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At least 1,045 records · Page 58

NWChem: Past, present, and future

Specialized computational chemistry packages have permanently reshaped the landscape of chemical sciences by providing tools to support and guide the experimental effort and for prediction of chemical and materials properties. In this regard, a special role has been played by electronic structure packages where complex chemical and materials processes can be modeled using first-principle-driven methodologies. Over the last few decades, the rapid development of computing technologies and a tremendous increase in computational power has offered a unique chance to study complex chemical transformations using sophisticated and predictive many-body techniques to describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, a critical role has been played by novel parallel algorithms capable of taking advantage of computational resources to address polynomial scaling of electronic structure methods. NWChem was among the first electronic structure codes that focused on delivering scalable performance for electronic structure simulations. Herein, we briefly review the NWChem suite of computational codes including its history, design principles, parallel tools, current capabilities, outreach and outlook.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A DG-IMEX Method for Two-moment Neutrino Transport: Nonlinear Solvers for Neutrino–Matter Coupling

Neutrino-matter interactions play an important role in core-collapse supernova (CCSN) explosions as they contribute to both lepton number and/or four-momentum exchange between neutrinos and matter, and thus act as the agent for neutrino-driven explosions. Due to the multiscale nature of neutrino transport in CCSN simulations, an implicit treatment of neutrino-matter interactions is desired, which requires solutions of coupled nonlinear systems in each step of the time integration scheme. In this paper we design and compare nonlinear iterative solvers for implicit systems with energy coupling neutrino-matter interactions commonly used in CCSN simulations. Specifically, we consider electron neutrinos and antineutrinos, which interact with static matter configurations through the Bruenn 85 opacity set. The implicit systems arise from the discretization of a nonrelativistic two-moment model for neutrino transport, which employs the discontinuous Galerkin (DG) method for phase-space discretization and an implicit-explicit (IMEX) time integration scheme. In the context of this DG-IMEX scheme, we propose two approaches to formulate the nonlinear systems — a coupled approach and a nested approach. For each approach, the resulting systems are solved with Anderson-accelerated fixedpoint iteration and Newton’s method. The performance of these four iterative solvers has been compared on relaxation problems with various degree of collisionality, as well as proto-neutron star deleptonization problems with several matter profiles adopted from spherically symmetric CCSN simulations. Here, numerical results suggest that the nested Anderson-accelerated fixed-point solver is more efficient than other tested solvers for solving implicit nonlinear systems with energy coupling neutrino-matter interactions.

79 ASTRONOMY AND ASTROPHYSICS↗

Activity‐Based Protein Profiling – Enabling Phenotyping of Host‐Associated and Environmental Microbiomes

Abstract Host‐associated and environmental microbiomes play central roles in human health, biogeochemical cycling, response to ecosystem change, and agriculture. Scientific approaches that can reveal the functional activities that contribute to observed phenotypes are needed in microbiome research. Broad characterization of the functional activity of microbes within microbiomes is currently hampered by approaches that rely on inference of function from metagenomes or indirect measurements. Activity‐based protein profiling is uniquely positioned to overcome these challenges and reveal the protein‐level mechanisms associated with microbiome phenotypes. In this review we describe the progress made to date using ABPP in gut microbiome, plant‐microbe interaction, and soil microbiome research, and suggest how ABPP data can be coupled with advanced computational methods to enable phenotype prediction and bioengineering of microbiomes for applied purposes.

59 BASIC BIOLOGICAL SCIENCES↗

MAPredict: Static Analysis Driven Memory Access Prediction Framework for Modern CPUs

Application memory access patterns are crucial in deciding how much traffic is served by the cache and forwarded to the dynamic random-access memory (DRAM). However, predicting such memory traffic is difficult because of the interplay of prefetchers, compilers, parallel execution, and innovations in manufacturer-specific micro-architectures. This research introduced MAPredict, a static analysis-driven framework that addresses these challenges to predict last-level cache (LLC)-DRAM traffic. By exploring and analyzing the behavior of modern Intel processors, MAPredict formulates cache-aware analytical models. MAPredict invokes these models to predict LLC-DRAM traffic by combining the application model, machine model, and user-provided hints to capture dynamic information. MAPredict successfully predicts LLC-DRAM traffic for different regular access patterns and provides the means to combine static and empirical observations for irregular access patterns. Evaluating 130 workloads from six applications on recent Intel micro-architectures, MAPredict yielded an average accuracy of 99% for streaming, 91% for strided, and 92% for stencil patterns. By coupling static and empirical methods, up to 97% average accuracy was obtained for random access patterns on different micro-architectures.

