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At least 415 records · Page 23

One dimensional heavy ion beam transport: Energy independent model

Attempts are made to model the transport problem for heavy ion beams in various targets, employing the current level of understanding of the physics of high-charge and energy (HZE) particle interaction with matter are made. An energy independent transport model, with the most simplified assumptions and proper parameters is presented. The first and essential assumption in this case (energy independent transport) is the high energy characterization of the incident beam. The energy independent equation is solved and application is made to high energy neon (NE-20) and iron (FE-56) beams in water. The numerical solutions is given and compared to a numerical solution to determine the accuracy of the model. The lower limit energy for neon and iron to be high energy beams is calculated due to Barkas and Burger theory by LBLFRG computer program. The calculated values in the density range of interest (50 g/sq cm) of water are: 833.43 MeV/nuc for neon and 1597.68 MeV/nuc for iron. The analytical solutions of the energy independent transport equation gives the flux of different collision terms. The fluxes of individual collision terms are given and the total fluxes are shown in graphs relative to different thicknesses of water. The values for fluxes are calculated by the ANASTP computer code.

Farhat, Hamidullah↗

On the controllability and control law design for an orbiting large flexible antenna system

The controllability and control law synthesis based on a finite element model of the Hoop/Column orbiting antenna system is considered. Graph theoretic techniques are employed to analyze the controllability of the system for posible proposed actuator arrangements which include torquers and point actuators along the mast and a single actuator placed on the hoop assembly. Once controllability is established for a given combination of number and location of actuators, the synthesis of control laws is based on an application of the linear regulator theory and also pole placement techniques. In general, surface torsion and feed mast torsion are among modes having the longest time constants. System transient performance is noticeably degraded when the hoop actuator is not included.

Bainum, P. M.↗

Dirac traces and the Tutte polynomial

Perturbative calculations involving fermion loops in quantum field theories require tracing over Dirac matrices. A simple way to regulate the divergences that generically appear in these calculations is dimensional regularisation, which has the consequence of replacing 4-dimensional Dirac matrices with d-dimensional counterparts for arbitrary complex values of d. In this work, a connection between traces of d-dimensional Dirac matrices and computations of the Tutte polynomial of associated graphs is proven. The time complexity of computing Dirac traces is analysed by this connection, and improvements to algorithms for computing Dirac traces are proposed.

