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At least 415 records · Page 23

Recent Advances on Computational Modeling of Supported Single-Atom and Cluster Catalysts: Characterization, Catalyst–Support Interaction, and Active Site Heterogeneity

To satisfy the need for catalyst materials with high activity, selectivity, and stability for energy conversion, material design and discovery guided by theoretical insights are a necessity. In the past decades, the rise in theoretical investigations into the properties of catalyst materials, reaction mechanisms, and catalyst design principles has shed light on the catalysis field. Quantitative structure–activity relationships have been developed through incorporating spectroscopic simulations, electronic structure calculations, and reaction mechanistic studies. Here, in this review, we report the state-of-the-art computational approaches to catalyst materials characterization for supported single-atom and cluster catalysts utilizing spectroscopic simulations, i.e., XANES simulation, and material properties investigation via electronic-structure calculations. Furthermore, approaches regarding reaction mechanisms, focusing on active site heterogeneity, are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic Structure Theory Calculations Using Modern Architectures: KNL vs Haswell

The time to solution and parallel efficiency of several commonly used electronic structure methods (Hartree–Fock, density functional theory, second order perturbation theory, resolution of the identity second order perturbation theory, coupled cluster) are evaluated on both the Intel Xeon Haswell and the Intel Xeon Phi Knights Landing (KNL) architectures. The Haswell completes the benchmark calculations with a faster time to solution than the KNL for all molecules and methods tested. While the Haswell exhibits an average speedup of at least 3.5 relative to the KNL for all nonthreaded computations, the KNL has a better parallel efficiency than the Haswell with increasing core counts. The architectures are further tested using a more computationally costly coupled cluster method on a transition state reaction. The Haswell appears to be the best choice to minimize the time to solution, though for very large systems and high levels of theory that require memory intensive processes the superior memory hierarchy and larger on node memory of the KNL can make it a better choice. These results are used to showcase aspects of novel architectures that will increase efficiency for quantum chemistry applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Study of the Resonance Enhancement of Raman Signals of Ligands Adsorbed to CdSe Clusters through Photoexcitation of the Cluster

This paper describes density-functional-theory-based computations of resonance Raman (RR) spectra of ligand molecules adsorbed to the surface of a Cd 16 Se 13 cluster. Signals from asymmetric vibrational modes of ligand binding groups, such as the asymmetric O–C–O stretching modes of carboxylates, are enhanced relative to the symmetric vibrational modes when the excitation energy is on-resonance with the excitonic energy of the cluster. Certain ligand molecules have frontier orbitals with the correct energies and symmetries to mix with the orbitals of the CdSe cluster, and as a result, the wave functions of the electron and the hole delocalize from the cluster onto the ligand molecules; experimentally, this delocalization results in a bathochromic shift of the band edge excitonic absorption. Increased excitonic delocalization results in greater vibronic coupling between the exciton and the ligand vibrations and, on average, preferential enhancements in the RR signals of those vibrations. This work suggests that the use of exciton-delocalizing ligands to optimize electronic coupling between neighboring CdSe nanoparticles may, at the same time, enhance the rates of nonradiative exciton decay by coupling the exciton and ligand vibrational modes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Poplar: a phylogenomics pipeline

Motivation Generating phylogenomic trees from the genomic data is essential in understanding biological systems. Each step of this complex process has received extensive attention and has been significantly streamlined over the years. Given the public availability of data, obtaining genomes for a wide selection of species is straightforward. However, analyzing that data to generate a phylogenomic tree is a multistep process with legitimate scientific and technical challenges, often requiring a significant input from a domain-area scientist. Results We present Poplar, a new, streamlined computational pipeline, to address the computational logistical issues that arise when constructing the phylogenomic trees. It provides a framework that runs state-of-the-art software for essential steps in the phylogenomic pipeline, beginning from a genome with or without an annotation, and resulting in a species tree. Running Poplar requires no external databases. In the execution, it enables parallelism for execution for clusters and cloud computing. The trees generated by Poplar match closely with state-of-the-art published trees. The usage and performance of Poplar is far simpler and quicker than manually running a phylogenomic pipeline. Availability and implementation Freely available on GitHub at https://github.com/sandialabs/poplar. Implemented using Python and supported on Linux.