Monil, M. A. H.↗

Cost-Performance Trade-off in thermoelectric air conditioning system with graded and constant material properties

Thermoelectric (TE) air cooling is a solid-state technology that has the potential to replace conventional vapor compression-based air conditioning. In this paper, we present a detailed system-level modeling for thermoelectric air conditioning system with position-dependent (graded) and constant material properties. Strategies for design optimization of the system are provided in terms of cost-performance trade-off. Realistic convection heat transfer at both sides of the system are taken into account in our modeling. Here, the effects of convection heat transfer coefficients, air flowrate, and thermoelectric material properties are investigated with varying key parameters such as TE leg thickness, module fill factor, and input current. Both constant material properties and graded properties are considered for the TE materials, and they are compared in terms of the degree of cooling, coefficient of performance (COP), and power consumption. For graded materials, we employ one-dimensional finite element methods to solve the coupled electrical and thermal current equations with arbitrary profile of material properties varying with position along the TE legs. We find that graded materials can enhance the degree of cooling, but only at the expense of COP, compared to the case of constant property materials. With constant material properties of ZT = 1 and relatively low electric current, the power consumption of TE coolers can be lower than those of conventional air conditioners at an equivalent cooling capacity. Considering additional advantages such as demand-flexible operation, low noise, and high scalability, thermoelectric cooling could be a competitive technology for future air conditioning applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Sylvester-preconditioned adaptive-rank implicit time integrators for advection-diffusion equations with variable coefficients

Here, we consider the adaptive-rank integration of multi-dimensional time-dependent advection-diffusion partial differential equations (PDEs) with variable coefficients. We employ a standard finite-difference method for spatial discretization coupled with high-order diagonally implicit Runge-Kutta temporal schemes. The discrete equation is a generalized Sylvester equation (GSE), which we solve with a projection-based adaptive-rank algorithm structured around two key strategies: (i) constructing dimension-wise subspaces using a novel atypical extended Krylov strategy, and (ii) efficiently solving the basis coefficient matrix with a preconditioned GMRES solver. The low-rank decomposition is performed in 2D using SVD and with high-order SVD (HOSVD) in 3D to represent the tensor in a compressed Tucker format. For d-dimensional problems (here, d = 2 or 3), the computational complexity and memory storage of the approach are found numerically to scale as and $\mathscr{O}(Nr^2) + \mathscr{O} (r^{d+1})$ and $\mathscr{O}(Nr) + \mathscr{O} (r^{d})$, respectively, with the one-dimensional resolution and the maximal rank during the Krylov iteration (which we find to be largely independent of on our numerical examples). We present numerical examples that illustrate the advertised properties of the algorithm.

97 MATHEMATICS AND COMPUTING↗

Depth-resolved thermal conductivity and damage in swift heavy ion irradiated metal oxides

We investigated thermal transport in swift heavy ion (SHI) irradiated insulating single crystalline oxide materials: yttrium aluminum garnet- Y 3 Al 5 O 12 (YAG), sapphire (Al 2 O 3 ), zinc oxide (ZnO) and magnesium oxide (MgO) irradiated by 167 MeV Xe ions at 10 12 – 10 14 ions/cm 2 fluences. Depth profiling of the thermal transport on nano- and micro- meter scales was assessed by time-domain thermoreflectance (TDTR) and modulated thermoreflectance (MTR) methods, respectively. This combination allowed us to isolate the conductivities of different sub-surface damage-regions characterized by their distinct microstructure evolution regimes. Thermal conductivity degradation in SHI irradiated YAG and Al 2 O 3 is attributed to formation of ion tracks and subsequent amorphization, while in ZnO and MgO it is mostly due to point defects. Additionally, notably lower conductivity when probed by very low penetrating thermal waves is consistent with surface hillock formation. An analytical model based on Klemens-Callaway method for thermal conductivity coupled with a simplified microstructure evolution capturing saturation in defect concentration was used to obtain depth dependent damage across the ion impacted region. The studies showed that YAG has the highest damage profile resulting in the less dependence of thermal conductivity with the depth, while MgO on the contrary has the strongest dependence. The presented work sheds new light on how SHI induced defects affect thermal transport degradation and recovery of oxide ceramics as promising candidates for next generation nuclear reactor applications.