Renormalization and Regularization↗

Development and Testing of Pulse Guns for Combustion Instability Testing

To test liquid rocket engines (LREs) for combustion instabilities, devices such as bombs are often used to create pressure wave disturbances. Bombs, while effective, are inherently dangerous, expensive, and difficult to procure. Over the years, pulse guns have been used as a safer and more cost-effective way to generate controlled pressure disturbances in engine chambers. In anticipation of the need for stability testing of prototype LREs at NASA Marshall Space Flight Center (MSFC), a set of pulse guns have been designed, fabricated, tested, and characterized. The pulse gun program is funded by the RS-25 Engine Program managed out of MSFC and funded by NASA’s Space Launch System (SLS) through the MSFC Liquid Engines Office (LEO). A pulse gun is a simple device – like a traditional gun, it has a breech and barrel section. However, unlike a traditional gun, there is no bullet, as the purpose of the pulse gun is strictly to fire a high pressure pulse. Instead of a firing pin and primer that would normally be used in a traditional gun, an initiator is used to activate the gun powder. The initiator is a highly reliable pyrotechnic initiator. For this study, clone versions of the NASA Standard Initiator (NSI) were used. The initiator is used to ignite a pre-measured amount of gun powder loaded into the breech. When the pressure of the burnt gun powder exceeds the set point of a downstream burst disk, the disk ruptures, allowing the high pressure pulse to travel downstream through the barrel section. A ballistic pressure transducer located in the breech section is used to measure the short duration, high pressure pulse. Some configurations of the pulse gun have barrel sections that include one or more additional ballistic pressure transducers. These additional pressure measurements help track the degradation and damping of the pulse as it travels out of the barrel section. The measurements may also be used to determine the velocity of pulse. The objective of this paper is to present the different variants of this newly-developed pulse gun and characterize performance over a range of parameters. The parameters include breech diameter, barrel length, amount of gun powder used, the way the gun powder is packed, and the pressure setting of the burst disk. There are a total of six pulse guns: three with the 0.25 inch breech and three different length barrels, and three with the 0.40 inch breech and three different length barrels. For both breech sizes, the associated barrels are referred to as standard, one-port, and two-port barrels. The standard barrel has no instrumentation and is likely the barrel that will be used for engine stability testing. The one- and two-port barrels were designed specifically for pulse gun component testing to allow measurements of the magnitude and timing of the high pressure pulse as it makes its way through the pulse gun. The burst disks tested were commercially-available burst disks designed to rupture at 8,000, 16,000, and 24,000 psid. Testing was accomplished by firing the pulse gun into a test chamber pressurized with nitrogen at about 2300 psig. A total of four Model 113B23 High frequency ICP® pressure sensors (10k psi) were mounted in the test chamber, in the same plane as the pulse gun. Two of the sensors had “trimmed” adapters, and two did not. Given the symmetrical configuration of the sensors within the test chamber, different amplitudes of pressure measurements are attributed to the use of trimmed versus untrimmed adapters. The untrimmed adapters, with their narrower passages, tended to amplify the pressure amplitudes by as much as 50%. In total, 41 pulse gun tests have been conducted.Data are still being analyzed, but some trends are apparent. For example, measurements taken within the pulse gun are shown in Figures 3 and 4 for Hot-fires (HFs) # 11 and 39, respectively. Both tests were identical in that the 0.40 inch ID breech, two-port barrel, 8,000 psid burst disk, and same amount of gunpowder (6.639 grains for HF# 11, and 6.576 grains for HF# 39) were used, and the back pressure in the nitrogen test chamber was ~2300 psig. Despite keeping all these variables constant, the results from these two tests look quite different. For both tests, the first pressure peak shown in the P2111 trace within the breech is the firing of the initiator. The second peak and any subsequent peaks are from the combustion of the gunpowder. It should be noted that because the sensors are dynamic, the ~2300 psig baseline static pressure is not shown in the figures. For HF# 11, the burst disk clearly ruptured in a little over 0.1 ms from the time the initiator was fired. This is evident from the abrupt rise in pressure for P2112 followed by another abrupt rise in pressure for P2113. The sensors track the movement of the high pressure pulse through the pulse gun. For HF# 39, however, there was nearly 1 ms delay between the initiator firing and the burst disk rupturing. The only difference between these two tests was the way in which the gunpowder was packed within the breech. For HF# 11, the gunpowder was poured directly into the breech, atop the initiator, and held in place with a vegetable fiber wad appropriately sized for the barrel diameter. Once in place, the wad firmly held the gunpowder in place. For HF# 39, the gunpowder was rolled within cigarette paper with the ends of the paper twisted. The rolled gunpowder was gently pushed down into the breech, toward the initiator, and no wad was used. This method of loading the gunpowder consistently produced longer delays in the rupture of the burst disk, presumably because there was a steady, fuller burning of the gunpowder. The burst disk was rated for 8,000 psid, which means that the burst disk should not have opened until the pressure in the breech reached ~10,300 since there was ~2300 psig back pressure in the test chamber. In the case of HF# 11, the breech pressure only reached roughly 4200 psi before there was leakage either through or past the burst disk, but for HF#39, the breech pressure reached 10,600 psi prior to the burst disk opening. The temperature of the burst disk is certainly a factor in determining when the burst disk will rupture. A sharp rise in the burst disk temperature could weaken it and cause it to stray from the designed set point burst pressure. The burst disks are manufactured of Inconel to try to reduce their sensitivity to temperature, but how the burst disks perform above 900°F is not documented. All burst disks were engineered and tested by the manufacturer for ambient temperature conditions. One theory for why rolling the gunpowder in cigarette paper may produce better results is related to a more controlled temperature environment. The cigarette paper may act as a sheath that protects the burst disk from excessive temperatures during the rapid buildup of pressure in the breech. The ultimate benefit of not breeching the burst disk prematurely is shown in Figures 5 and 6, which graphs the resultant pressure pulse produced in the test chamber. For HF #11, the peak pressure on the P2123 trimmed adapter is about 270 psi, while for HF# 39 it is 343 psi, which is about 1.27 times greater in magnitude. In either case, the pressure pulse is ~20 μs in width once it reaches the test chamber. Another pressure rise about 100 μs later can be seen on the sensors located across from the pulse gun port, P2124 and P2121. These pressures are lower due to attenuation of the pressure wave as it moves across the test chamber. After the wave encounters the wall, it reflects back and forth within the chamber until it completely dissipates.

