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At least 217 records · Page 12

Defense mechanism for non-volatile memory based main memory

A method includes receiving a write request for writing incoming data to a target memory line and, in response to the write request, comparing the incoming data with existing data in the target memory line to determine a number of a first type of state transition. The method further includes, in response to determining that the number of the first type of state transition for the write request exceeds a threshold, prior to writing the incoming data to the target memory line, storing adjacent data from each of a set of memory lines adjacent to the target memory line, and after writing the incoming data to the target memory line, writing the stored data to the set of adjacent memory lines.

SeyedzadehDelcheh, SeyedMohammad↗

Inverse Reinforcement Learning based Bayesian Goal Inference Method for Early Nuclear Proliferation Detection

Traditional methods for detection of nuclear proliferation indicators are usually applied after nuclear proliferation has already occurred. There is a need to advance these methods to perform early detection of nuclear proliferation indicators. In this project, we formulated an early detection problem as a sequential, decision-making, goal inference problem based on research publications of authors, to determine whether it is possible to infer whether an author will publish on a research activity before it has occurred. To develop and test our approach, we selected a civil nuclear activity for our case study. We constructed a state-action-state transition graph from publications of authors associated with the activity and the co-authors of their publications, using titles, abstracts, and author publication sequences. We then used inverse reinforcement learning to model the goal-directed behavior of authors in trajectories that terminate at selected goal states. Using a Bayesian formulation, we computed the probability that authors would reach each selected state from partially observed trajectories of their state transitions in their research topic space. The state with the highest probability was selected as the most probable goal state. Based on our results, we found that 60% of the times we can infer the correct goal state early; sometimes the inference is either delayed, or multiple states could be inferred as goal states. Overall, our results show that it is possible to perform early detection of research activities of authors in a nuclear technology area. Further research is necessary to establish a more accurate understanding of how topic modeling, topic space grid discretization, and the extent of overlap among trajectories of different goal states, affect the goal inference results. The methods developed in this work may be used to enhance data-driven methods for early detection of nuclear proliferation indicators.

97 MATHEMATICS AND COMPUTING↗

Rate Enhancement of Acid-Catalyzed Alcohol Dehydration by Supramolecular Organic Capsules

The presence of a (sub)nanometric environment has been demonstrated to enhance the rate of homogeneous acid-catalyzed reactions. Conventionally, such catalysts are constructed by directly embedding a catalytically active acid site into the structure of a porous material, linking the acid properties with the properties of the embedding solid. Here, a holoenzyme mimicking approach was used, in which a self-assembled hexameric resorcinarene capsule (1.4 nm 3 cavity) acts like an apoenzyme that transforms into a catalytically active site by hosting hydrated HCl as a cofactor. This capsule binds the hydronium ion together with cyclohexanol (CyOH) and catalyzes the dehydration to cyclohexene with enhanced rates that are 2 orders of magnitude higher than those in the unconstrained environment. Kinetic analysis shows that cyclohexanol dehydration proceeds via an E2 mechanism on hydrated HCl in the unconstrained environment, while the constrained environment of the active capsule induces the stabilization of an ionic intermediate, allowing an E1 mechanism to dominate. By comparison with the reaction in zeolite environments, we show that the direct chemical environment of the capsule or a zeolite wall exerts only a minor direct influence. The volume constraint increases the reaction rate by inducing a larger activation entropy, indicating the stabilization of a later transition state in the E1 mechanism, as well as a higher reaction space of the carbenium ion constituting the transition state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonadiabatic Molecular Dynamics Study of the Relaxation Pathways of Photoexcited Cyclooctatetraene