Koning, Elizabeth [Sandia National Laboratories (S↗

Pressure Effects on the Relaxation of an Excited Ethane Molecule in High-Pressure Bath Gases

Here, we use molecular dynamics to calculate the rotational and vibrational energy relaxation of C 2 H 6 in Ar, Kr, and Xe bath gases over a pressure range of 10 to 400 atm and at temperatures of 300 K and 800 K. The C 2 H 6 is instantaneously excited by 80 kcal/mol randomly distributed into both vibrational and rotational modes. The computed relaxation rates show little sensitivity to the identity of the noble gas in the bath. Vibrational relaxation rates show a non-linear pressure dependence at 300 K. At 800 K the reduced range of bath gas densities covered by the range of pressures do not yet show any non-linearity in the pressure dependence. Rotational relaxation is characterized with two relaxation rates. The slower rate is comparable to the vibrational relaxation rate. The faster rate has a linear pressure dependence at 300 K but an irregular, nonlinear pressure dependence at 800 K. To understand this, a model was developed based on approximating the periodic box used in the molecular dynamics simulations by an equal-volume collection of cubes where each cube is sized to allow only single occupancy by the noble gas or the molecule. Combinatorial statistics then leads to a pressure and temperature dependent analytic distribution of the bath gas species the molecule encounters in a collision. This distribution, the dissociation energy of molecule/bath gas complexes and bath gas clusters, and the computed energy release per collision combine to show that only at 300 K is the energy release sufficient to dissociate likely complexes and clusters. This suggests that persistent and pressure-dependent clusters and complexes at 800 K may be responsible for the non-linear pressure dependence of rotational relaxation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Vehicular Controller Area Networks (CANs) are susceptible to cyber attacks of different levels of sophistication. Fabrication attacks are the easiest to administer—an adversary simply sends (extra) frames on a CAN—but also the easiest to detect because they disrupt frame frequency. To overcome time-based detection methods, adversaries must administer masquerade attacks by sending frames in lieu of (and therefore at the expected time of) benign frames but with malicious payloads. Research efforts have proven that CAN attacks, and masquerade attacks in particular, can affect vehicle functionality. Examples include causing unintended acceleration, deactivation of vehicle’s brakes, as well as steering the vehicle. We hypothesize that masquerade attacks modify the nuanced correlations of CAN signal time series and how they cluster together. Therefore, changes in cluster assignments should indicate anomalous behavior. We confirm this hypothesis by leveraging our previously developed capability for reverse engineering CAN signals (i.e., CAN-D [Controller Area Network Decoder]) and focus on advancing the state of the art for detecting masquerade attacks by analyzing time series extracted from raw CAN frames. Specifically, we demonstrate that masquerade attacks can be detected by computing time series clustering similarity using hierarchical clustering on the vehicle’s CAN signals (time series) and comparing the clustering similarity across CAN captures with and without attacks. We test our approach in a previously collected CAN dataset with masquerade attacks (i.e., the ROAD dataset) and develop a forensic tool as a proof of concept to demonstrate the potential of the proposed approach for detecting CAN masquerade attacks.

Moriano Salazar, Pablo↗

Limits on clustering and smooth quintessence from the EFTofLSS

We apply the Effective Field Theory of Large-Scale Structure (EFTofLSS) to analyze cosmological models with clustering quintessence, which allows us to consistently describe the parameter region in which the quintessence equation of state w < -1. First, we extend the description of biased tracers in redshift space to the presence of clustering quintessence, and compute the one-loop power spectrum. We solve the EFTofLSS equations using the exact time dependence, which is relevant to obtain unbiased constraints. Then, fitting the full shape of BOSS pre-reconstructed power spectrum measurements, the BOSS post-reconstruction BAO measurements, BAO measurements from 6DF/MGS and eBOSS, the Supernovae from Pantheon, and a prior from BBN, we bound the clustering quintessence equation of state parameter w = -1.011 -0.048 +0.053 at 68% C.L. Further combining with Planck, we obtain w = -1.028 -0.030 +0.037 at 68% C.L. We also obtain constraints on smooth quintessence, in the physical regime w ≥ -1: combining all datasets, we get -1 ≤ w < -0.979 at 68% C.L. These results strongly support a cosmological constant.