36 MATERIALS SCIENCE↗

Computational studies of hydraulic stressors for biological performance assessment in a hydropower plant with Kaplan turbine

We report Hydropower is currently one of the preeminent sources of renewable energy in the United States and globally. Hydropower plants also have detrimental impacts on the environment and ecology, including direct impacts to anadromous fish populations. The computational fluid dynamics (CFD) – based Biological Performance Assessment (BioPA) toolset is used for biological evaluations of fish passage through hydropower plants. The hydraulic environment of a hydropower plant was evaluated using CFD coupled with discrete element method (DEM) simulations. The predicted flow field and particle collision rate were validated against the experimental data in a water flume that has an idealized hydroturbine distributor geometry. Flow simulations were conducted to evaluate the hydraulic stressors, such as nadir pressure, fluid shear, runner collision, in a physical scale in a hydropower plant with Kaplan turbine which are responsible for injury and mortality of fish in a downstream migration. The cumulative exposure probability for the nadir pressure and collision with turbine runner was found to decrease with increased discharge rate. The lowest discharge rate shows the higher value of cumulative shear exposure probability. The maximum value of collision velocity increases with increased discharge rate. We offer the conclusions that will help in understanding various hydraulic stressors for biological assessment for environmentally sustainable hydroturbine passage.

13 HYDRO ENERGY↗

Nanodomain Formation and Temperature-Dependent Diffusion in Deep Eutectic Solvents Revealed by Single-Molecule Tracking

Deep eutectic solvents (DESs) are typically regarded as homogeneous liquids; however, recent work shows that many exhibit nanoscale structural heterogeneity. Most studies attribute these nanoscale features to short-range chemical interactions. It is still unclear whether a long-range physical mechanism also plays a role. Here, in this study, we examined the nanoscale structure in two hydrophobic DESs, 1:3 tetrabutylammonium bromide: l-menthol (DES-butyl) and 1:3 tetraoctylammonium bromide: l-menthol (DES-octyl). The notation 1:3 represents the molar ratio of the hydrogen bond acceptors to hydrogen bond donors used in the synthesis of the DESs. Single-molecule tracking (SMT) coupled with maximum entropy method (MEM) analysis was used to measure the number of diffusion populations of a dilute concentration of an added fluorescent probe. The presence of more than one population of diffusion coefficients indicates the existence of multiple local environments for the fluorescent probe (i.e., nanoscale structures in the DES). DES-butyl showed a relatively narrow diffusion coefficient distribution centered at 0.55 μm 2 /s, whereas DES-octyl displayed two distinct diffusing populations at 20 °C, with diffusion coefficients of 0.12 μm 2 /s and 0.53 μm 2 /s for the slow and fast populations, respectively. As DES-octyl was heated, the slow-diffusing population steadily diminished and disappeared above ∼30 °C, indicating that the nanodomains present at lower temperatures collapse as the liquid becomes more thermodynamically mixed. This temperature-dependent homogenization is consistent with a physical mechanism of nanostructure formation, for example, liquid–liquid phase separation (LLPS), wherein the structure is not driven solely by specific chemical interactions. The SMT-MEM results suggest that a long-range physical mechanism is the most plausible origin of the measured nanoscale structure in DES-octyl.

Opare-Addo, Jemima [Ames Laboratory (AMES), Ames, ↗

Decoupling Carrier Dynamics and Energy Transport in Ultrafast Near-Field Nanoscopy

Ultrafast near-field optical nanoscopy has emerged as a powerful platform to characterize low-dimensional materials. While analytical and numerical models have been established to account for photoexcited carrier dynamics, quantitative evaluation of the associated pulsed laser heating remains elusive. Here, we decouple the photocarrier density and temperature increase in near-field nanoscopy by integrating the two-temperature model (TTM) with finite-difference time-domain (FDTD) simulations. These results reveal that the electron–phonon coupling in a silicon film after femtosecond laser excitation is most pronounced within approximately 3 ps–substantially shorter than the photocarrier decay time scale at tens of picoseconds. Moreover, the coupled TTM-FDTD method indicates that ultrafast laser heating can cause up to a 14% variation in the near-field signal at a 220 μJ/cm 2 pump pulse fluence. Our numerical results are further validated by transient experiments, highlighting the potential of this method for investigations of carrier and thermal phenomena in emerging nanomaterials and nanodevices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Pentavalent Uranium Enriched Mineral Surface under Electrochemically Controlled Reducing Environments