In the current study, we present nonadiabatic (NAMD) and adiabatic molecular dynamics simulations of the transition-state dynamics of photoexcited cyclooctatetraene (COT). The equilibrium-state structure and absorption spectra are analyzed using the semiempirical Austin Model 1 potential. The NAMD simulations are obtained by a surface-hopping algorithm. We analyzed in detail an active excited to ground state relaxation pathway accompanied by an S 2 /S 3 (D 2d ) → S 1 (D 8h ) → S o (D 4h ) → S o (D 2d ) double-bond shifting mechanism. The simulated excitation lifetime is in good agreement with experiment. The first excited singlet state S1 plays a crucial role in the photochemistry. Here, the obtained critical molecular conformations, energy barrier, and transition-state lifetime results will provide a basis for further investigations of the bond-order inversion and photoswitching process of COT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Velocity Absorption Features in FUSE Spectra of Eta Carinae

Numerous broad (200 to 1000 km/sec) features in the FUSE spectrum (905-1187 A) of eta Carinae are identified as absorption by a forest of high-velocity narrow lines formed in the expanding circumstellar envelope. These features were previously thought to be P-Cygni lines arising in the wind of the central star. The features span a heliocentric velocity range of -140 to -580 km/sec and are seen prominently in low-ionization ground-state transitions (e.g. N I 1134-35, Fe II 1145-42, 1133, 1127- 22, P II 1153, C I 1158) in addition to C III] 1176 A. The high-velocity components of the FUSE transitions have depths about 50% below the continuum. The identifications are consistent with the complex velocity structures seen in ground- and excited-state transitions of Mg I, Mg 11, Fe II, V II, etc observed in STIS/E230H spectra. The origin of other broad features of similar width and depth in the FUSE spectrum, but without low-velocity ISM absorption, are unidentified. However, they are suspected of being absorption of singly-ionized iron-peak elements (e.g. Fe II, V II, Cr II) out of excited levels 1,000 to 20,000 cmE-l above the ground state. The high-velocity features seen in Fe II 1145 are also present in Fe II 1608 (STIS/E140M), but are highly saturated in the latter. Since these transitions have nearly identical log (flambda) (1.998 vs. 2.080), the differences in the profiles are attributable to the different aperture sizes used (30 x 30 arcsec for FUSE, 0.2 x 0.2 arcsec for STIS/E140M). The high-velocity gas appears to be very patchy or has a small covering factor near the central star. Eta Carinae has been observed several times by FUSE over the past three years. The FUSE flux levels and spectral features in eta Car are essentially unchanged over the 2000 March to June 2002 period, establishing a baseline far-UV spectrum in advance of the predicted spectroscopic minimum in 2003.

Sonneborn, G.↗

A Molecular View of Methane Activation on Ni(111) through Enhanced Sampling and Machine Learning

A combination of machine learned interatomic potentials (MLIPs) and enhanced sampling simulations is used to investigate the activation of methane on a Ni(111) surface. The work entails the development and iterative refinement of MLIPs, initially trained on a dataset constructed via ab initio molecular dynamics (AIMD) simulations, supplemented by adaptive biasing forces, to enrich the sampling of catalytically relevant configurations. Our results reveal that by incorporating collective variables that capture the behavior of the reactant molecule, as well as additional frames that describe the dynamic response of the catalytic surface, it is possible to enhance considerably the accuracy of predicted energies and forces. By employing enhanced sampling schemes in the refinement of the MLIP, we systematically explore the potential energy surface, leading to a refined MLIP capable of predicting DFT-level energies and forces and replicating key geometric characteristics of the catalytic system. The resulting free energy landscapes at several temperatures provide a detailed view of the thermodynamics and dynamics of methane activation. Specifically, as methane approaches and dissociates on the catalytic surface, the process involves the dynamic interplay of CH 4 and the Ni catalyst that includes both enthalpic and entropic contributions. The progression towards the transition state involves an CH 4 moiety that is increasingly restrained in its ability to rotate or translate, while the stage following the transition state is characterized by a notable rise of the Ni atom that interacts with the cleaved C–H bond. Furthermore, this leads to an increase in the mobility of the adsorbed species, a feature that becomes more pronounced at higher temperatures.

