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At least 775 records · Page 43

Insight into the Catalytic Mechanism of GH11 Xylanase: Computational Analysis of Substrate Distortion Based on a Neutron Structure

The reaction mechanism of biomass decomposition by xylanases remains the subject of debate. Here, to clarify the mechanism, we investigated the glycosylation step of GH11 xylanase, an enzyme that catalyzes the hydrolysis of lignocellulosic hemicellulose (xylan). Making use of a recent neutron crystal structure, which revealed the protonation states of relevant residues, we used ab initio quantum mechanics/molecular mechanics (QM/MM) calculations to determine the detailed reaction mechanism of the glycosylation step. In particular, our focus is on the controversial question of whether or not an oxocarbenium ion intermediate is formed on the reaction pathway. The calculations support the validity of a basic retaining mechanism within a double-displacement scheme. The estimated free energy barrier of this reaction is ~18 kcal/mol with QM/MM-CCSD(T)/6-31(+)G**//MP2/6-31+G**/AMBER calculations, and the rate-determining step of the glycosylation is scission of the glycosidic bond after proton transfer from the acidic Glu177. The estimated lifetime of the oxocarbenium ion intermediate (on the order of tens of ps) and the secondary kinetic isotope effect suggest that there is no accumulation of this intermediate on the reaction path, although the intermediate can be transiently formed. In the enzyme–substrate (ES) complex, the carbohydrate structure of the xylose residue at the -1 subsite has a rather distorted (skewed) geometry, and this xylose unit at the active site has an apparent half-chair conformation when the oxocarbenium ion intermediate is formed. The major catalytic role of the protein environment is to orient residues that take part in the initial proton transfer. Because of a fine alignment of catalytic residues, the enzyme can accelerate the glycosylation reaction without paying a reorganization energy penalty.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fully variational incremental CASSCF

We report the complete-active-space self-consistent field (CASSCF) method is a canonical electronic structure theory that holds a central place in conceptualizing and practicing first principles simulations. For application to realistic molecules, however, the CASSCF must be approximated to circumvent its exponentially scaling computational costs. Applying the many-body expansion - also known as the method of increments - to CASSCF (iCASSCF) has been shown to produce a polynomially scaling method that retains much of the accuracy of the parent theory and is capable of treating full valence active spaces. Due to an approximation made in the orbital gradient, the orbital parameters of the original iCASSCF formulation could not be variationally optimized, which limited the accuracy of its nuclear gradient. Herein, a variational iCASSCF is introduced and implemented, where all parameters are fully optimized during energy minimization. This method is able to recover electronic correlations from the full valence space in large systems, produce accurate gradients, and optimize stable geometries as well as transition states. Demonstrations on challenging test cases, such as the oxoMn(salen)Cl complex with 84 electrons in 84 orbitals and the automerization of cyclobutadiene, show that the fully variational iCASSCF is a powerful tool for describing challenging molecular chemistries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

From disorganized data to emergent dynamic models: Questionnaires to partial differential equations

Starting with sets of disorganized observations of spatially varying and temporally evolving systems, obtained at different (also disorganized) sets of parameters, we demonstrate the data-driven derivation of parameter dependent, evolutionary partial differential equation (PDE) models capable of generating the data. This tensor type of data is reminiscent of shuffled (multidimensional) puzzle tiles. The independent variables for the evolution equations (their “space” and “time”) as well as their effective parameters are all emergent , i.e. determined in a data-driven way from our disorganized observations of behavior in them. We use a diffusion map based questionnaire approach to build a smooth parametrization of our emergent space/time/parameter space for the data. This approach iteratively processes the data by successively observing them on the “space,” the “time” and the “parameter” axes of a tensor. Once the data become organized, we use machine learning (here, neural networks) to approximate the operators governing the evolution equations in this emergent space. Our illustrative examples are based (i) on a simple advection–diffusion model; (ii) on a previously developed vertex-plus-signaling model of Drosophila embryonic development; and (iii) on two complex dynamic network models (one neuronal and one coupled oscillator model) for which no obvious smooth embedding geometry is known a priori. This allows us to discuss features of the process like symmetry breaking, translational invariance, and autonomousness of the emergent PDE model, as well as its interpretability.

generative models↗

Compare linear-system solver and preconditioner stacks with emphasis on GPU performance and propose phase-2 NGP solver development pathway

