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At least 919 records · Page 51

Wave Prediction using X-Band Radar (Final Summary Report)

Model Predictive Control (MPC) is the best controls framework available to wave energy today. It allows for the maximization of energy yield from a WEC system while respecting various constraints and losses in the system. This type of constrained optimization is a critical capability for the techno-economic optimization of WEC devices and is difficult to do effectively with causal controls frameworks. MPC requires a future prediction of wave excitation forces, requiring wave prediction on a future time horizon of up to 30 seconds. The future horizon required is highly dependent on the WEC and PTO type available. To our knowledge no-one has been able to implement MPC on a WEC device at sea, due to the fact that phase-resolved wave-prediction is not a capability that has been sufficiently developed to date. The key objectives of this project are focused on developing “industry-ready” wave prediction technology building blocks that can be applied to a wide range of different wave energy conversion topologies. Our collaborative work with device developers has demonstrated that the level of improvement attainable for any particular device is heavily dependent on the device and PTO topology chosen. The range of annual average power capture improvements is on the order of 10% to over 100%. However, the important aspect is that we can get within about 10% of theoretical upper limits even when considering errors in the wave prediction and more importantly, we can optimize performance while respecting various constraints such as motion amplitude or peak structural loads. The combination of improved performance while limiting structural loads has a net effect of reducing the levelized cost of energy from these emerging technologies and allows us to design control laws that meet an economic optimum. Efforts under a previous project on controls has focused on developing a set of wave-prediction algorithms that work by leveraging a network of wave sensing measurement buoys that are equipped with real-time telemetry. The present work is focusing primarily on using X-band radar to measure the wave-field around the WEC to predict the future excitation forces on the structure and combining the measurements of these different sources to create improvements in the wave-prediction accuracy.

16 TIDAL AND WAVE POWER↗

A Low-Power Time-to-Digital Converter for the CMS Endcap Timing Layer (ETL) Upgrade

We present the design and test results of a Time-to-Digital-Converter (TDC). The TDC will be a part of the readout ASIC, called ETROC, to read out Low-Gain Avalanche Detectors (LGADs) for the CMS Endcap Timing Layer (ETL) of High-Luminosity LHC upgrade. One of the challenges of the ETROC design is that the TDC is required to consume less than 200 W for each pixel at the nominal hit occupancy of 1%. To meet the low-power requirement, we use a single delay line for both the Time of Arrival (TOA) and the Time over Threshold (TOT) measurements without delay control. A double-strobe self-calibration scheme is used to compensate for process variation, temperature, and power supply voltage. The TDC is fabricated in a 65 nm CMOS technology. The overall performances of the TDC have been evaluated. The TOA has a bin size of 17.8 ps within its effective dynamic range of 11.6 ns. The effective measurement precision of the TOA is 5.6 ps and 9.9 ps with and without the nonlinearity correction, respectively. The TDC block consumes 97 W at the hit occupancy of 1%. Over a temperature range from 23 C to 78 C and a power supply voltage range from 1.05 V to 1.35 V (the nominal value of 1.20 V), the self-calibrated bin size of the TOA varies within 0.4%. The measured TDC performances meet the requirements except that more tests will be performed in the future to verify that the TDC complies with the radiation-tolerance specifications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Synthesis of Free-Standing Pd-Ni-P Metallic Glass Nanoparticles with Durable Medium-Range Ordered Structure for Enhanced Electrocatalytic Properties

