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Characterization of Embedded Sensors in Stainless Steel Test Articles and Design/Planning for MAGNET Testing

The nuclear industry is pursuing microreactors that can be factory assembled and deployed to remote regions for reliable power generation. One class of microreactors uses a monolithic metal core block coupled to heat pipes for heat rejection, which results in significant thermal stresses in the monolithic structures. This work describes the initial characterization and test plan for evaluating stainless steel test articles fabricated with embedded sensors for measuring heat pipe performance limits, as well as spatially distributed temperatures and strains during electrically heated thermal testing. The electrically heated testing will be performed in the non-nuclear Microreactor Agile Non-Nuclear Testbed and Single Primary Heat Extraction and Removal Emulator facilities located at Idaho National Laboratory. The goals of these tests are to (1) accurately monitor temperature and strain distributions that result from differential thermal expansion in the test articles and (2) quantify heat rejection limits of heat pipes as a function of operating temperature and working fluid during steady-state and transient operations. More generally, the ability to monitor component and system health during microreactor operation is attractive for providing a high sensor density to inform a limited number of microreactor operators to ultimately reduce operation and maintenance costs and move toward semi-autonomous operation. This report discusses the characterization of embedded thermocouples and fiber optic sensors in relevant test articles, including cylindrical pipes and hexagonal monolithic test articles for heat pipe-based reactors. The sensors were embedded by placing them in machined channels and then building up additional material by using ultrasonic additive manufacturing (UAM). UAM is a solid-state welding process that uses downward pressure and a lateral scrubbing motion to bond thin metal foils to a base material layer by layer. The ultrasonic welding process relies on the plastic deformation of the metal—as opposed to typical melting and solidification—to break oxide scales and bond the metal layers. The characterization of these embedded sensors included evaluating fiber optic signal attenuation, observing residual strain in the fibers, investigating microstructural and mechanical aspects, and demonstrating the sensors under various thermal loads and acoustic vibrations. Post-embedding characterization showed a fine grain structure (<1 μm) near the interfaces of the bonded foils as a result of severe deformation from the welding process. A large increase in hardness was observed at the foil interfaces and the fiber/matrix interface compared with the bulk matrix. Even when compared with the SS304 interfaces, the higher hardness observed around the embedded fiber suggests a higher degree of deformation due to the soft metal coating around the silica fiber core. The distributed fiber-optic temperature sensors and embedded thermocouples reliably measured temperature distributions during steady-state and transient thermal testing. The embedded fiber-optic sensors reliably measured strain during both transient and steady-state testing and properly identified resonant frequencies during acoustic testing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Computational insights into the interaction of water with the UiO-66 metal–organic framework and its functionalized derivatives

The UiO-66 metal–organic framework (MOF) has been identified as a promising hydrophilic material for water harvesting. Recent studies show that its water uptake ability at low relative humidity (RH) can be improved by incorporating hydrophilic functional groups into the framework. In this work, we provide computational insights into the adsorption of water in UiO-66 and its functionalized derivatives to reveal the role played by different adsorption sites and functional groups in the adsorption mechanism. We started by developing molecular models for UiO-66, UiO-66-NH 2 , UiO-66-OH, and UiO-66-(OH) 2 compatible with the MB-pol data-driven many-body potential of water. We then benchmarked these models against ab initio data. Here we used these models to perform molecular dynamics simulations and calculate radial distribution functions, IR spectra, and two-dimensional density distribution maps for water in the MOFs. These results consistently show that the μ 3 -OH sites are the preferential interaction sites for water in UiO-66 and all its variants, and the formation of localised water clusters inside the octahedral pores is responsible for the abrupt step in the experimental adsorption isotherms. Furthermore, the presence of functional groups in the framework allows water to cluster in the octahedral pores at lower RH, thus making the MOF a more efficient water harvester. Overall, this study provides molecular-level insights into the pore filling process of UiO-66 and its functionalized derivatives, which are needed for the design of efficient water harvesting materials based on MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Joint Inversion of Body Wave Arrival Times, Surface Wave Dispersion Data and Receiver Functions: Method and Application to South China

