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At least 775 records · Page 43

Insights into the action of phylogenetically diverse microbial expansins on the structure of cellulose microfibrils

Microbial expansins (EXLXs) are non-lytic proteins homologous to plant expansins involved in plant cell wall formation. Due to their non-lytic cell wall loosening properties and potential to disaggregate cellulosic structures, there is considerable interest in exploring the ability of microbial expansins (EXLX) to assist the processing of cellulosic biomass for broader biotechnological applications. Herein, EXLXs with different modular structure and from diverse phylogenetic origin were compared in terms of ability to bind cellulosic, xylosic, and chitinous substrates, to structurally modify cellulosic fibrils, and to boost enzymatic deconstruction of hardwood pulp. Five heterogeneously produced EXLXs (Clavibacter michiganensis; CmiEXLX2, Dickeya aquatica; DaqEXLX1, Xanthomonas sacchari; XsaEXLX1, Nothophytophthora sp.; NspEXLX1 and Phytophthora cactorum; PcaEXLX1) were shown to bind xylan and hardwood pulp at pH 5.5 and CmiEXLX2 (harboring a family-2 carbohydrate-binding module) also bound well to crystalline cellulose. Small-angle X-ray scattering revealed a 20–25% increase in interfibrillar distance between neighboring cellulose microfibrils following treatment with CmiEXLX2, DaqEXLX1, or NspEXLX1. Correspondingly, combining xylanase with CmiEXLX2 and DaqEXLX1 increased product yield from hardwood pulp by ~ 25%, while supplementing the TrAA9A LPMO from Trichoderma reesei with CmiEXLX2, DaqEXLX1, and NspEXLX1 increased total product yield by over 35%. This direct comparison of diverse EXLXs revealed consistent impacts on interfibrillar spacing of cellulose microfibers and performance of carbohydrate-active enzymes predicted to act on fiber surfaces. These findings uncover new possibilities to employ EXLXs in the creation of value-added materials from cellulosic biomass.

09 BIOMASS FUELS↗

Iodine Effects on Medical Isotope Producer Delay & Guard Bed Temperature and Performance in Support of NA-23 Program

In support of NA-23’s objective to accelerate the establishment of a reliable commercial United States (U.S.) domestic supply of 99Mo produced without the use of highly enriched uranium (HEU), the Pacific Northwest National Laboratory (PNNL) was tasked with modeling the performance of activated carbon delay and guard beds that may be typical for non-HEU 99Mo production processes. The specific tasks accomplished by PNNL included calculations of long-term effects of iodine on delay bed performance and development of a finite element simulation to better understand delay bed performance under various scenarios specifically with radioxenon and radioiodine decay heating of the delay beds. The main issue of interest in this study is understanding the effect of iodine on the abatement performance of the beds if iodine is not sufficiently removed from gases prior to reaching the delay beds. Finite element simulations of delay bed performance were developed using COMSOL Multiphysics® Software. These simulations are based on partial differential equations that describe xenon and iodine adsorption, heat transfer and decay of radioxenon and radioiodine isotopes. Heat transfer in the activated carbon beds is simulated with a heat source tied to the decay of radioactive xenon and iodine species. These simulations were used to investigate delay bed temperature and hold up time using radioxenon and radioiodine activities and flowrates expected from a non-HEU production process. A bounding case scenario was simulated, where all the iodine was released into the delay beds due to insufficient guarding of the delay beds. In addition, preliminary investigations of the guard beds were conducted.