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Tunable quantum logic gate on photonic qubits with a ladder emitter

We describe how a ladder emitter can implement a tunable quantum logic gate on photonic qubits encoded in the frequency basis. The ground-to-first excited state of the ladder emitter interacts with the control photon, and the first-to-second excited state transition interacts with the target photon. By controlling the relative detuning between the target photon and the first-to-second excited state transition of the ladder emitter, we enable any controlled-phase operation from 0 to π. We derive analytical formulas for the performance of the gate through the S-matrix formalism as well as describe the mechanism intuitively. This gate is deterministic, does not utilize any active control, and needs only a single ladder emitter, enabling low-footprint and more efficient decomposition of quantum circuits, especially the quantum Fourier transform. We suggest multiple potential systems for physical realization of our proposal, such as lanthanide ions embedded in Purcell-enhanced cavities. We expect these results to motivate further interest in photonic quantum information processing with designer emitters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Toward Rational Design of Supported Vanadia Catalysts of Lignin Conversion to Phenol

In sustainable chemical engineering, catalytic upgrading of lignocellulosic biomass has recently gained attention for producing renewable platform chemicals. To achieve maximal biomass utilization, upgrading the underutilized lignin components is essential. Among various catalysts for lignin upgrading, supported vanadia (V2O5) catalysts are promising because of their cost-effectiveness and tunability of either dopant metals or catalyst supports. Here, computational studies are conducted to derive rational design guidelines of supported V2O5 catalysts for accomplishing the high catalytic activity of lignin upgrading to phenol, a key compound for producing bioplastics and biofuel blendstocks. Guaiacol was used as the model compound since it comprises the highest portion of depolymerized lignin. Computational mechanistic studies for the catalytic guaiacol conversion to phenol were performed for the V2O5 catalysts on Titania (TiO2) and silica (SiO2) to explain higher experimental phenol yields on V2O5/SiO2 than V2O5/TiO2. The hydrogen migration from the methoxy group to the aryl ring was identified as a rate-determining step, and the overall activation energies on the two catalysts were compared. A structural analysis was carried out for the catalysts and rate-determining transition states to gain further insights from mechanistic studies. It was concluded that the tilt angle of the aryl group in the hydrogen migration transition state is a key descriptor determining the catalytic activity of phenol formation. These features correlate well with activation energies and experimental phenol yields, indicating that they provide design guidelines for supported metal catalysts for lignin upgrading before experiments.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

Four-body trajectory optimization

A comprehensive optimization program has been developed for computing fuel-optimal trajectories between the earth and a point in the sun-earth-moon system. It presents methods for generating fuel optimal two-impulse trajectories which may originate at the earth or a point in space and fuel optimal three-impulse trajectories between two points in space. The extrapolation of the state vector and the computation of the state transition matrix are accomplished by the Stumpff-Weiss method. The cost and constraint gradients are computed analytically in terms of the terminal state and the state transition matrix. The 4-body Lambert problem is solved by using the Newton-Raphson method. An accelerated gradient projection method is used to optimize a 2-impulse trajectory with terminal constraint. The Davidon's Variance Method is used both in the accelerated gradient projection method and the outer loop of a 3-impulse trajectory optimization problem.

Pu, C. L.↗

Supervised learning and the finite-temperature string method for computing committor functions and reaction rates

A central object in the computational studies of rare events is the committor function. Though costly to compute, the committor function encodes complete mechanistic information of the processes involving rare events, including reaction rates and transition-state ensembles. Under the framework of transition path theory, Rotskoff et al. [Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, Proceedings of Machine Learning Research (PLMR, 2022), Vol. 145, pp. 757–780] proposes an algorithm where a feedback loop couples a neural network that models the committor function with importance sampling, mainly umbrella sampling, which collects data needed for adaptive training. Here, in this work, we show additional modifications are needed to improve the accuracy of the algorithm. The first modification adds elements of supervised learning, which allows the neural network to improve its prediction by fitting to sample-mean estimates of committor values obtained from short molecular dynamics trajectories. The second modification replaces the committor-based umbrella sampling with the finite-temperature string (FTS) method, which enables homogeneous sampling in regions where transition pathways are located. We test our modifications on low-dimensional systems with non-convex potential energy where reference solutions can be found via analytical or finite element methods, and show how combining supervised learning and the FTS method yields accurate computation of committor functions and reaction rates. We also provide an error analysis for algorithms that use the FTS method, using which reaction rates can be accurately estimated during training with a small number of samples. The methods are then applied to a molecular system in which no reference solution is known, where accurate computations of committor functions and reaction rates can still be obtained.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the Long-Term Spectral Variability of Cygnus X-1 with Burst and Transient Source Experiment and All-Sky Monitor Observations