In this work, we have developed a new joint inversion method that incorporates body wave arrival times, surface wave dispersion and receiver functions to simultaneously update earthquake locations and constrain three-dimensional P-wave (Vp) and S-wave velocity (Vs) models. Due to complementary sensitivities of the three types of data, the proposed joint inversion algorithm can reduce the intrinsic non-uniqueness of inversions using fewer types of data and better determine smooth velocity variations and velocity discontinuities. Synthetic tests demonstrate the advantages of this new joint inversion algorithm in resolving velocity structures, especially in constraining velocity gradients across the Moho interface. We have applied the proposed joint inversion algorithm to image the lithosphere velocity structure of south China. The inverted Vp and Vs models fit body wave arrival times, surface wave dispersion and receiver functions well. We further analyzed the distribution of Vs gradients across the Moho interface in detail, which helps us better understand tectonics in south China.

58 GEOSCIENCES↗

First principles investigation of dopants and defect complexes in CdSe$_x$Te$_{1-x}$

Se alloying is a common approach to improve the performance of CdTe solar cells by tuning the bandgap, defect levels, and carrier density. A fundamental understanding of these improvements, specifically the effect of Se alloying on the behavior of defects and dopants in CdTe, remains unclear. Here, in this work, we present a density functional theory (DFT) study of point defect energetics in CdTe and CdSe x Te 1-x with x = 0.25, leading to a comparison of how native defects, dopants (As and Cu), impurities (Cl and O), and related defect complexes behave in CdTe vs CdSe x Te 1-x . Our calculations, performed by combining semi-local and nonlocal hybrid functionals, show a general lowering of the formation energies of native defects as well as substitutional defects formed by As and Cl upon Se addition. For successful p-type doping with As, destabilizing Cl-based defects in the CdSeTe lattice would be essential. We find evidence for some low-energy defect complexes of As, Cl, and O in CdSe 0.25 Te 0.75 . The computed defect formation energies further enable estimates of temperature-dependent defect concentrations and self-consistent Fermi levels. A comparison of defect energetics with the energies of impurity phases reveals that As, Cu, Cl, and O overwhelmingly prefer being segregated to unwanted As 2 O 5 , AsCl 3 , Cd 2 AsCl 2 , and CuO x phases rather than remain at defect sites, but such segregation is less likely to happen in CdSe 0.25 Te 0.75 than in CdTe. Overall, our work presents a list of likely defects and complexes in CdTe and Se-incorporated CdTe, paving the way to explain and mitigate limited dopant activation in experimental observations.

CdTe↗

Diamond surface functionalization via visible light–driven C–H activation for nanoscale quantum sensing

Nitrogen-vacancy (NV) centers in diamond are a promising platform for nanoscale NMR sensing. Despite significant progress toward using NV centers to detect and localize nuclear spins down to the single spin level, NV-based spectroscopy of individual, intact, arbitrary target molecules remains elusive. Such sensing requires that target molecules are immobilized within nanometers of NV centers with long spin coherence. The inert nature of diamond typically requires harsh functionalization techniques such as thermal annealing or plasma processing, limiting the scope of functional groups that can be attached to the surface. Solution-phase chemical methods can be readily generalized to install diverse functional groups, but they have not been widely explored for single-crystal diamond surfaces. Moreover, realizing shallow NV centers with long spin coherence times requires highly ordered single-crystal surfaces, and solution-phase functionalization has not yet been shown with such demanding conditions. In this work, we report a versatile strategy to directly functionalize C–H bonds on single-crystal diamond surfaces under ambient conditions using visible light, forming C–F, C–Cl, C–S, and C–N bonds at the surface. This method is compatible with NV centers within 10 nm of the surface with spin coherence times comparable to the state of the art. As a proof-of-principle demonstration, we use shallow ensembles of NV centers to detect nuclear spins from surface-bound functional groups. Our approach to surface functionalization opens the door to deploying NV centers as a tool for chemical sensing and single-molecule spectroscopy.