07 ISOTOPE AND RADIATION SOURCES↗

In-Situ Species Concentration Measurements In Ammonia-Mix Flames Using Ftir Spectroscopy

Hydrogen and ammonia represent two carbon-free fuel sources that could be used in place of current fossil energy sources in combustion systems. To develop optimized ammonia combustion systems, validated modeling tools are needed. In the open literature, it has been shown that the complex chemistry associated with fuel-bound nitrogen contained in ammonia differs greatly from natural gas or hydrogen combustion. As a result, several new chemical kinetic mechanisms have been developed. Many of these mechanisms have been validated experimentally, however this has primarily focused on bulk parameters such as laminar flame speed and ignition delay time. Critically, high quality measurements of species concentrations are needed under controlled conditions which are easily represented by simple models. In this paper, direct, in-situ measurements of species concentrations and gas temperature are performed in a laminar flat-flame burner. This arrangement enables comparison with 1D model predictions, better isolating chemical kinetics from the fluid dynamics. Quantitative species concentrations are determined by absorption spectroscopy using an FTIR spectrometer. Fuel compositions representative of cracked ammonia (NH 3 /H 2 ) and ammonia-natural gas (NH 3 /CH 4 ) are considered for rich and lean equivalence ratios. A major focus of the paper is on the selection of spectral features for nitric oxide and ammonia and correcting for large amounts of baseline H 2 O absorption.

36 MATERIALS SCIENCE↗

Quarter 4 Report: Report on Final Findings and Opportunities for Future Work in the Use of Mixed Precision in Iterative Solvers

The fourth quarter of the project was spent developing an error analysis of the s-step Lanczos and CG algorithms. Our theoretical bounds and numerical experiments show that the numerical behavior of the algorithm can be significantly improved by using extra precision in a small part of the computation related to the computation and application of the Gram matrix. We have published a technical report which includes all steps of the analysis [8]; a shortened version for journal submission is in preparation. We plan to submit this paper in the following weeks. Activities related to this also include a collaboration with Ichitaro Yamazaki on gathering performance results for these new mixed precision s-step Krylov subspace methods using single/double precision on GPUs. Namely, we would like to obtain performance results that show that the performance overhead of using double the working precision in these select computations is minimal. Other activities include attending biweekly xSDK meetings and presenting a pitch talk on this work to the group on February 25, 2021. In the remainder of the document, we summarize our findings on the potential for mixed precision in classical Krylov subspace methods and s-step Krylov subspace methods, as well as key opportunities for future work.

97 MATHEMATICS AND COMPUTING↗

Organic Macromolecular materials for Efficient Transport Properties in Light-Energy Conversion Applications. Final Report

We are grateful for the Department of Energy for support of this research related to the improvement of power conversion efficiency of organic photovoltaic architectures over the years. As we noted at the beginning and now, the fundamental photophysical pathways that connect the absorption of light to the production of charge carriers remain elusive in spite of continuing experimental and theoretical efforts. Our investigations were directed toward gaining information about the mechanism of this ultrafast, long-range charge separation in photovoltaic systems with non-fullerene acceptors. This problem is still of high importance for the organic photovoltaics because solving this problem will allow us to minimize the contribution of the geminate recombination and trapping the charges in bound charge transfer states. Extremely low charge separation driving energy specific to non-fullerene acceptor systems reduces the energy loss in organic photovoltaic cells making them competitive with inorganic and perovskite photovoltaic systems. A major accomplishment of this study was to detail the long-range ballistic charge separation in donor-non-fullerene acceptor photovoltaic systems. We have successfully probed the spatial structure of ultrafast long-range (~40nm) ballistic charge separation in donor-non-fullerene acceptor photovoltaic system. We performed a systematic investigation of the delocalized states in their connection to the efficient long-range charge separation using the pulse pair interferometric near-field microscopy method. This method possesses unique capability of detecting coherent effects with spatial resolution of few tens of nanometers. These measurements allowed us the determination of delocalized excitations locally in a thin film photovoltaic system and to be connected to the long-range charge separation and the power conversion efficiency. We also investigated long-lived coupled triplet pairs in a singlet fission process for the possibility of concerted extraction of two electrons from triplet entangled states. New experimental and theoretical approaches of the concerted double electron extraction were carried out. The impact of this work is the development of important structure-property relationships to the design criteria of more efficient organic photovoltaic cells in accordance with the BES mission.