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. In this report we evaluated GPU-performance baselines for the linear solvers in the Trilinos and hypre solver stacks using two representative Nalu-Wind simulations: an atmospheric boundary layer precursor simulation on a structured mesh, and a fixed-wing simulation using unstructured overset meshes. Both strong-scaling and weak-scaling experiments were conducted on the OLCF supercomputer Summit and similar proxy clusters. We focused on the performance of multi-threaded Gauss-Seidel and two-stage Gauss-Seidel that are extensions of classical Gauss-Seidel; of one-reduce GMRES, a communication-reducing variant of the Krylov GMRES; and algebraic multigrid methods that incorporate the afore-mentioned methods. The team has established that AMG methods are capable of solving linear systems arising from the fixed-wing overset meshes on CPU, a critical intermediate result for ExaWind FY20 Q3 and Q4 milestones. For the fixed-wing strong-scaling study (model with 3M grid-points), the team identified that Nalu-Wind simulations with the new Trilinos and hypre solvers scale to modest GPU counts, maintaining above 70% efficiency up to 6 GPUs. However, there still remain significant bottlenecks to performance: matrix assembly (hypre), AMG setup (hypre and Trilinos) In the weak-scaling experiments (going from 0.4M to 211M gridpoints), it's shown that the solver apply phases are faster on GPUs, but that Nalu-Wind simulation times grow, primarily due to the multigrid-setup process. Finally, based on the report outcomes, we propose a linear solver path-forward for the remainder of the ExaWind project. Near term, the NREL team will continue their work on GPU-based linear-system assembly. They will also investigate how the use of alternatives to the NVIDIA UVM (unified virtual memory) paradigm affects performance. Longer term, the NREL team will evaluate algorithmic performance on other types of accelerators and merge their improvements back to the main hypre repository branch. Near term, the Trilinos team will address performance bottlenecks identified in this milestone, such as implementing a GPU-based segregated momentum solve and reusing matrix graphs across linear-system assembly phases. Longer term, the Trilinos team will do detailed analysis and optimization of multigrid setup.

17 WIND ENERGY↗

Demonstration and performance testing of extreme-resolution simulations with static meshes on Summit (CPU & GPU) for a parked-turbine configuration and an actuator-line (mid-fidelity model) wind farm configuration (ECP-Q4 FY2020 Milestone Report)

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind simulation environment are Nalu-Wind, an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, AMR-Wind, a block-structured-grid solver with adaptive mesh refinement capabilities, and OpenFAST, a wind-turbine structural dynamics solver. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and Helmholtz-type equations for transport of momentum and other scalars. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. The choice of overset-mesh methodology to model the moving and non-moving parts of the computational domain introduces constraint equations in the elliptic pressure-Poisson solver. The presence of constraints greatly affects the performance of algebraic multigrid preconditioners.

17 WIND ENERGY↗

Demonstrate moving-grid multi-turbine simulations primarily run on GPUs and propose improvements for successful KPP-2

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines, capturing the thin boundary layers, and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources.

17 WIND ENERGY↗

Demonstrate multi-turbine simulation with hybrid-structured / unstructured-moving-grid software stack running primarily on GPUs and propose improvements for successful KPP-2

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines, capturing the thin boundary layers, and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources.

17 WIND ENERGY↗

Slicing Solutions for Wire Arc Additive Manufacturing

Both commercial and research applications of wire arc additive manufacturing (WAAM) have seen considerable growth in the additive manufacturing of metallic components. However, there remains a clear lack of a unified paradigm for toolpath generation when slicing parts for WAAM deposition. Existing toolpath generation options typically lack the appropriate features to account for all complexities of the WAAM process. This manuscript explores the key slicing challenges specific to toolpaths for WAAM geometry and pairs each consideration with multiple solutions to mitigate most negative effects on completed components. These challenges must be addressed to minimize voids, prevent bead collapse, and ensure deposited components accurately approximate the desired geometry. Slicing considerations are grouped into four general categories: geometric, process, thermal, and productivity. Geometric considerations are addressed with overhang compensation, corner-sharpening, and toolpath-smoothing features. Process considerations are addressed with start point configuration and controls for the bead lengths and end points. Thermal and productivity considerations are addressed with island optimization, multi-material printing, and connected insets. Finally, tools for the post-processing of generated G-code are explored. Overall, these solutions represent a critical set of slicing features used to improve generated toolpaths and the quality of the components deposited with those toolpaths.