Science & Technology - Other Topics↗

Compositionally-driven surface nanostructuring on refractory compositionally complex alloys under low energy helium bombardment

Additive manufacturing enables user-defined control of the compositional complexity, opening new design spaces for complex concentrated alloys (CCAs). Refractory CCAs may offer enhanced performance in the divertor region of a fusion reactor environment where plasma-facing materials will be subject to high temperatures, low energy He and D particles, and 14 MeV neutrons. In this work, specimens with the nominal composition of NbTaMoTi, NbTaMo, NbTaTi, and NbTa were fabricated via directed energy deposition (DED) then bombarded with 40 eV He ions to a fluence of 2x10 26 m −2 at ∼ 1000 K. Post irradiation, the surface morphology and composition were examined with electron microscopy and x-ray photoelectron spectroscopy to offer information on the spatial distribution of surface nano-structuring. Sub-surface He bubbles driving the nano-structuring were examined with electron microscopy techniques. Analysis indicates the local composition directly influences the He bubble and tendril size, while the region with the highest complexity showed the shortest nano-structuring. Molecular Dynamics simulations complement the experimental results, showing comparable helium bubble growth and migration as a function of compositional complexity. This work demonstrates the compositional dependence of surface nanostructure formation of compositionally complex alloys, important for future design of complex plasma facing materials in fusion reactors.

Complex concentrated alloys↗

Reversible control over the distribution of chemical inhomogeneities in multiferroic BiFeO3

Abstract Despite the appeal of flawless order, semiconductor technology has demonstrated that implanting inhomogeneities into single-crystalline materials is pivotal for modern electronics. However, the influence of the local arrangement of chemical inhomogeneities on the material’s functionalities is underexplored. In this work, we control the distribution of chemical inhomogeneities in La 3+ -substituted ferroelectric BiFeO 3 thin films. By means of a stress- and composition-driven phase transition, we trigger the formation of a lattice of La 3+ -rich and La 3+ -poor layers. This ordering correlates with the emergence of an antipolar phase. An electric field restores the original ferroelectric phase and re-randomizes the distribution of the La 3+ inhomogeneities. Leveraging these insights, we tune the polar/antipolar phase coexistence to set the net polarization of La 0.15 Bi 0.85 FeO 3 to any desired value between its saturation limits. Finally, we control the net polarization response in device-compliant capacitor heterostructures to show that inhomogeneity-distribution control is a valuable tool in the design of functional oxide electronics.

Science & Technology - Other Topics↗

Utilizing metal cation reactions with carbonyl sulfide to remove isobaric interferences in tandem inductively coupled plasma mass spectrometry analyses

Carbonyl sulfide (OCS) was used as a reaction gas to investigate gas phase metal (M + ) ion-molecule reactions using the Agilent 8900 inductively coupled plasma tandem mass spectrometer (ICP-MS/MS) to yield insight on how this gas may be used to remove isobaric interferences in analytical measurements. The experimental work was paired with density functional theory (DFT) calculations of the reaction enthalpy to predict whether M + will react with OCS. A multi-element standard containing 46 elements ranging from 9 to 208 u was analyzed in the presence and absence of OCS. When a reaction was observed, the dominant product was the sulfide (MS + ). Oxide products were also observed for many M + but formation was less efficient with OCS than previously observed with other reaction gases. This is likely due to the weaker OC-S bond that makes MS + formation more favorable. Increasing the flow rate from 0.1 to 0.2 mL/min (corresponding to a change in reaction gas pressure from 0.35 to 0.53 Pa (2.6 to 4.0 mTorr)) generally resulted in greater MS + production, including the secondary product MS 2 + for a few cations. The early lanthanide series ions (La + , Ce + , Pr + and Nd + ) produced greater quantities of MO + at the higher pressure, although MS + products were still the dominant product. The DFT-predicted reaction enthalpies were consistent with the observed sulfide formation, with an accuracy >90%; however, model predictions were less accurate for the minor and higher order products (< 77% for MO + ). Finally, the work presented here continues a systematic study of ion-molecule reactions in ICP-MS/MS to understand and develop new and novel ways to analyze complex mixtures with minimal pre-analysis treatment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Performance Advantaged Thermosets from Bioderived Amines: Benefits in Manufacturing, Performance, and End-of-Life