14 SOLAR ENERGY↗

In-Situ Species Concentration Measurements in Ammonia-Mix Flames Using FTIR Spectroscopy

Hydrogen and ammonia represent two carbon-free fuel sources that could be used in place of current fossil energy sources in combustion systems. To develop optimized ammonia combustion systems, validated modeling tools are needed. In the open literature, it has been shown that the complex chemistry associated with fuel-bound nitrogen contained in ammonia differs greatly from natural gas or hydrogen combustion. As a result, several new chemical kinetic mechanisms have been developed. Many of these mechanisms have been validated experimentally, however this has primarily focused on bulk parameters such as laminar flame speed and ignition delay time. Critically, high quality measurements of species concentrations are needed under controlled conditions which are easily represented by simple models. In this paper, direct, in-situ measurements of species concentrations and gas temperature are performed in a laminar flat-flame burner. This arrangement enables comparison with 1D model predictions, better isolating chemical kinetics from the fluid dynamics. Quantitative species concentrations are determined by absorption spectroscopy using an FTIR spectrometer. Fuel compositions representative of cracked ammonia (NH3/H2) and ammonia-natural gas (NH3/CH4) are considered for rich and lean equivalence ratios. A major focus of the paper is on the selection of spectral features for nitric oxide and ammonia and correcting for large amounts of baseline H2O absorption.

Bedick, Clinton↗

Zwitterionic Photocurable Resin for High‐Resolution 3D Printing of Ultralow‐Fouling Microstructures

High‐resolution 3D printing technologies are enabling a new generation of microstructured materials for applications where biocompatibility is critical. However, most conventional 3D‐printable resins yield materials that exhibit trade‐offs between antifouling properties and mechanical robustness, limiting their applicability in living systems. In nature, zwitterionic surface groups form tightly bound hydration layers that act as effective barriers against protein and cell attachment. Inspired by this strategy, a zwitterionic acrylamide‐based photoresist—carboxybetaine di‐methacrylamide (CBDA)—is developed for projection‐based vat photopolymerization, enabling the fabrication of complex microarchitectures with exceptional antifouling properties. The bifunctional monomer allows the formation of dense, cross‐linked networks that resist swelling while maintaining a high density of zwitterionic groups. Printed structures exhibit strong resistance to protein and cell adhesion, as confirmed by porcine blood assays, alongside robust mechanical performance. As a demonstration, a tubular structure featuring a negative Poisson's ratio lattice is printed to showcase structural fidelity and versatility. This resin formulation offers a broadly applicable strategy for fabricating microscale devices and surfaces where antifouling performance and structural integrity are both essential—spanning biomedical interfaces, soft robotics, and beyond.

3D printing↗

Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: Comparison with linear subspace techniques

Natural convection in porous media is a highly nonlinear multiphysical problem relevant to many engineering applications (e.g., the process of CO 2 sequestration). Here, we extend and present a non-intrusive reduced order model of natural convection in porous media employing deep convolutional autoencoders for the compression and reconstruction and either radial basis function (RBF) interpolation or artificial neural networks (ANNs) for mapping parameters of partial differential equations (PDEs) on the corresponding nonlinear manifolds. To benchmark our approach, we also describe linear compression and reconstruction processes relying on proper orthogonal decomposition (POD) and ANNs. Further, we present comprehensive comparisons among different models through three benchmark problems. The reduced order models, linear and nonlinear approaches, are much faster than the finite element model, obtaining a maximum speed-up of 7 × 10 6 because our framework is not bound by the Courant–Friedrichs–Lewy condition; hence, it could deliver quantities of interest at any given time contrary to the finite element model. Our model’s accuracy still lies within a relative error of 7% in the worst-case scenario. We illustrate that, in specific settings, the nonlinear approach outperforms its linear counterpart and vice versa. We hypothesize that a visual comparison between principal component analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) could indicate which method will perform better prior to employing any specific compression strategy.