36 MATERIALS SCIENCE↗

The Synthesis and Structure of a Scandium Nitrate Hydroxy-Bridged Dimeric Complex Supported by Bipyridyl Ligands

The current discussion on whether scandium, yttrium and lanthanum should represent Group 3 in the Periodic Table or whether lutetium should replace lanthanum in the group has prompted us to further explore the structural chemistry of the Group 3 elements and compare the coordination numbers and coordination geometries adopted. The steric and electronic properties of the coordinated ligands have a major influence on the structures adopted. We report the synthesis and crystal structure determination of an unusual dinuclear scandium complex [(bipy)(NO 3 ) 2 Sc(µ-OH) 2 Sc(NO 3 ) 2 (bipy)] obtained by the reaction of hydrated scandium nitrate with 2,2'-bipyridyl (bipy) in either ethanol or nitromethane. The crystal structure of the complex shows that the scandium centers are eight coordinate, and the structure obtained contrasts with related complexes found in the lanthanide series [Ln(bipy) 2 (NO 3 ) 3 ] and [Ln(phen) 2 (NO 3 ) 3 ] (phen = phenanthroline) and in [M(terpy)(NO 3 ) 3 ] (M = Sc, Er–Lu), where these complexes are all mononuclear.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Precise Synthesis of Complex Si–Si Molecular Frameworks

In this Perspective, we highlight the emergence of target-oriented syntheses of complex molecules composed of Si–Si (oligosilanes) rather than C–C bonds. Saturated oligosilanes structurally resemble alkanes with respect to a tetrahedral geometry, a preference for a staggered conformation in linear chains, the ability to form stable small rings, and tetrahedral stereochemistry at asymmetrically functionalized Si centers. There are also critical differences, for example, differences in multiple bonding and the ability to form penta- and hexacoordinated structures, that mean that chemical reactivity and, in particular, rules for stereoselective synthesis do not cleanly translate from carbon to silicon. This Perspective will discuss recent achievements in the precise, controlled synthesis of complex molecules comprised mainly of Si–Si bonds and highlight the mechanistic insights enabling increased molecular complexity. New tools, such as electrochemical and catalytic reactions, will be discussed as well as the problem of controlling relative configuration in molecules containing multiple stereogenic-at-silicon centers. Furthermore, these synthetic achievements facilitate the discovery of new properties, including insight into light absorption, conformation, and mechanical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bond-centric modular design of protein assemblies

Directional interactions that generate regular coordination geometries are a powerful means of guiding molecular and colloidal self-assembly, but implementing such high-level interactions with proteins remains challenging due to their complex shapes and intricate interface properties. Here we describe a modular approach to protein nanomaterial design inspired by the rich chemical diversity that can be generated from the small number of atomic valencies. We design protein building blocks using deep learning-based generative tools, incorporating regular coordination geometries and tailorable bonding interactions that enable the assembly of diverse closed and open architectures guided by simple geometric principles. Experimental characterization confirms the successful formation of more than 20 multicomponent polyhedral protein cages, two-dimensional arrays and three-dimensional protein lattices, with a high (10%–50%) success rate and electron microscopy data closely matching the corresponding design models. Due to modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable networks for designer nanomaterials.

Biomaterials – proteins↗

Analytical simulation of meander morphology from equilibrium to long-term evolution: Impacts of channel geometry and vegetation-induced coarsening

This study introduces an innovative approach to modeling meandering river morphology, integrating and investigating the effects of geometric characteristics and vegetation-induced channel coarsening. The developed comprehensive framework combines several advanced techniques: Genetic Programming for refining the scour factor of transverse bed slope, a Leaf Area Index (LAI)-enhanced analytical model for quantifying vegetative flow resistance, and an upstream-weighted moving average method for efficient approximation of the convolution integral in meander migration calculations. The model is validated against both an idealized Kinoshita meander and a natural bend of the Tumen River (China) in equilibrium, demonstrating its robustness across diverse scales and conditions. The model's ability to simulate the long-term evolution, including cutoff events, provides valuable insight for river management strategies. The current findings demonstrate that channel geometry, particularly width-to-depth ratio, plays a dominant role in meander evolution, with wider channels prone to more complex and rapid morphological changes. Vegetation effects are most pronounced in channels with moderate width-to-depth ratios, where they can significantly influence migration rates and bed topography. A combination of channel widening and deepening, coupled with strategic vegetation management, can effectively enhance navigability while maintaining channel stability in the studied Tumen River reach. Sensitivity analyses highlight the complex interplay between hydraulic conditions, sediment characteristics, and vegetation in shaping river morphology. This research advances understanding of the multifaceted nature of meandering river systems and offers practical tools for informed decision-making in river engineering and environmental management, particularly in the context of climate change and increasing anthropogenic pressures on fluvial ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Inverse Trans Influence and Uranium-Arene σ-Bonding Drive Molecular Geometry: Ligand Modification from Hard to Soft Flips the Oxide from Axial to Equatorial