We present a comprehensive analysis of all observations of Cyg X-1 by the Compton Gamma Ray Observatory Burst and Transient Source Experiment (BATSE; 20-300 keV) and by the Rossi X-Ray Timing Explorer all-sky monitor (ASM; 1.5-12 keV) until 2002 June, including approximately 1200 days of simultaneous data. We find a number of correlations between fluxes and hardnesses in different energy bands. In the hard (low) spectral state, there is a negative correlation between the ASM 1.5-12 keV flux and the hardness at any energy. In the soft (high) spectral state, the ASM flux is positively correlated with the ASM hardness but uncorrelated with the BATSE hardness. In both spectral states, the BATSE hardness correlates with the flux above 100 keV, while it shows no correlation with the 20-100 keV flux. At the same time, there is clear correlation between the BATSE fluxes below and above 100 keV. In the hard state, most of the variability can be explained by softening the overall spectrum with a pivot at approximately 50 keV. There is also another, independent variability pattern of lower amplitude where the spectral shape does not change when the luminosity changes. In the soft state, the variability is mostly caused by a variable hard (Comptonized) spectral component of a constant shape superposed on a constant soft blackbody component. These variability patterns are in agreement with the dependencies of the rms variability on the photon energy in the two states. We also study in detail recent soft states from late 2000 until 2002. The last of them has lasted thus far for more than 200 days. Their spectra are generally harder in the 1.5-5 keV band and similar or softer in the 3-12 keV band than the spectra of the 1996 soft state, whereas the rms variability is stronger in all the ASM bands. On the other hand, the 1994 soft state transition observed by BATSE appears very similar to the 1996 one. We interpret the variability patterns in terms of theoretical Comptonization models. In the hard state, the variability appears to be driven mostly by changing flux in seed photons Comptonized in a hot thermal plasma cloud with an approximately constant power supply. In the soft state, the variability is consistent with flares of hybrid, thermal/nonthermal, plasma with variable power above a stable cold disk. The spectral and timing differences between the 1996 and 2000-2002 soft states are explained by a decrease of the color disk temperature. Also, on the basis of broadband pointed observations simultaneous with those of the ASM and BATSE, we find the intrinsic bolometric luminosity increases by a factor of approximately 3-4 from the hard state to the soft one, which supports models of the state transition based on a change of the accretion rate.

Zdziarski, Andrzej A.↗

Vibrational control of the reaction pathway in the H + CHD 3 → H 2 + CD 3 reaction

An accurate full-dimensional quantum state-to-state simulation of the six-atom title reaction based on first-principles theory is reported. Counterintuitive effects are found: Increasing the energy in the reactant’s CD 3 umbrella vibration reduces the energy in the corresponding product vibration. An in-depth analysis reveals the crucial role of the effective dynamical transition state: Its geometry is controlled by the vibrational states of the reactants and subsequently controls the quantum state distribution of the products. This finding enables generalizing the concept of transition state control of chemical reactions to the quantum state–specific level.

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Predictor laws for pictorial flight displays

Two predictor laws are formulated and analyzed: (1) a circular path law based on constant accelerations perpendicular to the path and (2) a predictor law based on state transition matrix computations. It is shown that for both methods the predictor provides the essential lead zeros for the path-following task. However, in contrast to the circular path law, the state transition matrix law furnishes the system with additional zeros that entirely cancel out the higher-frequency poles of the vehicle dynamics. On the other hand, the circular path law yields a zero steady-state error in following a curved trajectory with a constant radius. A combined predictor law is suggested that utilizes the advantages of both methods. A simple analysis shows that the optimal prediction time mainly depends on the level of precision required in the path-following task, and guidelines for determining the optimal prediction time are given.