Topologically disordered metallic glass nanoparticles (MGNPs) with highly active and tailorable surface chemistries have immense potential for functional uses. The synthesis of free-standing MGNPs is crucial and intensively pursued because their activity strongly depends on their exposed surfaces. Herein, a novel laser-evaporated inert-gas condensation method is designed and successfully developed for synthesizing free-standing MGNPs without substrates or capping agents, which is implemented via pulse laser-induced atomic vapor deposition under an inert helium atmosphere. In this way, the metallic atoms vaporized from the targets collide with helium atoms and then condense into short-range-order (SRO) clusters, which mutually assemble to form the MGNPs. Using this method, free-standing Pd 40 Ni 40 P 20 MGNPs with a spherical morphology are synthesized, which demonstrates satisfactory electrocatalytic activity and durability in oxygen reduction reactions. Moreover, local structure investigations using synchrotron pair distribution function techniques reveal the transformation of SRO cluster connection motifs of the MGNPs from face-sharing to edge-sharing modes during cyclic voltammetry cycles, which enhances the electrochemical stability by blocking crystallization. Further, this approach provides a general strategy for preparing free-standing MGNPs with high surface activities, which may have widespread functional applications

36 MATERIALS SCIENCE↗

Rapid Patterning and Advanced Device Structures for Low Cost Manufacturable Crystalline Si IBC Cells

Recent record efficiency Si cells have had an interdigitated back contact (IBC) design where both positive and negative contacts are fabricated on the back side of the Si wafer. Many industry groups have investigated IBC cells but used photolithography to pattern the rear contacts although it is considered impractical for low cost, high volume manufacturing. Alternative patterning methods using lasers and mechanical masking have been utilized in fabrication of patterned regions in IBC Si solar cells to replace photolithography. Another exciting advance in Si solar cell technology has been replacing the high temperature diffusion of doped regions inside the crystalline Si wafer with low temperature deposition of very thin layers of doped amorphous hydrogenated Si (a-Si:H) on the Si wafer. This is called a Si heterojunction (HJ) device. The a-Si:H provides excellent passivation of surface defects and has produced the highest open circuit voltages (VOC) of any Si solar cell device structure. The Institute of Energy Conversion (IEC) demonstrated the first IBC-HJ solar cell combining these two strategies in 2007 and has fabricated IBC-HJ cells with 20% efficiency using three photolithography steps. Despite the demonstrated efficiency potential of this device by industry groups (>26%) there is no commercial production because of the challenges of patterning and processing the structure in an industrial environment. Our work sought to address that challenge. The objective of this 3 year project was to develop the processing for the IBC-HJ Si solar cell using lasers for patterning and contact formation instead of photolithography. Laser patterning enables rapid, contactless manufacturing of patterned regions. We intensively studied laser fired contacts, laser patterning of the a-Si multi-layer stacks and metal layers and the use of plasma shadow masks. After an exhaustive focus in the first year on the laser fired emitter (LFE) and contact (LFC), we were unable to achieve VOC greater than 660 mV, compared to the 720 mV required to meet our milestones. We discovered that an additional issue with our original IBC structure was the presence of an inversion layer at the back surface connecting the p and n regions which reduced the VOC and fill factor (FF). We developed innovative methods for characterizing the inversion layer. These two limitations in the original design lead to development of a new IBC-HJ process sequence and device structure which we called Plasma Masked Laser Processed (PMLP). It retained the original high efficiency features including manufacturability. The LFC was replaced with a standard n-type a-Si HJ contact. The inversion layer was eliminated by replacing the previous p-type stack in the gap with an n-type or SiN stack. The PMLP used laser ablation of a multi-layer a-Si stack followed by chemical etching to open the n-contact. It required deposition of a patterned stack through a mask in the plasma deposition chamber. This turned out to be a source of significant problems due to inevitable unwanted deposition ‘leakage’ under the mask. This formed a blocking contact on the emitter which significantly reduced Voc and FF. Several iterations in PMLP device structure and chemical etching steps resulted in a large improvements, e.g. the efficiency increasing from 3 to 15% and Voc from 450 to 660 mV but they were unable to completely eliminate it. The best IBC-HJ device we fabricated had only 15% efficiency. For perspective, our standard FHJ devices had 20% efficiency.