Pulse Gun↗

The REH theory of protein and nucleic acid divergence - A retrospective update

The random evolutionary hits (REH) theory of evolutionary divergence, originally proposed in 1972, is restated with attention to certain aspects of the theory that have caused confusion. The theory assumes that natural selection and stochastic processes interact and that natural selection restricts those codon sites which may fix mutations. The predicted total number of fixed nucleotide replacements agrees with data for cytochrome c, a-hemoglobin, beta-hemoglobin, and myoglobin. The restatement analyzes the magnitude of possible sources of errors and simplifies calculational methodology by supplying polynomial expressions to replace tables and graphs.

Holmquist, R.↗

Exact representations of many-body interactions with restricted-Boltzmann-machine neural networks

Restricted Boltzmann machines (RBMs) are simple statistical models defined on a bipartite graph which have been successfully used in studying more complicated many-body systems, both classical and quantum. In this work, we exploit the representation power of RBMs to provide an exact decomposition of many-body contact interactions into one-body operators coupled to discrete auxiliary fields. This construction generalizes the well known Hirsch's transform used for the Hubbard model to more complicated theories such as pionless effective field theory in nuclear physics, which we analyze in detail. Finally, we also discuss possible applications of our mapping for quantum annealing applications and conclude with some implications for RBM parameter optimization through machine learning.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗

Transient dynamic analysis of laminated composite plates subjected to transverse impact

The dynamic response of a composite laminate plate to transverse impact loading is simulated numerically. An FEM scheme based on an eight-point brick element and three-dimensional linear elasticity theory is employed, assuming that the laminate layers are homogeneous and orthotropic. The derivation of the model is given in detail; the numerical implementation is briefly outlined; and results for the impact of 0.5-inch-diameter Al spheres at 500, 1000, and 1500 inch/sec on clamped or simply supported 3 x 3-inch plates made of T300/934 graphite/epoxy prepreg with ply orientation (0/-45/45/90)2S are presented in extensive graphs. The model is shown to provide accurate information on the histories of impactor-plate contact force; impactor displacement and velocity; and displacement, velocity, strain, and stress throughout the plate.

Wu, Hsi-Yung T.↗

Brill-Noether-general limit root bundles: absence of vector-like exotics in F-theory Standard Models

Root bundles appear prominently in studies of vector-like spectra of 4d F-theory compactifications. Of particular importance to phenomenology are the Quadrillion F-theory Standard Models (F-theory QSMs). In this work, we analyze a superset of the physical root bundles whose cohomologies encode the vector-like spectra for the matter representations ($3$, $2$) 1/6 , ($\overline{3}$, $1$) -2/3 and ($1$, $1$) 1 . For the family B 3 (Δ$^{°}_{4}$) consisting of $\mathcal{O}$(10 11 ) F-theory QSM geometries, we argue that more than 99.995% of the roots in this superset have no vector-like exotics. This indicates that absence of vector-like exotics in those representations is a very likely scenario in the O(10 11 ) QSM geometries B 3 (Δ$^{°}_{4}$). The QSM geometries come in families of toric 3-folds B 3 (Δ°) obtained from triangulations of certain 3-dimensional polytopes Δ°. The matter curves in X Σ $\large{ϵ}$ B 3 (Δ°) can be deformed to nodal curves which are the same for all spaces in B 3 (Δ°). Therefore, one can probe the vector-like spectra on the entire family B 3 (Δ°) from studies of a few nodal curves. We compute the cohomologies of all limit roots on these nodal curves. In our applications, for the majority of limit roots the cohomologies are determined by line bundle cohomology on rational tree-like curves. For this, we present a computer algorithm. The remaining limit roots, corresponding to circuit-like graphs, are handled by hand. The cohomologies are independent of the relative position of the nodes, except for a few circuits. On these jumping circuits, line bundle cohomologies can jump if nodes are specially aligned. This mirrors classical Brill-Noether jumps. B 3 (Δ°) admits a jumping circuit, but the root bundle constraints pick the canonical bundle and no jump happens.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Conducting Beyond the Standard Model Searches in the MicroBooNE Detector with Machine Learning