Biomass derived monomers can offer unique functionality, often in the forms of heteroatoms, that is not easily accessible by routine petrochemical routes. Importantly, many of these monomers offer the potential to replace the petrochemical monomers used in the manufacture of thermosets to enable expanded functionality and performance. In the present work, we leverage amine containing monomers that can be obtained via biological conversions in both epoxy and benzoxazine thermosets. These monomers have a wide degree of functionality available to them that augment the material properties. In the case of benzoxazines, monomers that contain both an amine and carboxylic acid are used and the presence of the carboxylic acid leads to an acceleration in cure kinetics and a dramatic reduction in cure temperature. For the epoxy thermosets, multifunctional amine monomers are used as a hardener and the properties of the resultant materials are found to scale with the spacing and identity between reactive centers. The amines can be further modified and reacted to produce a mixed network of triazines and epoxy-amines that enables the end-of-life degradation of these materials. Importantly, subsequent process analysis reveals that the use of bioderived amines can present dramatic reductions in both supply chain energy and GHG emissions while possessing a cost similar to their petrochemical counterparts. Overall, this work demonstrates the robust potential to use bioderived amines for performance advantaged properties.

bioderived monomers↗

Molecular dynamics simulations of displacement cascades in LiAlO2 and LiAl5O8 ceramics

Abstract Molecular dynamics was employed to investigate the radiation damage due to collision cascades in LiAlO 2 and LiAl 5 O 8 , the latter being a secondary phase formed in the former during irradiation. Atomic displacement cascades were simulated by initiating primary knock-on atoms (PKA) with energy values = 5, 10 and 15 keV and the damage was quantified by the number of Frenkel pairs formed for each species: Li, Al and O. The primary challenges of modeling an ionic system with and without a core–shell model for oxygen atoms were addressed and new findings on the radiation resistance of these ceramics are presented. The working of a variable timestep function and the kinetics in the background of the simulations have been elaborated to highlight the novelty of the simulation approach. More importantly, the key results indicated that LiAlO 2 experiences much more radiation damage than LiAl 5 O 8 , where the number of Li Frenkel pairs in LiAlO 2 was 3–5 times higher than in LiAl 5 O 8 while the number of Frenkel pairs for Al and O in LiAlO 2 are ~ 2 times higher than in LiAl 5 O 8 . The primary reason is high displacement threshold energies (E d ) in LiAl 5 O 8 for Li cations. The greater E d for Li imparts higher resistance to damage during the collision cascade and thus inhibits amorphization in LiAl 5 O 8 . The presented results suggest that LiAl 5 O 8 is likely to maintain structural integrity better than LiAlO 2 in the irradiation conditions studied in this work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

SymbolFit: Automatic Parametric Modeling with Symbolic Regression

We introduce SymbolFit (API: https://github.com/hftsoi/symbolfit), a framework that automates parametric modeling by using symbolic regression to perform a machine-search for functions that fit the data while simultaneously providing uncertainty estimates in a single run. Traditionally, constructing a parametric model to accurately describe binned data has been a manual and iterative process, requiring an adequate functional form to be determined before the fit can be performed. The main challenge arises when the appropriate functional forms cannot be derived from first principles, especially when there is no underlying true closed-form function for the distribution. In this work, we develop a framework that automates and streamlines the process by utilizing symbolic regression, a machine learning technique that explores a vast space of candidate functions without requiring a predefined functional form because the functional form itself is treated as a trainable parameter, making the process far more efficient and effortless than traditional regression methods. We demonstrate the framework in high-energy physics experiments at the CERN Large Hadron Collider (LHC) using five real proton-proton collision datasets from new physics searches, including background modeling in resonance searches for high-mass dijet, trijet, paired-dijet, diphoton, and dimuon events. We show that our framework can flexibly and efficiently generate a wide range of candidate functions that fit a nontrivial distribution well using a simple fit configuration that varies only by random seed, and that the same fit configuration, which defines a vast function space, can also be applied to distributions of different shapes, whereas achieving a comparable result with traditional methods would have required extensive manual effort.