79 ASTRONOMY AND ASTROPHYSICS↗

The effect of hydrogen-bonding on flavin’s infrared absorption spectrum

Cluster and continuum solvation computational models are employed to model the effect of hydrogen bonding interactions on the vibrational modes of lumiflavin. Calculated spectra were compared to experimental Fourier-transform infrared (FTIR) spectra in the diagnostic 1450–1800 cm –1 range, where intense V C=C , V C=N , V C 2 =O , and V C 4 =O stretching modes of flavin’s isoalloxazine ring are found. Local mode analysis is used to describe the strength of hydrogen-bonding in cluster models. The computations indicate that V C=C and V C=N mode frequencies are relatively insensitive to intermolecular interactions while the V C 2 =O and V C 4 =O modes are sensitive to direct (and also indirect for V C 2 =O ) hydrogen-bonding interactions. Although flavin is neutral, basis sets without the diffuse functions provide incorrect relative frequencies and intensities. The 6-31+G* basis set is found to be adequate for this system, and there is limited benefit to considering larger basis sets. Calculated vibrational mode frequencies agree with experimentally determined frequencies in solution when cluster models with multiple water molecules are used. Accurate simulation of relative FTIR band intensities, on the other hand, requires a continuum (or possibly quantum mechanical/molecular mechanical) model that accounts for long-range electrostatic effects. Lastly, an experimental peak at ca. 1624 cm –1 that is typically assigned to the V C 2 =O vibrational stretching mode has a complicated shape that suggests multiple underlying contributions. Our calculations show that this band has contributions from both the C 6 –C 7 and C 2 = O stretching vibrations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The halo model in a massive neutrino cosmology

We provide a quantitative analysis of the halo model in the context of massive neutrino cosmologies. We discuss all the ingredients necessary to model the non-linear matter and cold dark matter power spectra and compare with the results of N-body simulations that incorporate massive neutrinos. Our neutrino halo model is able to capture the non-linear behavior of matter clustering with a ∼20% accuracy up to very non-linear scales of k = 10 h/Mpc (which would be affected by baryon physics). The largest discrepancies arise in the range k = 0.5 – 1 h/Mpc where the 1-halo and 2-halo terms are comparable and are present also in a massless neutrino cosmology. However, at scales k < 0.2 h/Mpc our neutrino halo model agrees with the results of N-body simulations at the level of 8% for total neutrino masses of < 0.3 eV. We also model the neutrino non-linear density field as a sum of a linear and clustered component and predict the neutrino power spectrum and the cold dark matter-neutrino cross-power spectrum up to k = 1 h/Mpc with ∼30% accuracy. For masses below 0.15 eV the neutrino halo model captures the neutrino induced suppression, casted in terms of matter power ratios between massive and massless scenarios, with a 2% agreement with the results of N-body/neutrino simulations. Finally, we provide a simple application of the halo model: the computation of the clustering of galaxies, in massless and massive neutrinos cosmologies, using a simple Halo Occupation Distribution scheme and our halo model extension.

79 ASTRONOMY AND ASTROPHYSICS↗

Spatiotemporal modeling of node temperatures in supercomputers

Los Alamos National Laboratory (LANL) is home to many large supercomputing clusters. These clusters require an enormous amount of power (~500-2000 kW each), and most of this energy is converted into heat. Thus, cooling the components of the supercomputer becomes a critical and expensive endeavor. Recently a project was initiated to investigate the effect that changes to the cooling system in a machine room had on three large machines that were housed there. Coupled with this goal was the aim to develop a general good-practice for characterizing the effect of cooling changes and monitoring machine node temperatures in this and other machine rooms. This paper focuses on the statistical approach used to quantify the effect that several cooling changes to the room had on the temperatures of the individual nodes of the computers. The largest cluster in the room has 1,600 nodes that run a variety of jobs during general use. Since extremes temperatures are important, a Normal distribution plus generalized Pareto distribution for the upper tail is used to model the marginal distribution, along with a Gaussian process copula to account for spatio-temporal dependence. A Gaussian Markov random field (GMRF) model is used to model the spatial effects on the node temperatures as the cooling changes take place. This model is then used to assess the condition of the node temperatures after each change to the room. The analysis approach was used to uncover the cause of a problematic episode of overheating nodes on one of the supercomputing clusters. Lastly, this same approach can easily be applied to monitor and investigate cooling systems at other data centers, as well.