MicroBooNE is one of the three neutrino detectors that comprise the Short Baseline Neutrino program at Fermilab. It utilizes Liquid Argon Time Projection Chamber (LArTPC) technology to probe the anomalous excess of electron-like events seen by its predecessor, MiniBooNE. Additionally, it provides a rich avenue of study for Beyond the Standard Model (BSM) theories. In the GeV energy regime relevant to MicroBooNE's beam neutrino program, many such theories lead to signatures which produce electron-positron (e+e-) final-states in the detector. While photons can pair produce into e+e- pairs with negligible opening angles, BSM theories often predict e+e- pairs with a broader range of opening angles. Thus, developing a tool that can reliably measure the opening angles of e+e- events is crucial for conducting rigorous BSM studies. However, these e+e- pairs result in topologically complex showers instead of clean tracks, making non-machine learning (ML) based methods such as line-fitting unsuitable for this task. This poster discusses the effectiveness of ML, namely a graph neural network called PointNet++, in accomplishing this goal. Our studies show promising results, with a resolution for the opening angle of 5 or less.

Bhelande, Vedang Adutya [Los Alamos]↗

Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm

Abstract We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning (ML) models for predicting properties of inorganic bulk materials. The test suite, Matbench, is a set of 13 ML tasks that range in size from 312 to 132k samples and contain data from 10 density functional theory-derived and experimental sources. Tasks include predicting optical, thermal, electronic, thermodynamic, tensile, and elastic properties given a material’s composition and/or crystal structure. The reference algorithm, Automatminer, is a highly-extensible, fully automated ML pipeline for predicting materials properties from materials primitives (such as composition and crystal structure) without user intervention or hyperparameter tuning. We test Automatminer on the Matbench test suite and compare its predictive power with state-of-the-art crystal graph neural networks and a traditional descriptor-based Random Forest model. We find Automatminer achieves the best performance on 8 of 13 tasks in the benchmark. We also show our test suite is capable of exposing predictive advantages of each algorithm—namely, that crystal graph methods appear to outperform traditional machine learning methods given ~10 4 or greater data points. We encourage evaluating materials ML algorithms on the Matbench benchmark and comparing them against the latest version of Automatminer.

36 MATERIALS SCIENCE↗

Scale-invariant machine-learning model accelerates the discovery of quaternary chalcogenides with ultralow lattice thermal conductivity

We design an advanced machine-learning (ML) model based on crystal graph convolutional neural network that is insensitive to volumes (i.e., scale) of the input crystal structures to discover novel quaternary chalcogenides, AMM'Q 3 (A/M/M' = alkali, alkaline earth, post-transition metals, lanthanides, and Q = chalcogens). These compounds are shown to possess ultralow lattice thermal conductivity (κ l ), a desired requirement for thermal-barrier coatings and thermoelectrics. Upon screening the thermodynamic stability of ~1 million compounds using the ML model iteratively and performing density-functional theory (DFT) calculations for a small fraction of compounds, we discover 99 compounds that are validated to be stable in DFT. Taking several DFT-stable compounds, we calculate their κ l using Peierls–Boltzmann transport equation, which reveals ultralow κ l (<2 Wm -1 K -1 at room temperature) due to their soft elasticity and strong phonon anharmonicity. Our work demonstrates the high efficiency of scale-invariant ML model in predicting novel compounds and presents experimental-research opportunities with these new compounds.