14 SOLAR ENERGY↗

Supramolecular Tuning Enables Selective Oxygen Reduction Catalyzed by Cobalt Porphyrins for Direct Electrosynthesis of Hydrogen Peroxide

Abstract We report a supramolecular strategy for promoting the selective reduction of O 2 for direct electrosynthesis of H 2 O 2 . We utilized cobalt tetraphenylporphyrin (Co‐TPP), an oxygen reduction reaction (ORR) catalyst with highly variable product selectivity, as a building block to assemble the permanently porous supramolecular cage Co‐PB‐1(6) bearing six Co‐TPP subunits connected through twenty‐four imine bonds. Reduction of these imine linkers to amines yields the more flexible cage Co‐rPB‐1(6). Both Co‐PB‐1(6) and Co‐rPB‐1(6) cages produce 90–100 % H 2 O 2 from electrochemical ORR catalysis in neutral pH water, whereas the Co‐TPP monomer gives a 50 % mixture of H 2 O 2 and H 2 O. Bimolecular pathways have been implicated in facilitating H 2 O formation, therefore, we attribute this high H 2 O 2 selectivity to site isolation of the discrete molecular units in each supramolecule. The ability to control reaction selectivity in supramolecular structures beyond traditional host–guest interactions offers new opportunities for designing such architectures for a broader range of catalytic applications.

Smith, Peter T.↗

Supramolecular Tuning Enables Selective Oxygen Reduction Catalyzed by Cobalt Porphyrins for Direct Electrosynthesis of Hydrogen Peroxide

Abstract We report a supramolecular strategy for promoting the selective reduction of O 2 for direct electrosynthesis of H 2 O 2 . We utilized cobalt tetraphenylporphyrin (Co‐TPP), an oxygen reduction reaction (ORR) catalyst with highly variable product selectivity, as a building block to assemble the permanently porous supramolecular cage Co‐PB‐1(6) bearing six Co‐TPP subunits connected through twenty‐four imine bonds. Reduction of these imine linkers to amines yields the more flexible cage Co‐rPB‐1(6). Both Co‐PB‐1(6) and Co‐rPB‐1(6) cages produce 90–100 % H 2 O 2 from electrochemical ORR catalysis in neutral pH water, whereas the Co‐TPP monomer gives a 50 % mixture of H 2 O 2 and H 2 O. Bimolecular pathways have been implicated in facilitating H 2 O formation, therefore, we attribute this high H 2 O 2 selectivity to site isolation of the discrete molecular units in each supramolecule. The ability to control reaction selectivity in supramolecular structures beyond traditional host–guest interactions offers new opportunities for designing such architectures for a broader range of catalytic applications.

Smith, Peter T.↗

Bringing Inorganic Carbon to Life: Developing Model Metalloenzymes for C1 Conversion Reactions

The global carbon cycle is carefully balanced through the use of specialized enzymes in plants, algae, bacteria, and archaea. A primordial metabolic pathway for the conversion of inorganic carbon into cellular biomass uses a large, nickel-containing enzyme called carbon monoxide dehydrogenase (CODH)/acetyl coenzyme A synthase (ACS). This system fixes carbon dioxide (CO 2 ) into carbon monoxide (CO) at the CODH site. The carbon monoxide is then used to generate acetyl coenzyme A, a biological building block, through a key carbon-carbon bond forming step at the nickel site in ACS. Despite the significance of these processes in the context of energy conversion, the fundamental chemistry underlying these transformations has remained elusive, in part due to the complexity of the natural enzyme. To better understand the principles governing these biological processes, which represent one-carbon (C 1 ) activation reactions, this project will develop functional models of CODH and ACS based on modifications to a small metalloprotein scaffold. Comprehensive characterization of these systems using advanced spectroscopic and biophysical techniques will reveal key elements responsible for conferring high levels of activity to the model systems, with implications for gaining insight into the mechanisms of the natural enzymes. Moreover, the principles learned from this research can be used to guide design of robust catalysts for efficient conversion of CO 2 and CO into liquid fuels.