Grunwald, A. J.↗

Oxidation Dynamics of Supported Catalytic Cu Clusters: Coupling to Fluxionality

Copper oxide nanoclusters have a wide range of catalytic applications, such as the selective oxidation of hydrocarbons. O 2 binding to the catalyst, activation, and release upon reagent oxidation are key events in these catalytic chemistries. Furthermore, these events are expected to be accompanied by significant structural changes of the Cu clusters, because O atoms integrate into the cluster, rather than bind to its surface. Topping the complexity of the problem, partially oxidized Cu clusters are known to exhibit strong fluxionality and feature diverse and interconverting structures and oxygen contents in conditions of oxidative dehydrogenation (ODH). Hence, a significant dynamic coupling between the “hot” O 2 molecule impacting the cluster at reaction temperatures and the cluster fluxionality can be expected. In this work, we focus on the dynamics of dioxygen integration into a partially oxidized Cu cluster supported on hydroxylated amorphous alumina–a system recently reported to be an exceptionally selective catalyst for cyclohexane ODH with very little CO produced, whose mechanistic underpinnings are of utmost interest. The statistics over a swarm of adsorption and scattering trajectories where O 2 hits various sites on the cluster at reaction temperature shows that the O 2 binding does not only follow the minimal energy paths. O 2 also rarely integrates into the cluster in a single step and instead first binds to a single Cu atom via either an η 1 -O 2 or an η 2 -O 2 mode. Surprisingly, this step often has a higher barrier than the subsequent O 2 integration and dissociation, which in turn take multiple steps and complete the oxidation process. Dynamic trajectories starting from the key transition state of integration of the adsorbed O 2 can also lead to different intermediate structures during or right after the dissociation, due to the energy released from the transition state and the thermal intracluster effects. From these activated O 2 chemisorbed structures, O 2 dissociation occurs with moderate barriers (~0.5 eV), producing multiple final oxidized Cu 4 O 4 states. Hence, a diversity of reaction profiles for the attack of supported Cu cluster by O 2 emerges due to the dynamic effects, with implications for mechanisms, kinetic models, and catalyst design principles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Curing the Divergence in Time-Dependent Density Functional Quadratic Response Theory

While time-dependent density functional theory has emerged as a method of choice for computing electronic spectra and response of molecules and materials, its reliability is hindered by the adiabatic approximation that is commonly made. In this work, we address one problematic aspect that arises from this approximation: an incorrect pole structure in the quadratic response function, leading to unphysical divergences in excited state-to-state transition probabilities and hyperpolarizabilties. We find the form of the exact quadratic response kernel and derive a practical and accurate approximation that cures the divergence. Here, we demonstrate our results on excited state-to-state transition probabilities of a model system and of the LiH molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generative AI models for learning flow maps of stochastic dynamical systems in bounded domains

Simulating stochastic differential equations (SDEs) in bounded domains, presents significant computational challenges due to particle exit phenomena, which requires accurate modeling of interior stochastic dynamics and boundary interactions. Despite the success of machine learning-based methods in learning SDEs, existing learning methods are not applicable to SDEs in bounded domains because they cannot accurately capture the particle exit dynamics. We present a unified hybrid data-driven approach that combines a conditional diffusion model with an exit prediction neural network to capture both interior stochastic dynamics and boundary exit phenomena. Our ML model consists of two major components: a neural network that learns exit probabilities using binary cross-entropy loss with rigorous convergence guarantees, and a training-free diffusion model that generates state transitions for non-exiting particles using closed-form score functions. The two components are integrated through a probabilistic sampling algorithm that determines particle exit at each time step and generates appropriate state transitions. Here, the performance of the proposed approach is demonstrated via three test cases: a one-dimensional simplified problem for theoretical verification, a two-dimensional advection-diffusion problem in a bounded domain, and a three-dimensional problem of interest to magnetically confined fusion plasmas.