36 MATERIALS SCIENCE↗

Scaling quantum approximate optimization on near-term hardware

The quantum approximate optimization algorithm (QAOA) is an approach for near-term quantum computers to potentially demonstrate computational advantage in solving combinatorial optimization problems. However, the viability of the QAOA depends on how its performance and resource requirements scale with problem size and complexity for realistic hardware implementations. Here, we quantify scaling of the expected resource requirements by synthesizing optimized circuits for hardware architectures with varying levels of connectivity. Assuming noisy gate operations, we estimate the number of measurements needed to sample the output of the idealized QAOA circuit with high probability. We show the number of measurements, and hence total time to solution, grows exponentially in problem size and problem graph degree as well as depth of the QAOA ansatz, gate infidelities, and inverse hardware graph degree. These problems may be alleviated by increasing hardware connectivity or by recently proposed modifications to the QAOA that achieve higher performance with fewer circuit layers.

97 MATHEMATICS AND COMPUTING↗

Graph-Based Similarity Metrics for Comparing Simulation Model Causal Structures

The causal structure of a simulation is a major determinant of both its character and behavior, yet most methods we use to compare simulations focus only on simulation outputs. We introduce a method that combines graphical representation with information theoretic metrics to quantitatively compare the causal structures of models. The method applies to agent-based simulations as well as system dynamics models and facilitates comparison within and between types. Comparing models based on their causal structures can illuminate differences in assumptions made by the models, allowing modelers to (1) better situate their models in the context of existing work, including highlighting novelty, (2) explicitly compare conceptual theory and assumptions to simulated theory and assumptions, and (3) investigate potential causal drivers of divergent behavior between models. We demonstrate the method by comparing two epidemiology models at different levels of aggregation.

97 MATHEMATICS AND COMPUTING↗

Gear Performance Improved by Coating

Gears, bearings, and other mechanical elements transmit loads through contacting surfaces. Even if properly designed, manufactured, installed, and maintained, gears and bearings will eventually fail because of the fatigue of the working surfaces. Economical means for extending the fatigue lives of gears and bearings are highly desired, and coatings offer the opportunity to engineer surfaces to extend the fatigue lives of mechanical components. A tungsten-containing diamondlike-carbon coating exhibiting high hardness, low friction, and good toughness was evaluated for application to spur gears. Fatigue testing was done at the NASA Glenn Research Center on both uncoated and coated spur gears. The results showed that the coating extended the surface fatigue lives of the gears by a factor of about 5 relative to the uncoated gears. For the experiments, a lot of spur test gears made from AISI 9310 gear steel were case-carburized and ground to aerospace specifications. The geometries of the 28-tooth, 8-pitch gears were verified as meeting American Gear Manufacturing Association (AGMA) quality class 12. One-half of the gears were randomly selected for coating. The method of coating was selected to achieve desired adherence, toughness, hardness, and low-friction characteristics. First the gears to be coated were prepared by blasting (vapor honing) with Al2O3 particles and cleaning. Then, the gears were provided with a thin adhesion layer of elemental chromium followed by magnetron sputtering of the outer coating consisting of carbon (70 at.%), hydrogen (15 at.%), tungsten (12 at.%), and nickel (3 at.%) (atomic percent at the surface). In total, the coating thickness was about 2.5 to 3 microns. As compared with the steel substrate, the coated surface was harder by a factor of about 2 and had a smaller elastic modulus. All gears were tested using a 5-centistoke synthetic oil, a 10,000-rpm rotation speed, and a hertzian contact stress of at least 1.7 GPa (250 ksi). Tests were run until either surface fatigue occurred or 300 million stress cycles were completed. Tests were run using either a pair of uncoated gears or a pair of coated gears (coated gears mated with uncoated gears were not evaluated). The fatigue test results, shown on Weibull coordinates in the graph, demonstrate that the coating provided substantially longer fatigue lives even though some of the coated gears endured larger stresses. The increase in fatigue life was a factor of about 5 and the statistical confidence for the improvement is high (greater than 99 percent). Examination of the tested gears revealed substantial reductions of total wear for coated gears in comparison to uncoated gears. The coated gear surface topography changed with running, with localized areas of the tooth surface becoming smoother with running. Theories explaining how coatings can extend gear fatigue lives are research topics for coating, tribology, and fatigue specialists. This work was done as a partnership between NASA, the U.S. Army Research Laboratory, United Technologies Research Corporation, and Sikorsky Aircraft.