10 SYNTHETIC FUELS↗

Nondestructive Evaluation of Concrete: Elastic Property Imaging Through Full-Waveform Inversion

Concrete is a vital material in construction—especially in the nuclear industry, where it is used in critical structures such as containment vessels. Over time, concrete can degrade due to harsh operational and environmental conditions, necessitating that its elastic properties be accurately evaluated to ensure structural integrity and safety. Traditional nondestructive evaluation methods such as ultrasound-based techniques often rely on simplifying assumptions that may not hold true for concrete. This paper presents an advanced ultrasound-based method that uses elastic full-waveform inversion (EFWI) to create detailed images of concrete’s mechanical properties. By accurately modeling wave behaviors such as scattering and reflection, we aim to overcome the limitations of conventional ultrasonic-based methods. In this work, the imaging problem involved reconstructing the various elastic properties of a heterogenous concrete block with three steel rebars embedded in it. The ultrasonic measurements were synthetically generated from multiple sources and receivers, and the reconstruction process was performed using a gradient-based optimization algorithm. Our approach leveraged EFWI to reconstruct high-resolution images of the pressure wave speed, shear wave speed, and density. Multiple misfit functions—including L2-norm, cross-correlation (CC), and L1-norm—combined with total variation (TV) regularization and parameter constraints using a Sigmoid function—were explored for the reconstruction. The results demonstrated that using the L1-norm misfit function in conjunction with TV regularization and Sigmoid constraints significantly improved the reconstruction quality in comparison to traditional methods. This approach provided clearer images with fewer artifacts and better captured background heterogeneity. Our findings highlight that, when properly designed, EFWI carries great potential for providing comprehensive, more accurate, and more reliable assessments of concrete conditions, as is crucial for the maintenance and safety of nuclear power plant structures.

97 - MATHEMATICS AND COMPUTING↗

A human antibody epitope map of Pfs230D1 derived from analysis of individuals vaccinated with a malaria transmission-blocking vaccine

Pfs230 domain 1 (Pfs230D1) is an advanced malaria transmission-blocking vaccine antigen demonstrating high functional activity in clinical trials. However, the structural and functional correlates of transmission-blocking activity are not defined. Here, we characterized a panel of human monoclonal antibodies (hmAbs) elicited in vaccinees immunized with Pfs230D1. These hmAbs exhibited diverse transmission-reducing activity, yet all bound to Pfs230D1 with nanomolar affinity. We compiled epitope-binning data for seventeen hmAbs and structures of nine hmAbs complexes to construct a high-resolution epitope map and revealed that potent transmission-reducing hmAbs bound to one face of Pfs230D1, while non-potent hmAbs bound to the opposing side. The structure of Pfs230D1D2 revealed that non-potent transmission-reducing epitopes were occluded by the second domain. The hmAb epitope map delineated binary hmAb combinations that synergized for extremely high-potency, transmission-reducing activity. Finally, this work provides a high-resolution guide for structure-based design of enhanced immunogens and informs diagnostics that measure the transmission-reducing response.

60 APPLIED LIFE SCIENCES↗

Colloidal crystal engineering with metal–organic framework nanoparticles and DNA

Abstract Colloidal crystal engineering with nucleic acid-modified nanoparticles is a powerful way for preparing 3D superlattices, which may be useful in many areas, including catalysis, sensing, and photonics. To date, the building blocks studied have been primarily based upon metals, metal oxides, chalcogenide semiconductors, and proteins. Here, we show that metal–organic framework nanoparticles (MOF NPs) densely functionalized with oligonucleotides can be programmed to crystallize into a diverse set of superlattices with well-defined crystal symmetries and compositions. Electron microscopy and small-angle X-ray scattering characterization confirm the formation of single-component MOF superlattices, binary MOF–Au single crystals, and two-dimensional MOF nanorod assemblies. Importantly, DNA-modified porphyrinic MOF nanorods (PCN-222) were assembled into 2D superlattices and found to be catalytically active for the photooxidation of 2-chloroethyl ethyl sulfide (CEES, a chemical warfare simulant of mustard gas). Taken together, these new materials and methods provide access to colloidal crystals that incorporate particles with the well-established designer properties of MOFs and, therefore, increase the scope of possibilities for colloidal crystal engineering with DNA.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Domain-specific compilers for dynamic simulations of quantum materials on quantum computers

