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Modeling and Simulation of Fuel Dispersal During the Loss-of-Coolant Accident

This document is the compilation of the milestone portion to a larger end of project NEUP report. The executive summary of the modeling portion is provided below: In the event of cladding rupture during a postulated LOCA in a pressurized water reactor, fuel particles, along with fission gases, can be expelled into the reactor core from the fractured fuel rod, a phenomenon referred to as fuel dispersal. The initial stage of fuel dispersal is strongly influenced by the high-pressure ejection of fuel fragments, the size and geometry of the ruptured cladding, and the depressurization history of the fuel rod during the postulated LOCA transient. Depending on the location of the burst orifice relative to the quench front, the dispersal event represents an intricate three-phase flow and heat transfer phenomenon, where high-temperature fuel particles carried by the fission gases interact with the coolant within the narrow subchannels of the fuel assemblies, inducing localized phase change. Given the unique multiphysics nature of this phenomena, the current study develops a dedicated computational framework to predict the mass distribution and cooling of dispersing fuel particles, facilitating post-accident assessment and management of the fuel assemblies. Considering the scale of nuclear reactor applications, a continuum three-fluid model is proposed for simulating the transport of solids within the reactor core. With high-temperature fuel fragments within the liquid media, nucleation sites inducing phase changes are dispersed within the flow domain. Coupled with the fact that the transient dispersal event occurs on different time scales than other three-phase flow applications, this study derives a time-averaged three-fluid flow model without losing generality. The assumptions regarding the continuum treatment of the solid phase and the modeling of fuel dispersal behavior are incorporated to simplify the governing equations and derive applicable closure relations. The computational validation of the model was conducted using adiabatic experimental results obtained from ongoing research at Oregon State University, focusing on characterizing fuel dispersal behavior during simulated LOCA conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched the probability density functions reported in experimental studies. The transport of fuel particles within a scaled 5 × 5 lattice of a pressurized-water reactor rod bundle geometry was modeled through a two-fluid Eulerian framework. The required boundary conditions were evaluated from the fuel performance code BISON in a postulated large-break LOCA scenario. The modeling framework considered solid fuel particles as granular matter, interacting with the gaseous dry steam phase and fission gases through the governing interfacial momentum exchange between the participating fluids. The simulation results provided the volume fraction of the solids obtained at the bottom surface of the enclosing tank geometry. Postulated LOCA leading to fuel dispersal phenomena involves the strong coupling between fuel thermomechanics, cladding deformation, thermal-hydraulics, and fuel particle transport. Incorporation of such a strong coupling in numerical simulation is performed by coupling the multiphysics solvers. In the case of fuel dispersal, a strong coupled simulation can be performed by coupling the BISON code for fuel performance, the TRACE code for system-level thermal hydraulics, and fuel particle transport in Multiphysics Object-Oriented Simulation Environment (MOOSE). For such intricate infrastructure, the MOOSE Framework eases the data transfer between codes. The recent version of MOOSE has incorporated the Navier-Stokes module for the fluid flow. An exploratory exercise was done to gain familiarity with finite volume capabilities in the MOOSE framework to incorporate the Spalart-Allmaras (SA) turbulence model. New finite-volume and auxiliary kernels were introduced to assemble the SA transport equation, compute turbulent viscosity, and evaluate wall distance and diagnostic turbulence terms, fully integrated with existing Navier-Stokes modules. A turbulent lid-driven cavity at a Reynolds number of approximately 10,000 is used for verification. MOOSE shows the robust solver convergence and produces the turbulent features. But it underpredicts the velocity profile and turbulent quantities, emphasizing the need to develop improved SA near-wall treatments (e.g., low-Re corrections or wall functions) as a key direction for future work.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Collective excitations and low-energy ionization signatures of relativistic particles in silicon detectors

Abstract Solid-state detectors with a low energy threshold have several applications, including searches of non-relativistic halo dark-matter particles with sub-GeV masses. When searching for relativistic, beyond-the-Standard-Model particles with enhanced cross sections for small energy transfers, a small detector with a low energy threshold may have better sensitivity than a larger detector with a higher energy threshold. In this paper, we calculate the low-energy ionization spectrum from high-velocity particles scattering in a dielectric material. We consider the full material response including the excitation of bulk plasmons. We generalize the energy-loss function to relativistic kinematics, and benchmark existing tools used for halo dark-matter scattering against electron energy-loss spectroscopy data. Compared to calculations commonly used in the literature, such as the Photo-Absorption-Ionization model or the free-electron model, including collective effects shifts the recoil ionization spectrum towards higher energies, typically peaking around 4–6 electron-hole pairs. We apply our results to the three benchmark examples: millicharged particles produced in a beam, neutrinos with a magnetic dipole moment produced in a reactor, and upscattered dark-matter particles. Our results show that the proper inclusion of collective effects typically enhances a detector’s sensitivity to these particles, since detector backgrounds, such as dark counts, peak at lower energies.