97 MATHEMATICS AND COMPUTING↗

Properties of the water to boron nitride interaction: From zero to two dimensions with benchmark accuracy

Molecular adsorption on surfaces plays an important part in catalysis, corrosion, desalination, and various other processes that are relevant to industry and in nature. As a complement to experiments, accurate adsorption energies can be obtained using various sophisticated electronic structure methods that can now be applied to periodic systems. The adsorption energy of water on boron nitride substrates, going from zero to 2-dimensional periodicity, is particularly interesting as it calls for an accurate treatment of polarizable electrostatics and dispersion interactions, as well as posing a practical challenge to experiments and electronic structure methods. Here, we present reference adsorption energies, static polarizabilities, and dynamic polarizabilities, for water on BN substrates of varying size and dimension. Adsorption energies are computed with coupled cluster theory, fixed-node quantum Monte Carlo (FNQMC), the random phase approximation, and second order Møller-Plesset theory. These wavefunction based correlated methods are found to agree in molecular as well as periodic systems. The best estimate of the water/h-BN adsorption energy is -107 ± 7 meV from FNQMC. In addition, the water adsorption energy on the BN substrates could be expected to grow monotonically with the size of the substrate due to increased dispersion interactions, but interestingly, this is not the case here. This peculiar finding is explained using the static polarizabilities and molecular dispersion coefficients of the systems, as computed from time-dependent density functional theory (DFT). Dynamic as well as static polarizabilities are found to be highly anisotropic in these systems. Finally, the many-body dispersion method in DFT emerges as a particularly useful estimation of finite size effects for other expensive, many-body wavefunction based methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reinterpretation of the electronic absorption spectrum of the methylene amidogen radical (H 2 CN)

The odd electronic absorption spectrum of H 2 CN has been of great interest to experiment. Herein, this system is reported on extensively by applying theoretical methods to the ground and low-lying excited electronic states. Employing a large breadth of high-level ab initio computations, including coupled cluster [CCSD(T) and CCSDT(Q)] and multireference configuration interaction [MRCISD+Q] methods, we comprehensively demonstrate that the most recent experimental and theoretical interpretations of the electronic spectrum of H 2 CN are in error. The previous assignments of the two broad features in the spectrum as the origin 0$^{0}_{0}$ (~35 050 cm –1 ) and 4$^{2}_{0}$ (~35 600 cm –1 )$\widetilde{B}$ 2 A 1 ←$\widetilde{X}$ 2 B 2 transitions are both found to be incorrect. The presently reported transition energies suggest that the higher energy band near 35 600 cm –1 is the true origin band. Moreover, from the computed anharmonic vibrational frequencies of the $\widetilde{X}$ 2 B 2 and $\widetilde{B}$ 2 A 1 states, we demonstrate that this ~550 cm –1 band spacing cannot be attributed to a simple vibronic transition, as claimed by the 4$^{2}_{0}$ assignment. Possible alternative explanations for the appearance of the lower intensity band near 35 050 cm –1 are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SPT-CL J2040–4451: An SZ-selected galaxy cluster at z = 1.478 with significant ongoing star formation

SPT-CL J2040–4451—spectroscopically confirmed at z = 1.478—is the highest-redshift galaxy cluster yet discovered via the Sunyaev-Zel'dovich effect. SPT-CL J2040–4451 was a candidate galaxy cluster identified in the first 720 deg{sup 2} of the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) survey, and has been confirmed in follow-up imaging and spectroscopy. From multi-object spectroscopy with Magellan-I/Baade+IMACS we measure spectroscopic redshifts for 15 cluster member galaxies, all of which have strong [O II] λλ3727 emission. SPT-CL J2040–4451 has an SZ-measured mass of M {sub 500,} {sub SZ} = 3.2 ± 0.8 × 10{sup 14} M {sub ☉} h {sub 70}{sup −1}, corresponding to M {sub 200,} {sub SZ} = 5.8 ± 1.4 × 10{sup 14} M {sub ☉} h {sub 70}{sup −1}. The velocity dispersion measured entirely from blue star-forming members is σ {sub v} = 1500 ± 520 km s{sup –1}. The prevalence of star-forming cluster members (galaxies with >1.5 M {sub ☉} yr{sup –1}) implies that this massive, high-redshift cluster is experiencing a phase of active star formation, and supports recent results showing a marked increase in star formation occurring in galaxy clusters at z ≳ 1.4. We also compute the probability of finding a cluster as rare as this in the SPT-SZ survey to be >99%, indicating that its discovery is not in tension with the concordance ΛCDM cosmological model.

