMP-DX protocol, which was developed for the exchange of infrared spectra. This standard made by the Joint Committee on Atomic and Molecular Physical Data is of a flexible design. The aim of this paper is to adopt JCAMP-DX to the special requirements of ion mobility spectra.
To assist current discussion in the field of ion mobility spectrometry, at the Institut fur Spectrochemie und angewandte Spektroskopie, Dortmund, start with 4th of December, 1994 work of an FTP-Server, available for all research groups at univerisities, institutes and research worker in industry. We support the exchange, interpretation, and database-search of ion mobility spectra through data format JCAMP-DS (Joint Committee on Atomic and Molecular Physical Data) as well as literature retrieval, pre-print, notice, and discussion board. We describe in general lines the entrance conditions, local addresses, and main code words. For further details, a monthly news report will be prepared for all common users. Internet email address for subscribing is included in document.
At high altitudes and velocities equal to or greater than the geosynchronous return velocity (10 kilometers per second), the shock layer of a hypersonic flight will be in thermochemical nonequilibrium and partially ionized. The amount of ionization is determined by the velocity. For a trans atmospheric flight of 10 kilometers per second and at an altitude of 80 kilometers, a maximum of 1% ionization is expected. At a velocity of 12 - 17 kilometer per second, such as a Mars return mission, up to 30% of the atoms and molecules in the flow field will be ionized. Under those circumstances, electrons play an important role in determining the internal states of atoms and molecules in the flow field and hence the amount of radiative heat load and the distance it takes for the flow field to re-establish equilibrium. Electron collisions provide an effective means of transferring energy even when the electron number density is as low as 1%. Because the mass of an electron is 12,760 times smaller than the reduced mass of N2, its average speed, and hence its average collision frequency, is more than 100 times larger. Even in the slightly ionized regime with only 1% electrons, the frequency of electron-molecule collisions is equal to or larger than that of molecule-molecule collisions, an important consideration in the low density part of the atmosphere. Three electron-molecule collision processes relevant to hypersonic flows will be considered: (1) vibrational excitation/de-excitation of a diatomic molecule by electron impact, (2) electronic excitation/de-excitation, and (3) dissociative recombination in electron-diatomic ion collisions. A review of available data, both theory and experiment, will be given. Particular attention will be paid to tailoring the molecular physics to the condition of hypersonic flows. For example, the high rotational temperatures in a hypersonic flow field means that most experimental data carried out under room temperatures are not applicable. Also, the average electron temperature is expected to be between 10,000 and 20,000 K. Thus only data for low energy electrons are relevant to the model.
Computational study of electron-molecule collisions not only complements experimental measurements, but can also be used to investigate processes not readily accessible experimentally. A number of ab initio computational methods are available for these types of calculations. Here we describe a recently developed technique, the finite element Z-matrix method, Analogous to the R-matrix, method, it partitions the space into regions and employs real matrix elements. However, unlike the implementation of the R-matrix method commonly used in atomic and molecular physics, the Z-matrix method is fully variational. In the present implementation, a mixed basis of finite elements and Gaussians is used to represent the continuum electron, thus offering full flexibility without imposing fixed boundary conditions. Numerical examples include the electron-impact dissociation of N2 via the metastable A3Su+ state, a process which may be important in the lower thermosphere, and the dissociation of the CF radical, a process of interest to plasma etching. To understand the dissociation pathways, large scale quantum chemical calculations have been carried out for all target states which dissociate to the lowest five limits in the case of N2, and to the lowest two limits in the case of CF. For N2, the structural calculations clearly show the preference for predissociation if the initial state is the ground X1 Sg+ state, but direct dissociation appears to be preferable if the initial state is the A3Su+ state. Multi-configuration SCF target functions are used in the collisional calculation.