A rare example of an equatorially bound terminal uranium(V) oxo complex in a chelating sulfur-based ligand environment, namely [(mes( Me,Ad ArS) 3 )U V (O eq )(THF)] (2), is presented. Octahedrally coordinated 2 is obtained by reaction of the mesitylene-anchored tris-thiophenolate-coordinated uranium(III) complex [U III ((SAr Ad,Me ) 3 mes)] (1) with the oxygen-atom transfer reagent N 2 O. The observed, equatorially bound oxo ligand in 2 is in stark contrast to its known tris-aryloxide analog, [(mes( Me,Ad ArO) 3 )U V (O ax )(THF)] (A), where the oxo ligand occupies the typically observed axial coordination site. Complexes 1 and 2 are characterized by single-crystal X-ray diffraction analyses and spectroscopic and magnetochemical methods, including 1 H NMR, UV/vis/NIR electronic absorption, as well as EPR spectroscopy and SQUID magnetometry, thus confirming the C S symmetry and the pentavalent oxidation state of 2. Encompassing quantum chemical calculations (DFT and CASPT2) on 2 and its tris-phenolate analog A, support and rationalize the structural and electronic differences. The molecular orbital pictures show that a stabilizing σ-bonding interaction arising from the U–O eq inverse trans influence (ITI) is present in 2 but missing in A. In 2, the sulfur 3p orbitals are closer in energy to the uranium 5f manifold than the arene π-system, leading to an ITI, while U–arene σ- or δ-bonding is not observed. Although the arene orbitals remain separated from the uranium 5f orbitals in A, the absence of an ITI allows the arene a 2u orbital to engage in a σ-type interaction with the metal. Thus, incorporating a tris-thiophenolate to an arene anchor introduces a new design concept in molecular f-element chemistry. This approach stabilizes an equatorially bound U(V) oxo center, contrasting with its tris-phenolate counterpart, where oxo coordination is axial. The observed geometric divergence, driven by competing ITI and U–arene interactions, not only tunes electronic structure but also leads to differentiated reactivity: only the phenolate analogs activate H 2 O, while the thiolates do not.

Hydrocarbons↗

Computing virtual dark-field X-ray microscopy images of complex discrete dislocation structures from large-scale molecular dynamics simulations

Dark-field X-ray microscopy (DFXM) is a novel diffraction-based imaging technique that non-destructively maps the local deformation from crystalline defects in bulk materials. While studies have demonstrated that DFXM can spatially map 3D defect geometries, it is still challenging to interpret DFXM images of the high-dislocation-density systems relevant to macroscopic crystal plasticity. This work develops a scalable forward model to calculate virtual DFXM images for complex discrete dislocation structure(s) (DDS) obtained from atomistic simulations. Our new DDS-DFXM model integrates a non-singular formulation for calculating the local strain from the DDS and an efficient geometrical optics algorithm for computing the DFXM image from the strain field. We apply the model to complex DDS obtained from a large-scale mol­ecular dynamics simulation of compressive loading on single-crystal silicon. Simulated DFXM images exhibit prominent contrast for dislocation features between the multiple slip systems, demonstrating the potential of DFXM to resolve features from dislocation multiplication. In conclusion, the integrated DDS-DFXM model provides a toolbox for DFXM experimental design and image interpretation in the context of bulk crystal plasticity for a range of measurements across shock plasticity and the broader materials science community.