97 MATHEMATICS AND COMPUTING↗

A rigorous physics-based enhanced parameter estimation (EPE) methodology for calibration of building energy simulations

Buildings rarely perform as designed/simulated and there are numerous tangible benefits if this gap is reconciled. A new scientifically rigorous yet pragmatic methodology for calibrating building energy simulations - called Enhanced Parameter Estimation (EPE) - is proposed that allows physically relevant parameter estimation rather than a blind force-fit to energy use data. Starting with a rapidly created simulation model, calibration is performed in two stages: (a) building shell calibration with the HVAC system replaced by an ideal system that meets the loads (b) HVAC system calibration with the building shell and all internal loads replaced by a box with only process loads. In the first stage, EPE identifies a small number of high-level heat flows in the energy balance, calculates them with specifically tailored individual driving functions, introduces physically significant parameters to best accomplish energy balance, and, estimates the parameters and their uncertainty bounds. Calibration is thus done with corrective heat flows without any arbitrary tuning of input parameters. Calibration accuracy is enhanced by machine learning of the residual errors. The EPE methodology is demonstrated by means of: a synthetic building and an actual 75,000 sq. ft. building in Pennsylvania. Future work needed for widespread application is discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multi-fidelity thermal modeling of laser powder bed additive manufacturing

Laser powder bed fusion (LPBF) Additive manufacturing (AM) has attracted interest as an agile method of building production metal parts to reduce design-build-test cycle times for systems. However, predicting part performance is difficult due to inherent process variabilities. This makes qualification challenging. Computational process models have attempted to address some of these challenges, including mesoscale, full physics models and reduced fidelity conduction models. The goal of this work is credible multi-fidelity modeling of the LPBF process by investigating methods for estimating the error between models of two different fidelities. Two methods of error estimation are investigated, adjoint-based error estimation and Bayesian calibration. Adjoint-based error estimation is found to effectively bounding the error between the two models, but with very conservative bounds, making predictions highly uncertain. Bayesian parameter calibration applied to conduction model heat source parameters is found to effectively bound the observed error between the models for melt pool morphology quantities of interest. However, the calibrations do not effectively bound the error in heat distribution.

36 MATERIALS SCIENCE↗

Searching for neutrino polarizability at DUNE

We perform an initial study of DUNE’s sensitivity to enhanced neutrino polarizability within models of light scalar mediators. We identify two possible signatures of polarizability due to neutrino scattering on electrons and due to coherent scattering on argon nuclei. These result in either one or two separated electromagnetic showers, respectively, with no associated hadronic activity. For each signature we compute the signal rates and the relevant backgrounds, obtaining the projected reach of the DUNE near detector. We then compare this with the current astrophysical and terrestrial bounds on light scalar models coupling to neutrinos and/or photons.

Carey, Sam [Wayne State U.] (ORCID:000900029607531↗

How Does Bending the Uranyl Unit Influence Its Spectroscopy and Luminescence?

We report bent uranyl complexes can be formed with chloride ligands and 1,10-phenanthroline (phen) ligands bound to the equatorial and axial planes of the uranyl(VI) moiety, as revealed by the crystal structures, IR and Raman spectroscopy, and quantum-chemical calculations. With the goal of probing the influence of chloride and phenanthroline coordination enforcing the bending on the absorption and emission spectra of this complex, spin–orbit time-dependent density functional theory calculations for the bare uranyl complexes as well as for the free UO 2 Cl 2 subunit and the UO 2 Cl 2 (phen) 2 complex were performed. The emission spectra have been fully simulated by ab initio methods and compared to experimental photoluminescence spectra, recorded for the first time for UO 2 Cl 2 (phen) 2 . Notably, the bending of uranyl in UO2Cl2 and UO 2 Cl 2 (phen) 2 triggers excitations of the uranyl bending mode, yielding a denser luminescence spectrum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Supramolecular assemblies of polybenzimidazole and aromatic polycarboxylic acids with superior mechanical and H 2 /CO 2 separation properties