Tsoi, Ho Fung [Univ. of Pennsylvania, Philadelphia↗

Applying Configurational Complexity to the 2D Ruddlesden–Popper Crystal Structure

The layered Ruddlesden–Popper crystal structure can host a broad range of functionally important behaviors. In this work, we establish extraordinary configurational disorder in a layered Ruddlesden–Popper (RP) structure using entropy stabilization assisted synthesis. A protype A 2 CuO 4 RP cuprate oxide with five cations on the A-site sublattice is designed and fabricated into epitaxial single crystal films using pulsed laser deposition. When grown on a near lattice matched substrate, the (La 0.2 Pr 0.2 Nd 0.2 Sm 0.2 Eu 0.2 ) 2 CuO 4 film features a T'-type RP structure with uniform A-site cation mixing and square-planar CuO4 units. These observations are made with a range of combined characterizations using X-ray diffraction, atomic-resolution scanning transmission electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray absorption spectroscopy measurements. It is further found that heteroepitaxial strain plays an important role in crystal phase formation during synthesis. Compressive strain over ~1.5% results in the formation of a non-RP cubic phase consistent with a Cu X 2O 4 spinel structure. The ability to manipulate configurational complexity and move between 2D layered RP and 3D cubic crystal structures in cuprate and related materials promises to enable flexible design strategies for a range of functionalities, such as magnetoresistance, unconventional superconductivity, ferroelectricity, catalysis, and ion transport.

36 MATERIALS SCIENCE↗

Tailored Silicone Network Architecture for Ultimate Mechanical Reinforcement

Hydrosilylation cured silicone elastomers are subject to reaction inefficiency, leading to incomplete and non-uniform crosslink networks, restricting the potential of mechanical reinforcement. This work investigates pre-synthesized, functional PDMS architectures as additives to improve ultimate mechanical performance relative to conventional single-step curing. Three custom, functional structures were prepared: a partially crosslinked PDMS scaffold (Structure A), a bottle-brush PDMS (Structure B), and a star-shaped PDMS derived from an MQ resin (Structure C). Rheological characterization was used to identify the ultimate design space and proper stoichiometric ratio for Structure A, and confirm successful formation of all structures for suitable incorporation into a base silicone formulation at 30wt%. Mechanical tests indicated that all three structures increased in ultimate tensile strength relative to their single-step counterparts, with Structure A providing additional improvements to toughness (432 vs. 258 kJ/m3) and ultimate elongation (158 vs. 115%). Furthermore, Structure B remained very soft in the unfilled state, while Structure C provided hardness (23 vs. 18 Shore A) and stiffness (780 vs. 420 kPa Young’s modulus) increases. In silica filled systems, Structure A retained increased strength but reduced elongation, while Structure B indicated strong reinforcement in terms of strength, toughness, and stiffness. Thermal analysis on the cure profiles of these materials suggested that pre-formation of network architectures enable a more complete reaction than a single-step process (15.9 vs. 15.1 J/g). Ultimately, these results indicate that tailoring PDMS architecture before the final cure can improve ultimate mechanical properties via improved network development in silicone elastomers. Furthermore, this work offers a promising strategy for designing higher-performance, more tunable silicone formulations.