Physics↗

Data-driven nonlocal model for fragmentation in the crushing of solids

A technique is proposed for reproducing particle size distributions in three-dimensional simulations of the crushing and comminution of solid materials. The method is designed to produce realistic distributions over a wide range of loading conditions, especially for small fragments. In contrast to most existing methods, the new model does not explicitly treat the small-scale process of fracture. Instead, it uses measured fragment distributions from laboratory tests as the basic material property that is incorporated into the algorithm, providing a data-driven approach. The algorithm is implemented within a nonlocal peridynamic solver, which simulates the underlying continuum mechanics and contact interactions between fragments after they are formed. Finally, the technique is illustrated in reproducing fragmentation data from drop weight testing on sandstone samples.

58 GEOSCIENCES↗

Optical constants measurements of liquids for modeling aerosolized threats

Spectroscopic identification of aerosolized chemical threats is challenging due to the complex nature of the photon/particle interaction, as well as the diversity of possible particle sizes, morphologies, and compositions. Constructing a database of laboratory - measured transmittance spectra that covers each permutation is not practical. However, calculation of the spectra using the measured optical constants as a function of wavenumber, n(?) and k(?), for each of the liquids and/or solids composing the aerosol particles provides a viable alternative. These synthetic spectra (vis-à-vis laboratory-measured spectra) can be used to identify chemicals of interest and subtract out background interferents in field measurements. Using a well-established multiple pathlength approach, we measure the optical constants n/k for liquids that may be found as chemical species of interest or common background interferents aerosolized in plumes. These measurements are also used to generate several test case aerosol synthetic spectra.

Lockwood, Schuyler↗

Fostering a Guiding Multiscale Model for the Development of Advanced MgB 2 Hydrogen Storage Materials (Final Technical Report)