Aromatic polycarboxylic acids complex with imidazoles, forming supramolecular assemblies. Herein, we demonstrate that polybenzimidazole (PBI) can be augmented by aromatic polycarboxylic acids, including phthalic acid (PA), trimesic acid (TMA), and pyromellitic acid (PMA), and the resulting supramolecular assemblies exhibit attractive H 2 /CO 2 separation performance for precombustion carbon capture. The acid doping decreases the free volume and gas permeability but increases H 2 /CO 2 selectivity, which can be correlated with the molar ratio of the protons to PBI repeating units in the assemblies. Increasing the temperature decreases the H 2 /CO 2 selectivity because of weakened interactions. When challenged with model gas mixtures, a supramolecular assembly based on TMA shows H 2 /CO 2 separation properties superior to state-of-the-art materials and above Robeson's upper bound. Furthermore, this study elucidates the fruitful harnessing of dynamic non-covalent bonds to design robust and highly selective membranes for industrial gas separations.

36 MATERIALS SCIENCE↗

Trainability of Dissipative Perceptron-Based Quantum Neural Networks

Several architectures have been proposed for quantum neural networks (QNNs), with the goal of efficiently performing machine learning tasks on quantum data. Rigorous scaling results are urgently needed for specific QNN constructions to understand which, if any, will be trainable at a large scale. Here, we analyze the gradient scaling (and hence the trainability) for a recently proposed architecture that we call dissipative QNNs (DQNNs), where the input qubits of each layer are discarded at the layer’s output. We find that DQNNs can exhibit barren plateaus, i.e., gradients that vanish exponentially in the number of qubits. Moreover, we provide quantitative bounds on the scaling of the gradient for DQNNs under different conditions, such as different cost functions and circuit depths, and show that trainability is not always guaranteed. Here our work represents the first rigorous analysis of the scalability of a perceptron-based QNN.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Considerations for Defining G-Values for Aluminum-Clad Spent Nuclear Fuel

Sealed-canister dry storage of aluminum-clad spent nuclear fuel (ASNF) generated by research reactors is an alternative to current storage and disposition pathways as directed by the U.S. Department of Energy. The major challenge faced for this storage approach is radiolytic H 2 generation, including from the aluminum (oxy)hydroxide layers on the surface of ASNF. Experimental and modeling activities have been carried out to characterize the radiolytic yield as part of a DOE-sponsored research program to develop the technical basis for ASNF dry storage. The G-value is a commonly way to report results of radiolysis testing and is defined as the radiolytic yield of a species (e.g. molecular hydrogen) per unit radiation energy deposited into the material system. An independent technical review of the ASNF dry storage technical basis performed by Pacific Northwest National Laboratory raised questions about differences in G-value definitions used for experiments on ASNF surrogates consisting of aluminum samples with adherent (oxy)hydroxides compared to G-values reported in prior literature and how the magnitudes compared between different studies. Material systems resembling ASNF pose complications for measuring/defining G-values to predict the evolution of H 2 in a sealed canister, including i) accounting for radiolytic yields potentially arising from multiple sources, i.e., residual free (vapor), physisorbed, and chemisorbed/chemically bound waters; ii) deciding what portions of the multi-material system to include in the absorbed energy (radiation dose) calculation, considering possible energy exchange between materials as well as measurement limitations, and iii) capturing variations in G-value associated with non-linear yield vs. dose curves and/or dependence on the cover gas. This report summarizes previous literature information on radiolytic H 2 generation and associated G-values from mixed-material systems (generally oxides in contact with water or organic compounds) and from (oxy)hydroxides/hydrates to compare with the definitions and values for ASNF surrogate samples containing adherent aluminum (oxy)hydroxides.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Features of mid- and high-latitude low-level clouds and their relation to strong aerosol effects in the Energy Exascale Earth System Model version 2 (E3SMv2)