36 MATERIALS SCIENCE↗

Improving stability of ALD ZrN thin film coatings over U-Mo dispersion fuel

Atomic layer deposition (ALD) of ZrN is a candidate technology for coating U-Mo dispersion fuel as a diffusion barrier coating. During the early development stages of the coating the ZrN deposition showed to be mechanically unstable and ultimately resulted in spalling. Based on experimental outcomes it was found that instabillity can be eliminated through the introduction of a thin amorphous (a) Al 2 O 3 interlayer coating deposited in between the ~1-μm thick ZrN and the U-Mo. substrate. To elucidate these findings simulations were performed with density functional theory (DFT) to measure work of adhesions at different interfaces while finite element modeling (FEM) was performed to measure the residual stress distribution. DFT indicated that the ZrN coating deposited over (a)-Al 2 O 3 is ~2.5 times stronger when compared to direct deposition over U or UO 2 substrate. While calculations from FEM recognized; (1) large stress concentrations can originate from the irregularly distributed native surface oxides (UO 2 ) over U-Mo and (2) stress concentrations can be reduced if those surface UO 2 can be modified to a uniform layer (achieved after application of a 8 nm (a)-Al 2 O 3 interlayer). These results provided explanations and confirmed the role played by interlayer in eliminating the original mechanical instability of the ZrN.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multi-catalytic active site biochar-based catalysts for glucose isomerized to fructose: Experiments and density functional theory study

In this study, this work provides an innovative method for preparing different isomerization catalysts by impregnating different proportions of MgCl 2 and AlCl 3 and combining different K compounds on cellulose-derived biochar, followed by pyrolysis. Results show MgO and Al(OH) 3 existing in 4 Mg- 1 Al-C catalyst can obtain better catalytic effect on glucose isomerization than the singe of Al presenting in 0 Mg- 1 Al-C catalyst. Moreover, the synergism effects of the multi-catalytic active sites such as β-, γ -Al(OH) 3 , KCl, MgO, and K 4 H 2 (CO 3 ) 3 in Mg-Al-KHCO 3 -C catalyst can further lead to an increase in glucose isomerization, compared to the 4 Mg- 1 Al-C catalyst. The X-ray diffraction results present that the value of O/Al in Mg-Al-KHCO 3 -C catalyst is as high as 13.38, which provides many unsaturated acidic catalysis sites and benefits the glucose isomerization. Simultaneously, the TPD results reveal that the main active sites (MgO, Al(OH) 3 , and K 4 H 2 (CO 3 ) 3 ) in Mg-Al-KHCO 3 -C catalyst can provide weakly acidic and basic sites and avoid strongly acidic and basic sites to excessively attack the glucose. Based on the DFT analysis, the results indicate that the MgO has a great effect on the ring-opening reaction to form acyclic glucose, while Al(OH) 3+ has a great effect on promoting acyclic glucose hydrogen transfer isomerized to form fructose. Compared to other carbon-based metal catalysts, the prepared Mg-Al-KHCO 3 -C has excellent catalytic performance, which gives a higher fructose yield (38.7%) and selectivity (87.72%) and glucose conversion (44.12%) at 100 °C in 30 min. In this study, we develop a highly efficient Mg-Al-K-biochar catalyst for glucose isomerization and provide an efficient method for cellulose valorization.

36 MATERIALS SCIENCE↗

The latent variable proximal point algorithm for variational problems with inequality constraints

The latent variable proximal point (LVPP) algorithm is a framework for solving infinite-dimensional variational problems with pointwise inequality constraints. The algorithm is a saddle point reformulation of the Bregman proximal point algorithm. At the continuous level, the two formulations are equivalent, but the saddle point formulation is more amenable to discretization because it introduces a structure-preserving transformation between a latent function space and the feasible set. Working in this latent space is much more convenient for enforcing inequality constraints than the feasible set, as discretizations can employ general linear combinations of suitable basis functions, and nonlinear solvers can involve general additive updates. LVPP yields numerical methods with observed mesh-independence for obstacle problems, contact, fracture, plasticity, and others besides; in many cases, for the first time. The framework also extends to more complex constraints, providing means to enforce convexity in the Monge–Ampère equation and handling quasi-variational inequalities, where the underlying constraint depends implicitly on the unknown solution. Here, in this paper, we describe the LVPP algorithm in a general form and apply it to ten problems from across mathematics.