Redox reactions of uranium (U) in aqueous environments have important impacts on the mobility and isotopic fractionation of U in the geosphere. Pentavalent U as the cationic uranyl ion, UO 2 +, is rarely observed in naturally occurring samples because of its limited lifetime, but it may be an important intermediate state controlling the redox kinetics between hexavalent and tetravalent U. Increasing evidence has indicated that U(V) can be stabilized under laboratory conditions. Here, we showed that U(V) is the dominant species on the magnetite (Fe 3 O 4 ) surface under reducing conditions controlled by electrochemical methods. Cyclic voltammetry reveals coupled redox peaks corresponding to the U(VI)O 2 2+ /U(V)O 2+ one-electron redox reaction. Magnetite electrodes polarized at a series of potentials to reduce U(VI)O 2 2+ were characterized by X-ray photoelectron spectroscopy (XPS), X-ray absorption spectroscopy (XAS), and Auger electron mapping. Overall, the results showed that up to twice the amount of U(V) to U(VI) was present on the magnetite surface. U(V) adopted a typical uranyl-type structure, and the U coverage on the magnetite surface increased with decreasing potentials. The formation of mixed-valence U(V)/U(VI) species on the surface of magnetite may hinder the U(V) disproportionation reaction, thereby eliminating the presence of tetravalent U. These results show that U(V) can exist over short time scales as the dominant U species on mineral surfaces under selected reducing conditions by the controlled polarization of a mineral electrode.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanoengineering room temperature ferroelectricity into orthorhombic SmMnO 3 films

Orthorhombic R MnO 3 ( R = rare-earth cation) compounds are type-II multiferroics induced by inversion-symmetry-breaking of spin order. They hold promise for magneto-electric devices. However, no spontaneous room-temperature ferroic property has been observed to date in orthorhombic R MnO 3 . Here, using 3D straining in nanocomposite films of (SmMnO 3 ) 0.5 ((Bi,Sm) 2 O 3 ) 0.5 , we demonstrate room temperature ferroelectricity and ferromagnetism with T C,FM ~ 90 K, matching exactly with theoretical predictions for the induced strain levels. Large in-plane compressive and out-of-plane tensile strains (-3.6% and +4.9%, respectively) were induced by the stiff (Bi,Sm) 2 O 3 nanopillars embedded. The room temperature electric polarization is comparable to other spin-driven ferroelectric R MnO 3 films. Also, while bulk SmMnO 3 is antiferromagnetic, ferromagnetism was induced in the composite films. The Mn-O bond angles and lengths determined from density functional theory explain the origin of the ferroelectricity, i.e. modification of the exchange coupling. Our structural tuning method gives a route to designing multiferroics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Tuning the electronic structure of Ag-Pd alloys to enhance performance for alkaline oxygen reduction

Alloying is a powerful tool that can improve the electrocatalytic performance and viability of diverse electrochemical renewable energy technologies. Herein, we enhance the activity of Pd-based electrocatalysts via Ag-Pd alloying while simultaneously lowering precious metal content in a broad-range compositional study focusing on highly comparable Ag-Pd thin films synthesized systematically via electron-beam physical vapor co-deposition. Cyclic voltammetry in 0.1 M KOH shows enhancements across a wide range of alloys; even slight alloying with Ag (e.g. Ag 0.1 Pd 0.9 ) leads to intrinsic activity enhancements up to 5-fold at 0.9 V vs. RHE compared to pure Pd. Based on density functional theory and x-ray absorption, we hypothesize that these enhancements arise mainly from ligand effects that optimize adsorbate–metal binding energies with enhanced Ag-Pd hybridization. This work shows the versatility of coupled experimental-theoretical methods in designing materials with specific and tunable properties and aids the development of highly active electrocatalysts with decreased precious-metal content.

25 ENERGY STORAGE↗

A scalable, biopolymer-based microenvironment for electrochemical CO 2 conversion to multicarbon products with current densities over 2 A cm −2

The electrochemical CO 2 reduction reaction (CO 2 RR) relies heavily on the surrounding microenvironment to promote formation of desirable multicarbon (C 2+ ) products. However, microenvironment control to achieve high C 2+ yields at industrially relevant current densities remains a crucial challenge. We report that chitosan, cellulose and chitin biopolymer coatings on CO 2 RR electrocatalysts enhance the microenvironment by increasing local CO 2 /CO concentration, reducing local water activity and providing suitable ion conductivity and local pH. This facile approach achieves C 2+ Faradaic efficiencies of 90 ± 1.7% at 1.6 A cm −2 and C 2+ Faradaic efficiency = 83 ± 3.2% at 2.2 A cm −2 with a formation rate of 5,926 μmol h −1 cm −2 . Importantly, within the cathode, these ion-conductive hydrophilic biopolymers can fully substitute traditional hydrophobic ionomers/binders, such as Nafion, challenging previous assumptions about the non-viability of hydrophilic materials for selective CO 2 RR due to excess interfacial H 2 O. These findings unveil key insights into microenvironment design to enhance C–C coupling through a simple method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Training calibration-based counterfactual explainers for deep learning models in medical image analysis