The E3SMv2 model, like various other global models that include representations of aerosol–cloud interactions, uses an empirically chosen lower bound on the simulated in-cloud cloud droplet number concentration (CDNC) to help constrain the effective radiative forcing of anthropogenic aerosols, ERFaer. This study identifies where ultra-low CDNCs (i.e., concentrations lower than 10 cm−3) occur in the stratiform and shallow convective clouds simulated by E3SMv2 and which of the occurrences have the strongest impact on ERF aer . Process-level analyses are presented to reveal characteristics of the cloud droplet formation and removal processes associated with impactful ultra-low CDNCs. Simulations performed with present-day emissions show that ultra-low CDNCs are most frequently found over the mid- and high-latitude oceans in both hemispheres, while the occurrences are also frequent in polluted continental regions despite the high aerosol concentrations. Ultra-low CDNCs with the largest impacts on the simulated regional and global mean ERF aer are found in the lower troposphere in the Northern Hemisphere middle and high latitudes. These cases are typically associated with large cloud fractions, strong water vapor condensation, weak turbulence, and lack of cloud droplet nucleation from aerosol activation. Under such atmospheric conditions, boosting aerosol activation and enhancing turbulent mixing of cloud droplet number can increase the simulated CDNCs, although the magnitude of the global mean ERF aer increases undesirably. The reason for this model behavior is discussed. Overall, our study suggests that mid- and high-latitude low-level stratus occurring under weak turbulence is a cloud regime worth further investigating for the purpose of identifying and addressing the root causes of ultra-low CDNCs and strong ERF aer in E3SM.

Aerosol-Cloud Interaction↗

Crossing symmetry, transcendentality and the Regge behaviour of 1d CFTs

We develop the technology for Polyakov-Mellin (PM) bootstrap in one- dimensional conformal field theories (CFT 1 ). By adding appropriate contact terms, we bootstrap various effective field theories in AdS 2 and analytically compute the CFT data to one loop. The computation can be extended to higher orders in perturbation theory, if we ignore mixing, for any external dimension. We develop PM bootstrap for O(N) theories and derive the necessary contact terms for such theories (which also involves a new higher gradient contact term absent for N = 1). We perform cross-checks which include considering the diagonal limit of the 2d Ising model in terms of the 1d PM blocks. As an independent check of the validity of the results obtained with PM bootstrap, we propose a suitable basis of transcendental functions, which allows to fix the four-point correlators of identical scalar primaries completely, up to a finite number of ambiguities related to the number of contact terms in the PM basis. We perform this analysis both at tree level (with and without exchanges) and at one loop. We also derive expressions for the corresponding CFT data in terms of harmonic sums. Finally, we consider the Regge limit of one-dimensional correlators and derive a precise connection between the latter and the large-twist limit of CFT data. Exploiting this result, we study the crossing equation in the three OPE limits and derive some universal constraints for the large-twist limit of CFT data in Regge-bounded theories with a finite number of exchanges.

1/N expansion↗

Portable C++ Code that can Look and Feel Like Fortran Code with Yet Another Kernel Launcher (YAKL)

This paper introduces the Yet Another Kernel Launcher (YAKL) C++ portability library, which strives to enable user-level code with the look and feel of Fortran code. The intended audience includes both C++ developers and Fortran developers unfamiliar with C++. The C++ portability approach is briefly explained, YAKL’s main features are described, and code examples are given that demonstrate YAKL’s usage. YAKL fills a niche capability important particularly to scientific applications seeking to port Fortran code quickly to a portable C++ library. YAKL places heavy emphasis on simplicity, readability, and productivity with performance mainly emphasizing Graphics Processing Units (GPUs). Central to YAKL’s ability to allow Fortran-like user-level code are three features: (1) a multi-dimensional Array class that allows Fortran behavior; (2) a limited library of Fortran intrinsic functions; and (3) an efficient pool allocator that transparently enables cheap frequent allocations and deallocations of YAKL Arrays. While YAKL allows Fortran-style code, it also allows Arrays that exhibit C-like behavior as well, including row-major index ordering and lower bounds of “0”. YAKL currently supports CPUs, CPU threading, and Nvidia, AMD, and Intel GPUs.

97 MATHEMATICS AND COMPUTING↗