Krantz, Timothy L.↗

The dynamics of particle disks. III - Dense and spinning particle disks

The kinetic theory of planetary rings developed by Araki and Tremaine (1986) and Araki (1988) is extended and refined, with a focus on the implications of finite particle size: (1) nonlocal collisions and (2) finite filling factors. Consideration is given to the derivation of the equations for the local steady state, the low-optical-depth limit, and the steady state at finite filling factors (including the effects of collision inelasticity, spin degrees of freedom, and self-gravity). Numerical results are presented in extensive graphs and characterized in detail. The importance of distinguishing effects (1) and (2) at low optical depths is stressed, and the existence of vertical density profiles with layered structures at high filling factors is demonstrated.

Araki, Suguru↗

Scalable generalized screening for high-order terms in the many-body expansion: Algorithm, open-source implementation, and demonstration

The many-body expansion lies at the heart of numerous fragment-based methods that are intended to sidestep the nonlinear scaling of ab initio quantum chemistry, making electronic structure calculations feasible in large systems. In principle, inclusion of higher-order n-body terms ought to improve the accuracy in a controllable way, but unfavorable combinatorics often defeats this in practice and applications with n ≥ 4 are rare. Here, we outline an algorithm to overcome this combinatorial bottleneck, based on a bottom-up approach to energy-based screening. This is implemented within a new open-source software application (“Fragme∩t”), which is integrated with a lightweight semi-empirical method that is used to cull subsystems, attenuating the combinatorial growth of higher-order terms in the graph that is used to manage the calculations. This facilitates applications of unprecedented size, and we report four-body calculations in (H2O)64 clusters that afford relative energies within 0.1 kcal/mol/monomer of the supersystem result using less than 10% of the unique subsystems. We also report n-body calculations in (H2O)20 clusters up to n = 8, at which point the expansion terminates naturally due to screening. These are the largest n-body calculations reported to date using ab initio electronic structure theory, and they confirm that high-order n-body terms are mostly artifacts of basis-set superposition error.

Chemistry↗

Understanding the effect of density functional choice and van der Waals treatment on predicting the binding configuration, loading, and stability of amine-grafted metal organic frameworks

Metal organic frameworks (MOFs) are crystalline, three-dimensional structures with high surface areas and tunable porosities. Made from metal nodes connected by organic linkers, the exact properties of a given MOF are determined by node and linker choice. MOFs hold promise for numerous applications, including gas capture and storage. M2(4,4′-dioxidobiphenyl-3,3′-dicarboxylate)—henceforth simply M2(dobpdc), with M = Mg, Mn, Fe, Co, Ni, Cu, or Zn—is regarded as one of the most promising structures for CO2 capture applications. Further modification of the MOF with diamines or tetramines can significantly boost gas species selectivity, a necessity for the ultra-dilute CO2 concentrations in the direct-air capture of CO2. There are countless potential diamines and tetramines, paving the way for a vast number of potential sorbents to be probed for CO2 adsorption properties. The number of amines and their configuration in the MOF pore are key drivers of CO2 adsorption capacity and kinetics, and so a validation of computational prediction of these quantities is required to suitably use computational methods in the discovery and screening of amine-functionalized sorbents. In this work, we study the predictive accuracy of density functional theory and related calculations on amine loading and configuration for one diamine and two tetramines. In particular, we explore the Perdew–Burke–Ernzerhof (PBE) functional and its formulation for solids (PBEsol) with and without the Grimme-D2 and Grimme-D3 pairwise corrections (PBE+D2/3 and PBEsol+D2/3), two revised PBE functionals with the Grimme-D2 and Grimme-D3 pairwise corrections (RPBE+D2/3 and revPBE+D2/3), and the nonlocal van der Waals correlation (vdW-DF2) functional. We also investigate a universal graph deep learning interatomic potential’s (M3GNet) predictive accuracy for loading and configuration. These results allow us to identify a useful screening procedure for configuration prediction that has a coarse component for quick evaluation and a higher accuracy component for detailed analysis. Our general observation is that the neural network-based potential can be used as a high-level and rapid screening tool, whereas PBEsol+D3 gives a completely qualitatively predictive picture across all systems studied, and can thus be used for high accuracy motif predictions. We close by briefly exploring the predictions of relative thermal stability for the different functionals and dispersion corrections.

Chemistry↗