The rapid adoption of artificial intelligence methods in healthcare is coupled with the critical need for techniques to rigorously introspect models and thereby ensure that they behave reliably. This has led to the design of explainable AI techniques that uncover the relationships between discernible data signatures and model predictions. In this context, counterfactual explanations that synthesize small, interpretable changes to a given query while producing desired changes in model predictions have become popular. This under-constrained, inverse problem is vulnerable to introducing irrelevant feature manipulations, particularly when the model’s predictions are not well-calibrated. Hence, in this paper, we propose the TraCE (training calibration-based explainers) technique, which utilizes a novel uncertainty-based interval calibration strategy for reliably synthesizing counterfactuals. Given the wide-spread adoption of machine-learned solutions in radiology, our study focuses on deep models used for identifying anomalies in chest X-ray images. Using rigorous empirical studies, we demonstrate the superiority of TraCE explanations over several state-of-the-art baseline approaches, in terms of several widely adopted evaluation metrics. Our findings show that TraCE can be used to obtain a holistic understanding of deep models by enabling progressive exploration of decision boundaries, to detect shortcuts, and to infer relationships between patient attributes and disease severity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A theoretical investigation of the hydrolysis of uranium hexafluoride: the initiation mechanism and vibrational spectroscopy

Depleted uranium hexafluoride (UF 6 ), a stockpiled byproduct of the nuclear fuel cycle, reacts readily with atmospheric humidity, but the mechanism is poorly understood. Here we compare several potential initiation steps at a consistent level of theory, generating underlying structures and vibrational modes using hybrid density functional theory (DFT) and computing relative energies of stationary points with double-hybrid (DH) DFT. A benchmark comparison is performed to assess the quality of DH-DFT data using reference energy differences obtained using a complete-basis-limit coupled-cluster (CC) composite method. The associated large-basis CC computations were enabled by a new general-purpose pseudopotential capability implemented as part of this work. Dispersion-corrected parameter-free DH-DFT methods, namely PBE0-DH-D3(BJ) and PBE-QIDH-D3(BJ), provided mean unsigned errors within chemical accuracy (1 kcal mol -1 ) for a set of barrier heights corresponding to the most energetically favorable initiation steps. The hydrolysis mechanism is found to proceed via intermolecular hydrogen transfer within van der Waals complexes involving UF 6 , UF 5 OH, and UOF 4 , in agreement with previous studies, followed by the formation of a previously unappreciated dihydroxide intermediate, UF 4 (OH) 2 . The dihydroxide is predicted to form under both kinetic and thermodynamic control, and, unlike the alternate pathway leading to the UO 2 F 2 monomer, its reaction energy is exothermic, in agreement with observation. Finally, harmonic and anharmonic vibrational simulations are performed to reinterpret literature infrared spectroscopy in light of this newly identified species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Li + CaF → Ca + LiF chemical reaction under cold conditions

The calcium monofluoride (CaF) molecule has emerged as a promising candidate for precision measurements, quantum simulation, and ultracold chemistry experiments. Inelastic and reactive collisions of laser cooled CaF molecules in optical tweezers have recently been reported and collisions of cold Li atoms with CaF are of current experimental interest. In this paper, we report ab initio electronic structure and full-dimensional quantum dynamical calculations of the Li + CaF → LiF + Ca chemical reaction. The electronic structure calculations are performed using the internally contracted multi-reference configuration-interaction method with Davidson correction (MRCI + Q). An analytic fit of the interaction energies is obtained using a many-body expansion method. Furthermore, a coupled-channel quantum reactive scattering approach implemented in hyperspherical coordinates is adopted for the scattering calculations under cold conditions. Results show that the Li + CaF reaction populates several low-lying vibrational levels and many rotational levels of the product LiF molecule and that the reaction is inefficient in the 1–100 mK regime allowing sympathetic cooling of CaF by collisions with cold Li atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aluminosilicate-mediated C(sp 2 )–H alkylation of furans using allylic alcohols

Alkyl furans have a variety of applications and therefore numerous approaches exist for their synthesis. While these methods can be effective, there are various drawbacks largely associated with the waste generated. Herein we report a novel method for the direct coupling of readily available furans with allylic alcohols. These include terpenoid alcohols such as geraniol and prenol, which are readily available from renewable, bio-derived feedstocks. Furthermore, the reaction is facilitated using aluminosilicates, including zeolites. It was found that Y-type zeolites were highly effective at mediating the coupling with furan, giving the 2-alkylated furan high yields. While various allylic alcohols were effective for this reaction, the identity of the furan proved to have a drastic impact on reactivity. For substituted furans, the reaction proved most effective with an amorphous aluminosilicate and calculations later revealed potential key factors in further developing and generalizing this methodology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