Abstract Simulation of the dynamics of quantum materials is emerging as a promising scientific application for noisy intermediate-scale quantum (NISQ) computers. Due to their high gate-error rates and short decoherence times, however, NISQ computers can only produce high-fidelity results for those quantum circuits smaller than some given circuit size. Dynamic simulations, therefore, pose a challenge as current algorithms produce circuits that grow in size with each subsequent time-step of the simulation. This underscores the crucial role of quantum circuit compilers to produce executable quantum circuits of minimal size, thereby maximizing the range of physical phenomena that can be studied within the NISQ fidelity budget. Here, we present two domain-specific (DS) quantum circuit compilers for the Rigetti and IBM quantum computers, specifically designed to compile circuits simulating dynamics under a special class of time-dependent Hamiltonians. The compilers outperform state-of-the-art general-purpose compilers in terms of circuit size reduction by around 25%–30% as well as wall-clock compilation time by around 40% (dependent on system size and simulation time-step). Drawing on heuristic techniques commonly used in artificial intelligence, both compilers scale well with simulation time-step and system size. Code for both compilers is open-source and packaged into a full-stack quantum simulation software with tutorials included for ease of use for future researchers wishing to perform dynamic simulations of quantum materials on quantum computers. As our DS compilers provide significant improvements in both compilation time and simulation fidelity, they provide a building block for accelerating progress toward physical quantum supremacy.

Physics↗

Thermally induced structural evolution and nanoscale interfacial dynamics in Bi-Sb-Te layered nanostructures

Layered chalcogenides, including Bi-Sb-Te ternary alloys and heterostructures, are renowned as thermoelectric and topological insulators and have recently been highlighted as plasmonic building blocks beyond noble metals. Here, we conduct joint in situ transmission electron microscopy and density functional theory calculations to investigate the temperature-dependent nanoscale dynamics and interfacial properties, identifying the role of native defects and edge configurations in the anisotropic sublimation of Bi 2 Te 3 -Sb 2 Te 3 heterostructures and Sb 2-x Bi x Te 3 alloys. We report structural dynamics, including edge evolution, layer-by-layer sublimation, and the formation and coalescence of thermally induced polygonal nanopores. These nanopores are initiated by preferential dissociation of tellurium, reducing thermal stability in heterostructures. Triangular and quasi-hexagonal configurations dominate nanopore structures in heterostructures. Our calculations reveal antisite defects (Te Sb and Te Bi ) as key players in defect-assisted sublimation. These findings enhance our understanding of nanoscale dynamics and assist in designing tunable low-dimensional chalcogenides.

Bi2Te3-Sb2Te3 heterostructure↗

Development of Segregated Thermal-Hydraulics Solvers in MOOSE

The simulation of fluid flows is an essential part of the design and analysis of nuclear systems. Algorithms able to simulate flows at different fidelity levels are available in the Multiphysics Object-Oriented Simulation Environment (MOOSE) and MOOSE-based applications such as Pronghorn \cite{novak2018pronghorn}, Pronghorn-Subchannel, RELAP-7, and SAM. Currently, significant effort is being invested in the development of coarse-mesh Computational Fluid Dynamics (CFD) capabilities within MOOSE and Pronghorn for the simulation of Generation IV nuclear reactors. Traditionally, the solution algorithms in MOOSE have relied on Newton or quasi-Newton methods (such as the preconditioned Jacobian-free Newton-Krylov method) where residuals and Jacobians (or approximations thereof) are constructed. Both Newton and quasi-Newton methods require the solution of a linear system at each nonlinear Newton iteration with the Jacobian as the system matrix. The Jacobian contains blocks originating from all variables in the problem (i.e., for thermal-hydraulics at least pressure, velocities, and temperature). Due to the formulation of the problem in a general multiphysics setting on unstructured mesh, creating a good preconditioner for the linear system can be challenging, thus many fluid applications have utilized direct solver-based methods such as LU factorization. However, with increasing system size and complexity in multi-dimensional problems, the direct solution of linear systems becomes computationally expensive both in execution time and and memory. For this reason, recent effort has focused on adapting segregated solution algorithms for CFD problems in MOOSE. These algorithms use fixed-point iteration between segregated systems whose assembly and preconditioning are easier those of the monolithic system. Initial results show that the segregated solution algorithm outperforms the monolithic approach in terms of memory usage and for large 3D problems in terms of CPU time as well.