Bounded domains↗

Rate constants and temperature dependences for the reactions of hydroxyl radical with several halogenated methanes, ethanes, and propanes by relative rate measurements

Rate constants of 15 OH reactions with halogen-substituted alkanes, C1 to C3, were studied using a relative rate technique in the temperature range 283-403 K. Compounds studied were CHF2Cl (22), CHF2Br (22B), CH3F (41), CH2F2 (32), CHF3 (23), CHClFCCl2F (122a), CHCl2CF3 (123), CHClFCF3 (124), CH3CF3 (143a), CH3CH2F (161), CF3CHFCF3 (227ea), CF3CH2CF3 (236fa), CF3CHFCHF2 (236ea), and CHF2CF2CH2F (245ca). Using CH4, CH3CCl3, CF3CF2H, and C2H6 as primary reference standards (JPL 92-20 rate constants), absolute rate constants are derived. Results are in good agreement with previous experimental results for six of the compounds studied, including CHF2Cl, CHF2Br, CH2F2, CH3CF3, CHFClCFCl2, and CF3CHFCF3. For the remainder the relative rate constants are lower than those derived from experiments in which OH loss was used to measure the reaction rate. Comparisons of the derived Arrhenius A factors with previous literature transition-state calculations show order of magnitude agreement in most cases. However, the experimental A factors show a much closer proportionality to the number of H atoms in the molecule than is evident from the transition state calculations. For most of the compounds studied, an A factor of (8 +/- 3)E-13 cm(exp 3)/(molecule s) per C-H bond is observed. A new measurement of the ratio k(CH3CCl3)/k(CH4) is reported that is in good agreement with previous data.

Hsu, K.-J.↗

Controlling P–C/C–H Bond Cleavage in Nickel Bis(diphosphine) Complexes: Reactivity Scope, Mechanism, and Computations

The synthesis of heteroleptic [Ni(P 2 N 2 )(diphosphine)][BF 4 ] 2 complexes and the cleavage of P–C and C–H bonds of the P 2 N 2 ligand in those complexes are reported here. The products are five-coordinate complexes in which Ni–C and P–H bonds have formed to give a cyclic moiety containing Ni–CH$=$NR 2 . The reactivity of [Ni(P 2 N 2 )(diphosphine)][BF 4 ] 2 complexes is influenced by the rigidity of the diphosphine, the steric effect of the substituents, and length of the carbon linker of the diphosphine ligands. Diphosphine ligands bearing a rigid backbone (e.g., dmpbz, 1,2-bis(dimethylphosphino)benzene) or aromatic substituents (e.g., dppe, 1,2-bis(diphenylphosphino)ethane) react with [Ni(P t Bu 2 N Bn 2 )(CH 3 CN) 2 ][BF 4 ] 2 to give P–C/C–H bond cleavage products. Both [Ni(P t Bu 2 N Bn 2 )(dmpe)(MeCN)][BF 4 ] 2 and [Ni(P t Bu 2 N Bn 2 )(dmpm)(MeCN)][BF 4 ] 2 (dmpm = 1,2-bis(dimethylylphosphino)methane) were prepared by the reaction of [Ni(P t Bu 2 N Bn 2 )(CH 3 CN) 2 ][BF 4 ] 2 with the corresponding diphosphine ligands. [Ni(P t Bu 2 N Bn 2 )(dmpe)(MeCN)][BF 4 ] 2 readily undergoes P–C/C–H bond cleavage in nitromethane. In sharp contrast, [Ni(P t Bu 2 N Bn 2 )(dmpm)][BF 4 ] 2 is stabilized by dmpm, a diphosphine with small bite angle, and does not show P–C/C–H bond cleavage reactivity. Computational results show that for complexes bearing less bulky diphosphine ligands, such as dmpm, the barriers for the rate-determining transition states are in some examples higher than 30 kcal/mol with the M06 functional, higher than those for complexes bearing more rigid or more bulky ligands, consistent with experimental studies. The calculated barriers for the first transition state correlated with increased values of the dihedral angle formed by the two NiP 2 planes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