Project Goal and Objective. The demand for energy and for an upgraded energy infrastructure has steadily grown, as have the needs for energy independence and alternatives to our reliance on petroleum. Hydrogen is considered the most viable fuels for wide-scale implementation in the near future as it is less-polluting, non-toxic, and has more stored energy than petroleum. It is envisioned that hydrogen can eventually become the prime energy carrier, integrating the transportation, grid, and chemical sectors in a way that improves resiliency, diversifies feedstocks, and affords new economic opportunities. A key remaining challenge is the development materials with enhanced gravimetric and volumetric hydrogen storage capacities that offer a higher performance than compressed gas. These materials would eliminate the need for large-scale compression, thereby dramatically reducing the footprint and cost of gas storage. The high gravimetric and volumetric hydrogen capacities of complex hydrides has prompted an intensive investigation of the potential of this class of materials as hydrogen storage media over the past 25 years. Among the many complex hydrides that have been explored, magnesium borohydride, Mg(BH 4 ) 2 , has been found to possess the best combination of practical thermodynamic properties. These include a gravimetric H 2 density of 14.9 wt% H 2 and thermodynamics for the dehydrogenation of Mg(BH 4 ) 2 to MgB 2 (equation 1) (ΔH° = 39 kJ/mol H 2 , ΔS = 112 J/K mol H 2 ) which lie in the narrow window required Mg(BH 4 ) 2 $\Leftrightarrow$ MgB 2 + 4 H 2 (1) for reversibility under moderate pressure and temperature. However, overcoming the extremely slow kinetics of the reversible release of hydrogen by this material in the solid state is a daunting challenge. At temperatures greater than 400 °C, the borohydride releases up to 14 wt% hydrogen giving MgB 2 . We discovered that the direct re-hydrogenation of MgB 2 to Mg(BH 4 ) 2 can be accomplished under 950 bar H 2 at 400 °C. While this demonstrated that complete reversibility can be achieved, the conditions employed are far too extreme for commercial hydrogen storage applications. More recently, we found through US DOE funded research projects (EERE HyMARC and HySCOR), that hydrogen cycling, can be accomplish at much milder conditions upon modification of the borohydride or boride. Guided by these discoveries these discoveries, the objective of this research project was to obtain key information that will enable the development of a model of reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 . The ultimate goal of our efforts is to attain a model of this transformation that can be utilized to accelerate development further advanced materials. This project directly follows on discoveries that were made over the course of a US DOE, EERE HyMARC project that was focused on improvement of the hydrogen cycling kinetics of modified MgB 2 . We found that that mechanical milling with graphene results the desired, pronounced kinetic enhancement. The dramatic lowering of the conditions required for the hydrogenation of MgB 2 is a significant step towards overcoming its chemical inertness allowing its development as a practical onboard hydrogen storage material. However, the exact nature of the modification(s) of MgB 2 that is responsible for its activation towards hydrogenation is completely unknown. This situation is not unique, as efforts to develop hydrogen storage materials typically have a narrow focus rather than a comprehensive approach that takes atomic level bonding and structure; molecular dynamics; long range, nano- and mesoscale-structure and their interconnection all into account. The goal of this project was the development of a comprehensive, multi-scale computational model of reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 that can be utilized for development of higher performance versions of the modified material. Development of the model requires determination of: 1) the bulk, nano-scale, and meso-scale structural changes occurring at elevated pressure following mechano-chemical modification of MgB 2 ; 2) the reaction pathway of the reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 ; 3) the effect of elevated pressure and mechano-chemical modification on the chemical reaction pathways; 4) the interactions at solid-gas interfaces; and particle surfaces; and 5) the kinetics and thermodynamic parameters associated with each step of the hydrogenation reaction pathway. This investigation required advanced techniques as preliminary, standard XRD, 11 B NMR, and FTIR analysis showed no signs of material modification. In order to gain this level of understanding of modified MgB 2 , required the teaming of a diverse group of experts and state-of-the art experimental capabilities at the University of Hawaii at Manoa (UHM) and collaborating National Laboratories: Craig Jensen , Department of Chemistry (PI and Project Director), solid state, solution, and high pressure NMR spectroscopy; solid-state synthesis; and high pressure hydrogenation (collaboration with SNL); Godwin Severa , Hawaii Natural Energy Institute (co-PI) calorimetry; infrared and Raman spectroscopy (collaboration with NREL); Dera , high pressure X-ray diffraction including in situ experiments (collaboration with ANL); Hope Ishii , Hawaii Institute of Geophysics electron microscopy investigations (collaboration with LBNL); and Joe Brown , Mechanical Engineering , material electronic structure and electric field effects.

08 HYDROGEN↗

Development of a Liquid Bridge Model for Particle Agglomeration and Defluidization in Plastic Pyrolysis

Molten plastic that forms during the pyrolysis of plastic or municipal solid waste feedstock can lead to particle agglomeration. A liquid bridge model is developed in MFiX-DEM and validated against a cold flow experiment with glass beads coated with silicone oil. The liquid bridge model is then extended to support an evolving liquid layer thickness for pyrolysis applications. The extended model is used to study the sensitivity of the pyrolysis reactor to solids holdup, flow conditions, and plastic properties.

Banerjee, Subhodeep↗

Effect of Sample Mass, Confinement, and Preheating Time on the Thermal Response of LLM‐105: Experiments and Kinetic Analysis

Various small-scale experiments were performed to provide data for developing a model to predict the thermal response of LLM-105 over a wide range of conditions. The thermal decomposition of LLM-105 was studied as a function of sample mass, confinement of volatile products, and preheating time in both isothermal and ramped heating experiments. The thermal decomposition of LLM-105 is a two-step process, as shown by the two exothermic peaks in the heat flow profiles, which were fitted to two nth-order autocatalytic reaction models with a similar activation energy of ∼289 kJ/mol. The magnitude and shape of these peaks varied with sample mass and confinement. Increasing sample mass enhanced the second exotherm with respect to the first one, while increasing the level of confinement promoted a transition from a sublimation-dominated regime towards thermal decomposition. The effect of LLM-105 particle size on the rate of weight loss was evident for open-pan experiments, where bigger particles sublimed at lower temperatures than smaller particles. Thermal response and solid residue composition of LLM-105 samples were analyzed following preheating for different durations. Longer preheating times caused a shift of the second exotherm to lower temperatures and a decrease in the reaction enthalpy, confirming that LLM-105 decay is a consecutive reaction mechanism, probably autocatalytic. In conclusion, the kinetic model derived from ramped experiments was validated against the measured LLM-105 fraction remaining and the enthalpy remaining of the solid residue as a function of preheating times and showed good agreement.