42 ENGINEERING↗

Development of Segregated Thermal-Hydraulics Solvers in MOOSE

The simulation of fluid flows is an essential part of the design and analysis of nuclear systems. Algorithms able to simulate flows at different fidelity levels are available in the Multiphysics Object-Oriented Simulation Environment (MOOSE) and MOOSE-based applications such as Pronghorn \cite{novak2018pronghorn}, Pronghorn-Subchannel, RELAP-7, and SAM. Currently, significant effort is being invested in the development of coarse-mesh Computational Fluid Dynamics (CFD) capabilities within MOOSE and Pronghorn for the simulation of Generation IV nuclear reactors. Traditionally, the solution algorithms in MOOSE have relied on Newton or quasi-Newton methods (such as the preconditioned Jacobian-free Newton-Krylov method) where residuals and Jacobians (or approximations thereof) are constructed. Both Newton and quasi-Newton methods require the solution of a linear system at each nonlinear Newton iteration with the Jacobian as the system matrix. The Jacobian contains blocks originating from all variables in the problem (i.e., for thermal-hydraulics at least pressure, velocities, and temperature). Due to the formulation of the problem in a general multiphysics setting on unstructured mesh, creating a good preconditioner for the linear system can be challenging, thus many fluid applications have utilized direct solver-based methods such as LU factorization. However, with increasing system size and complexity in multi-dimensional problems, the direct solution of linear systems becomes computationally expensive both in execution time and and memory. For this reason, recent effort has focused on adapting segregated solution algorithms for CFD problems in MOOSE. These algorithms use fixed-point iteration between segregated systems whose assembly and preconditioning are easier those of the monolithic system. Initial results show that the segregated solution algorithm outperforms the monolithic approach in terms of memory usage and for large 3D problems in terms of CPU time as well.

42 ENGINEERING↗

Side-Chain Nanophase Separation Broadens the Double-Gyroid Stability Window in PS–PODMA Diblock Copolymers

Expanding access to bicontinuous network phases in block copolymers remains an important challenge because the double gyroid (DG) phase is usually stable only within a narrow composition window in conventional diblock copolymers. Here, we show that poly(styrene-block-octadecyl methacrylate) (PS-b-PODMA) exhibits an unusually broad DG window. Small-angle X-ray scattering measurements across a wide composition range reveal lamellar and hexagonally packed cylindrical phases at higher polystyrene fractions. In contrast, the DG phase appears over 0.22 ≤ fPS ≤ 0.35, with DG/BCC and DG/HEX coexistence near fPS = 0.18 and 0.40, respectively. This broad DG window is much wider than those reported for neat diblock copolymers and is not readily explained by conformational asymmetry alone. Wide-angle X-ray scattering detects a characteristic signature of nanophase separation within the PODMA-rich domains, indicating that side-chain ordering introduces an additional internal length scale. These results suggest that hierarchical side-chain nanophase separation modifies packing frustration and curvature selection, thereby broadening DG stability and providing a new molecular design strategy for stabilizing complex network morphologies.