79 ASTRONOMY AND ASTROPHYSICS↗

Importance of elastic finite-size effects: Neutral defects in ionic compounds

Small system sizes are a well known source of error in DFT calculations, yet computational constraints frequently dictate the use of small supercells, often as small as 96 atoms in oxides and compound semiconductors. In ionic compounds, electrostatic finite size effects have been well characterised, but self-interaction of charge neutral defects is often discounted or assumed to follow an asymptotic behaviour and thus easily corrected with linear elastic theory. Here we show that elastic effect are also important in the description of defects in ionic compounds and can lead to qualitatively incorrect conclusions if inadequatly small supercells are used; moreover, the spurious self-interaction does not follow the behaviour predicted by linear elastic theory. Considering the exemplar cases of metal oxides with fluorite structure, we show that numerous previous studies, employing 96-atom supercells, misidentify the ground state structure of (charge neutral) Schottky defects. We show that the error is eliminated by employing larger cells (324, 768 and 1500 atoms), and careful analysis determines that elastic effects, not electrostatic, are responsible. The spurious self-interaction was also observed in non-oxide ionic compounds and irrespective of the computational method used, thereby resolving long standing discrepancies between DFT and force-field methods, previously attributed to the level of theory. The surprising magnitude of the elastic effects are a cautionary tale for defect calculations in ionic materials, particularly when employing computationally expensive methods (e.g. hybrid functionals) or when modelling large defect clusters. We propose two computationally practicable methods to test the magnitude of the elastic self-interaction in any ionic system. In commonly studies oxides, where electrostatic effects would be expected to be dominant, it is the elastic effects that dictate the need for larger supercells | greater than 96 atoms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Studying CPU and memory utilization of applications on Fujitsu A64FX and Nvidia Grace Superchip

ARM-based manycore CPU architectures are well-positioned to provide the rising memory throughput requirements of modern data intensive scientific applications in High Performance Computing (HPC). The Fujitsu A64FX CPU platform is based on the ARM v8.2A architecture, and is the processor of the flagship Japanese supercomputer - "Fugaku", which was previously ranked as the #1 supercomputer in the world according to the Top500 list. The Nvidia Grace superchip features 144 Neoverse V2 cores based on the ARMv9 architecture with 4x128b SVE2, providing exceptional computational power. The chip supports up to 480GB of memory, making it ideal for AI, machine learning, and scientific computing workloads. In this paper, we conduct a thorough performance exploration of a variety of parallel bandwidth-sensitive benchmarks and applications compiled with the native Fujitsu compiler on a Fugaku A64FX compute node and ARM (LLVM) Compiler on an NVIDIA Grace superchip compute node, engaging all the computational cores per cluster using OpenMP multithreading (assuming the cores can drive the available bandwidth). Our ultimate goals are to study the resource utilization of scientific applications and benchmarks on A64FX and Grace superchip, considering graph application scenarios ( GAP Benchmark suite) and eleven appli- cation proxies from the Rodinia heterogeneous benchmark suite (considering domains such as Data Mining, Bioinformatics, Fluid Dynamics, Pattern Recognition, etc.). Through exhaustive performance monitoring, we quantify the resource utilization of diverse OpenMP-based HPC applications on both the Fujitsu A64FX and the Nvidia Grace Superchip platforms.

benchmarking, Performance Analysis, High performan↗

Cosmological inference from an emulator based halo model. II. Joint analysis of galaxy-galaxy weak lensing and galaxy clustering from HSC-Y1 and SDSS