X-ray imaging↗

CHALLENGES IN THE DEVELOPMENT OF THE ELECTROREFINING PROCESS AT Y-12

In order to ensure future capabilities of the Y-12 site as older buildings retire, a new process was developed, the Metal Purification Process. The purpose of this new process is to provide a simpler and more efficient uranium metal purification that the previous multi-staged, complex chemical processes. The basis for this technology currently exists in the US DOE complex, but it has not been utilized on a large scale for uranium at higher enrichments. The system requires larger-geometry vessels and furnaces in order to meet the through-put requirements. The crux of the process is the electrorefining cell, consisting of several concentric liners and an unfavorable geometry cylindrical crucible. Within the crucible, a molten Li-CL-KCL-UCL3 salt electrolyte is present. ‘Dirty’ metal is placed into a loading basket and loaded into an electrorefining cell. Here, the metal reacts into the molten salt within the cell to form UCL3, while ‘clean’ metal simultaneously plates out from the salt electrolyte in the form of metal dendrites. These dendrites are then collected and removed from the cell. After removal from the cell, the dendrites are taken to a furnace to remove adhered salts. Then, the salt-free dendrites are moved to a separate furnace for consolidation into the final product form. The development of the Criticality Safety Evaluation for this complex system brought with it many NCS Challenges and lessons learned. These challenges include: design decisions for ensuring subcriticalty in the electrorefining cell during abnormal conditions, the interface of the main glovebox system with auxiliary systems such as the purification system and designated storage, implementation of mass tracking, and concerns from production and operation regarding the movement of material within the system.

36 MATERIALS SCIENCE↗

Structures of RNA ligase RtcB in complexes with divalent cations and GTP

Pyrococcus horikoshii (Pho) RtcB exemplifies a family of binuclear transition metal- and GTP-dependent RNA ligases that join 3'-phosphate and 5'-OH ends via RtcB-(histidinyl-N)–GMP and RNA 3' pp 5' G intermediates. We find that guanylylation of PhoRtcB is optimal with manganese and less effective with cobalt and nickel. Zinc and copper are inactive and potently inhibit manganese-dependent guanylylation. We report crystal structures of PhoRtcB in complexes with GTP and permissive (Mn, Co, Ni) or inhibitory (Zn, Cu) metals. Zinc and copper occupy the M1 and M2 sites adjacent to the GTP phosphates, as do manganese, cobalt, and nickel. The identity/positions of enzymic ligands for M1 (His234, His329, Cys98) and M2 (Cys98, Asp95, His203) are the same for permissive and inhibitory metals. The differences pertain to: (i) the coordination geometries and phosphate contacts of the metals; and (ii) the orientation of the His404 nucleophile with respect to the GTP α-phosphate and pyrophosphate leaving group. M2 metal coordination geometry correlates with metal cofactor activity, whereby inhibitory Zn2 and Cu2 assume a tetrahedral configuration and contact only the GTP γ-phosphate, whereas Mn2, Co2, and Ni2 coordination complexes are pentahedral and contact the β- and γ-phosphates. The His404-Nε–Pα–O(α-β) angle is closer to apical in Mn (179°), Co (171°), and Ni (169°) structures than in Zn (160°) and Cu (155°) structures. The octahedral Mn1 geometry in our RtcB•GTP•Mn 2+ structure, in which Mn1 contacts α-, β-, and γ-phosphates, transitions to a tetrahedral configuration after formation of RtcB•(His404)–GMP•Mn 2+ and departure of pyrophosphate.

59 BASIC BIOLOGICAL SCIENCES↗

“Lagrangian disks” in M-theory

While the study of bordered (pseudo-)holomorphic curves with boundary on Lagrangian submanifolds has a long history, a similar problem that involves (special) Lagrangian submanifolds with boundary on complex surfaces appears to be largely overlooked in both physics and math literature. We relate this problem to geometry of coassociative submanifolds in G 2 holonomy spaces and to Spin(7) metrics on 8-manifolds with T 2 fibrations. As an application to physics, we propose a large class of brane models in type IIA string theory that generalize brane brick models on the one hand and 2d theories T[M 4 ] on the other.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Three-dimensional electronic scaffolds for monitoring and regulation of multifunctional hybrid tissues

Recently, the integration of electronic elements with cellular scaffolds has brought forth the ability to monitor and control tissue function actively by using flexible free-standing two-dimensional (2D) systems. Capabilities for electrically probing complex, physicochemical and biological three-dimensional (3D) microenvironments demand, however, 3D electronic scaffolds with well-controlled geometries and functional-component distributions. This work presents the development of flexible 3D electronic scaffolds with precisely defined dimensions and microelectrode configurations formed using a process that relies on geometric transformation of 2D precursors by compressive buckling. It demonstrates a capability to fabricate these constructs in diverse 3D architectures and/or electrode distributions aimed at achieving an enhanced level of control and regulation of tissue function relatively to that of other approaches. In addition, this work presents the integration of these 3D electronic scaffolds within engineered 3D cardiac tissues, for monitoring of tissue function, controlling tissue contraction through electrical stimulation, and initiating on-demand, local release of drugs, each through well-defined volumetric spaces. These ideas provide opportunities in fields ranging from in vitro drug development to in vivo tissue repair and many others.

3D electronic scaffolds↗