Seko, Tamio↗

Physics-Driven Construction of Compact Primitive Gaussian Density Fitting Basis Sets

We present a model-assisted density fitting (MADF) basis set generator, an algorithm for generating primitive atomic Gaussian density fitting (DF) basis sets (DFBSs) from a contracted Gaussian orbital basis set (OBS). The MADF algorithm produces DFBSs suitable for accurate robust DF approximation of 2-particle interactions in mean-field and correlated electronic structures. The algorithm is designed to (a) saturate the OBS product space by a large regularized set of primitive solid-harmonic Gaussian shells with nonuniform distribution of exponents, followed by (b) pruning of the shells according to their contributions to the 2- body energy of a correlated atomic ensemble. Building the DFBS generator model almost exclusively on mathematical and physical principles allows one to limit the number of parameters that control the density fitting error to three, with a single set of parameters sufficient for computations with all basis cardinal numbers, with and without correlation of core electrons, with and without scalar and spin-dependent relativistic effects, spanning almost all of the Periodic Table. Performance assessment included basis sets up to quadruple-ζ quality from several major basis set families, using molecules composed of main-group, d-block, and f-block elements. The resulting DF errors in Hartree−Fock and second-order MP2 energies (with relativistic all-electron treatments, when appropriate) were on the order of 20 and 10 μE h per electron, respectively.

Approximation↗

Linking classical PRA models to a dynamic PRA

Here, this paper presents a series of methods designed to incorporate classical Probabilistic Risk Assessment (PRA) models such as Event Trees (ETs) and Fault Trees (FTs) into dynamic PRA. In contrast to classical PRA, dynamic PRA couples stochastic methods with system simulators to determine the risks associated with complex systems such as nuclear power plants. Compared with classical PRA methods, they can evaluate with higher resolution the safety impact of timing and sequencing of events on the progression of the accident. As part of a dynamic PRA analysis, it is not uncommon that parts of the system to be analyzed might not require a computationally expensive simulation model. These parts could be in fact modeled by employing classical PRA models (e.g., a FT). Here, we present a set of methods and tools that can be used to link the most common classical PRA models (ETs, FTs, reliability block diagrams and Markov models) to simulation codes such as RELAP5-3D: creating a “hybrid PRA.” In order to show the potential of such an hybrid PRA we employ this method to verify ET modeling assumptions (e.g., success criteria) using a large break loss of coolant accident initiating event as a test case. In this respect, we link a set of FTs from the original PRA to the RELAP5-3D code and perform a hybrid PRA. The FTs are employed to model the control logic of several safety systems and to propagate component failures throughout the system. Provided the generated dynamic PRA data, we show how conservative assumptions in the original PRA can be identified and how such original PRA can be modified by updating success criteria captured by the set of RELAP5-3D simulation runs.

97 - MATHEMATICS AND COMPUTING↗

Hex-C 558 : A new porous metallic carbon allotrope for lithium-ion battery anode

Due to the limited specific capacity of graphite anodes in lithium-ion batteries (LIBs), it is imperative to find alternatives with better performance. Here in this work, we propose, for the first time, a three dimensional (3D) porous metallic 5-5-8 carbon monolith with hexagonal lattice as a potential candidate. With 5-5-8 carbon nanoribbon as the building block, this material, named Hex-C558, goes beyond graphene-nanoribbon-based 3D porous carbon structures. Using first-principles calculations, we show that Hex-C 558 is not only dynamically and thermally stable, but also is energetically more favorable than many other theoretically predicted carbon allotropes. More importantly, Hex-C 558 is metallic with ordered ionic conducting channels and possesses a low mass density of 1.05 gcm -3 , exhibiting great potential for ion-battery applications. As an anode for LIBs, Hex-C558 possesses a large specific capacity of 591 mAhg -1 , low diffusion energy barrier of 0.27 eV (at low Li concentration) and 0.52 eV (at high Li concentration), a low open-circuit voltage of 0.51 V, and a small volume change of 2.4%. This work provides a new route for the design and synthesis of novel carbon materials for battery applications by using pentagon-based building units.

36 MATERIALS SCIENCE↗