Here, we present high-fidelity cosmology results from a blinded joint analysis of galaxy-galaxy weak lensing (ΔΣ) and projected galaxy clustering (w p ) measured from the Hyper Suprime-Cam Year-1 (HSC-Y1) data and spectroscopic Sloan Digital Sky Survey (SDSS) galaxy catalogs in the redshift range 0.15 < z < 0.7. We define luminosity-limited samples of SDSS galaxies to serve as the tracers of w p in three spectroscopic redshift bins, and as the lens samples for ΔΣ. For the ΔΣ measurements, we select a single sample of 4×10 6 source galaxies over 140 deg 2 from HSC-Y1 with photometric redshifts (photo z) greater than 0.75, enabling a better handle of photo- z errors by comparing the ΔΣ amplitudes for the three lens redshift bins. The deep, high-quality HSC-Y1 data enable significant detections of the ΔΣ signals, with integrated signal-to-noise ratio S/N ~ 15 in the range 3 ≤ R/[h –1 Mpc] ≤ 30 for the three lens samples, despite the small area coverage. For cosmological parameter inference, we use an input galaxy-halo connection model built on the dark emulator package (which uses an ensemble set of high-resolution N-body simulations and enables fast, accurate computation of the clustering observables) with a halo occupation distribution that includes nuisance parameters to marginalize over modeling uncertainties. We model the ΔΣ and wp measurements on scales from R≃3 and 2h –1 Mpc , respectively, up to 30 h –1 Mpc (therefore excluding the baryon acoustic oscillations information) assuming a flat Λ CDM cosmology, marginalizing over about 20 nuisance parameters and demonstrating the robustness of our results to them. With various tests using mock catalogs described in Miyatake et al. [preceding paper, Phys. Rev. D 106, 083519 (2022)], we show that any bias in the clustering amplitude S 8 ≡ σ 8 (Ω m /0.3) 0.5 due to uncertainties in the galaxy-halo connection is less than ~ 50 % of the statistical uncertainty of S 8 , unless the assembly biaseffect is unexpectedly large. Our best-fit models have S 8 = 0.795$_{-0.042}^{+0.049}$ (mode and 68% credible interval) for the flat Λ CDM model; we find tighter constraints on the quantity S 8 (α = 0.17)≡σ 8 (Ω m /0.3) 0.17 = 0.745$_{-0.031}^{+0.039}$.

79 ASTRONOMY AND ASTROPHYSICS↗

Multiscale modeling of fission gas behavior in U 3 Si 2 under LWR conditions

In this work, we present a model of fission gas behavior in U 3 Si 2 under light water reactor (LWR) conditions for application in engineering fuel performance codes. The model includes components for intra-granular and inter-granular behavior of fission gases. The intra-granular component is based on cluster dynamics and computes the evolution of intra-granular fission gas bubbles and swelling coupled to gas diffusion to grain boundaries. The inter-granular component describes the evolution of grain-boundary fission gas bubbles coupled to fission gas release. Given the lack of experimental data for U 3 Si 2 under LWR conditions, the model is informed with parameters calculated via atomistic simulations. In particular, we derive fission gas diffusivities through density functional theory calculations, and the re-solution rate of fission gas atoms from intra-granular bubbles through binary collision approximation calculations. Further, the developed model is applied to the simulation of an experiment for U 3 Si 2 irradiated under LWR conditions available from the literature. Results point out a credible representation of fission gas swelling and release in U 3 Si 2 . Finally, we perform a sensitivity analysis for the various model parameters. Based on the sensitivity analysis, indications are derived that can help in addressing future research on the characterization of the physical parameters relative to fission gas behavior in U 3 Si 2 . The developed model is intended to provide a suitable infrastructure for the engineering scale calculation of fission gas behavior in U 3 Si 2 that exploits a multiscale approach to fill the experimental data gap and can be progressively improved as new lower-length scale calculations and validation data become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Conservation of Dynamics Associated with Biological Function in an Enzyme Superfamily

Enzyme superfamily members that share common chemical and/or biological functions also share common features. While the role of structure is well characterized, the link between enzyme function and dynamics is not well understood. We present a systematic characterization of intrinsic dynamics of over 20 members of the pancreatic-type RNase superfamily, which share a common structural fold. This study is motivated by the fact that the range of chemical activity as well as molecular motions of RNase homologs spans over 105 folds. Dynamics was characterized using a combination of nuclear magnetic resonance experiments and computer simulations. Phylogenetic clustering led to the grouping of sequences into functionally distinct subfamilies. Detailed characterization of the diverse RNases showed conserved dynamical traits for enzymes within subfamilies. These results suggest that selective pressure for the conservation of dynamical behavior, among other factors, may be linked to the distinct chemical and biological functions in an enzyme superfamily.

Biochemistry & Molecular Biology↗