Inequality constraints↗

DASSH-F: Subchannel Based Thermal Analysis

The DASSH thermal analysis code is designed to rapidly allow a reactor design engineer to obtain flow rates requirements that satisfy peak temperature constraints in the domain. The advantage of using DASSH over a hand calculation is that it has a more rigorous treatment of the pin power distribution and coolant heat transfer within an assembly and between assemblies. The advantage of using DASSH over a conventional 3D subchannel code or a computational fluid dynamics code (CFD) is that it can obtain the desired solution in a matter of minutes in serial with minor computer memory needs. The DASSH methodology is virtually identical to SUPERENERGY-2 with additional functionalities taken from follow on work to SUPERENERGY-2 done at ANL in the 1980s. DASSH today is an integral component of the Argonne Fast Reactor analysis suite for reactor design work. DASSH obtains the power distribution from a coupled neutron-gamma heating calculation in GAMSOR (including DIF3D) at each time point of a companion fuel cycle analysis calculation with REBUS. The domain in DASSH assumes a hexagonal grid typical for fast reactors with much of the geometry information taken from the DIF3D model. DASSH assumes the assemblies that are loaded into each grid position are ducted to control the coolant flow. Considerable detail is given on the subchannel formulation of DASSH in this document. Much of the formulation and design of the code builds upon research done by previous authors with little new investigation. Thus the decisions made in developing the subchannel model used in DASSH have their origins over 50 years ago. Much of the heat transfer methodology in DASSH is built upon correlations for both the coolant mixing and heat transfer coefficients for pins and ducts. DASSH is thus not a rigorous treatment of a given problem, but a rapid assessment of the temperature field that has known limitations with respect to an experimental measurement or CFD calculation. The DASSH input and output are detailed along with usage of the software. The DASSH output provides tables of evaluated material properties and key coolant and pin temperature results. DASSH can create Python scripts that generate domain summary pictures. DASSH can also generate assembly temperature maps and VTK output files which allow the DASSH solution to be visualized. As the primary purpose of the DASSH software is to compute the coolant and fuel pin temperature distribution for a given model of a reactor, much of the output focus is giving the user quick summary tables needed to assess the performance of a given orifice flow specification. The present version of DASSH has a crude orifice search capability and an efficient orifice flow search capability. The flow search tries to meet user specified constraints for 1) peak 2-sigma clad midwall temperature, 2) peak coolant temperature, and 3) desired bulk outlet temperature. There are many development shortcomings in DASSH detailed in this document, but this version is functional for modern analysis needs. This document serves as the manual for the Fortran based DASSH software that was developed to replace the Python version of DASSH developed as part of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Selectivity of enzymes involved in the formation of opposite enantiomeric series of p -menthane monoterpenoids in peppermint and Japanese catnip

Peppermint (Mentha x piperita L.) and Japanese catnip (Schizonepeta tenuifolia (Benth.) Briq.) accumulate p-menthane monoterpenoids with identical functionalization patterns but opposite stereochemistry. In the present study, we investigate the enantioselectivity of multiple enzymes involved in monoterpenoid biosynthesis in these species. Based on kinetic assays, mint limonene synthase, limonene 3-hydroxylase, isopiperitenol dehydrogenase, isopiperitenone reductase, and menthone reductase exhibited significant enantioselectivity toward intermediates of the pathway that proceeds through (-)-4S-limonene. Limonene synthase, isopiperitenol dehydrogenase and isopiperitenone reductase of Japanese catnip preferred intermediates of the pathway that involves (+)-4R-limonene, whereas limonene 3-hydroxylase was not enantioselective, and the activities of pulegone reductase and menthone reductase were too low to acquire meaningful kinetic data. Molecular modeling studies with docked ligands generally supported the experimental data obtained with peppermint enzymes, indicating that the preferred enantiomer was aligned well with the requisite cofactor and amino acid residues implicated in catalysis. A striking example for enantioselectivity was peppermint (-)-menthone reductase, which binds (-)-menthone with exquisite affinity but was predicted to bind (+)-menthone in a non-productive orientation that positions its carbonyl functional group at considerable distance to the NADPH cofactor. Here, the work presented here lays the groundwork for structure-function studies aimed at unraveling how enantioselectivity evolved in closely related species of the Lamiaceae and beyond.

59 BASIC BIOLOGICAL SCIENCES↗