Chemistry - Chemical explosives↗

Pathways to Electrochemical Ironmaking at Scale Via the Direct Reduction of Fe 2 O 3

Electrochemical ironmaking can provide an energy efficient, zero-emissions alternative to traditional methods of ironmaking, but the scalability of low-temperature electrochemical cells may be constrained by reactor throughput and the availability of acceptable feedstocks. Electrodes directly converting solid iron-oxide particles to metal circumvent traditional mass-transport limitations but are sensitive to both the particle size and nanoscale morphology of reactants. Furthermore, the effect of these properties on reactor throughput has not been systematically studied at model electrowinning surfaces. Here, we have used size-controlled, homologous α-Fe 2 O 3 particles to study how the nanoscale morphology of oxides influences the obtainable current density toward Fe metal and integrated these results in a technoeconomic model for alkaline iron electrowinning systems. Micron-scale α-Fe 2 O 3 with nanoscale porosity can be used to form Fe at current densities commensurate with industrial water electrolysis (>0.6 A cm –2 ) in the absence of external convection, providing a path to cost-competitive and scalable ironmaking using electrochemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward a Better Understanding of Ni Coarsening in Solid Oxide Cells: NiH on Ni (111) Examined Using a Combined Theoretical Approach

The coarsening of the Ni particles in the hydrogen electrode of solid oxide cells (SOCs) is an important degradation mechanism. Here, in this paper, density-functional theory and kinetic Monte Carlo methods are used to explore our recent hypothesis that the surface diffusion of NiH may cause faster Ni coarsening in electrolysis cell mode under an overpotential. Using both methods, the diffusion constant or diffusivity of NiH on Ni (111) is determined as the product of the surface coverage and single-molecule diffusivity for the first time considering all possible diffusion paths. It is then determined versus overpotential at the triple-phase boundary of the hydrogen electrode assuming a typical operating temperature of the SOC. Under a significant overpotential, the diffusivity of NiH is found to be sufficiently large to support the above hypothesis that NiH may promote Ni coarsening. However, based on the adsorption configurations identified, the dissociation and reformation of NiH on Ni (111) could occur. Thus, more work is needed to develop a model of Ni coarsening considering both molecular and dissociated forms of NiH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deciphering the Conflict Between Ion and Electron Percolating Networks in Solid-State Battery Cathodes

High-energy- and power-density solid state batteries require an optimal cathode composition and microstructural arrangement of cathode active material, solid-state electrolyte, conductive carbon, and binder to simultaneously support lithium-ion transport, electron conduction, and storage capacity. The ion and electron conducting phases in solid-state cathodes counteract each other's percolating networks as their mass ratios increase or decrease relative to each other. Here, we investigate targeted mass ratio variations of argyrodite solid electrolyte and two different types of conductive carbon (particles and fibers) in composite LiNi0.8Mn0.1Co0.1O2 (NMC811) solid-state cathodes to ascertain the ionic-electronic tradeoffs in cathode performance. Through ionic and electronic conductivity measurements on composite cathodes, as well as rate-testing and cycling performance in full cells, it is shown that the conductive carbon fibers form a percolative electronic network within the composite at a lower mass ratio (3-5 wt%) than particulate carbon (>5 wt%). The threshold to achieve electronic percolation coincides with higher accessible capacity in the cathode as the active material particles become electronically connected. However, carbon loadings beyond this percolation threshold lead to increased ion transport resistance, arising from disruptions to ionic conduction pathways and degraded contact at the interface between the electrolyte and active materials. Imaging, spectroscopy, and physics-based models quantitatively describe the relationship between carbon and electrolyte compositions and the cell's capacity and rate performance through percolation theory. This work demonstrates the importance of quantitatively understanding percolating networks in solid-state cells and that strategic engineering of conductive carbon morphologies can further increase the energy- and power-density of solid-state cells.

25 ENERGY STORAGE↗

Application of soot carbonization kinetics to deduce meaningful soot formation rates in premixed flat flames

Soot formation rates measured in fuel-rich premixed flat flames are frequently used to calibrate or validate chemical kinetic models of soot formation. Unfortunately, these flames feature an extended region of soot precursor particle inception and carbonization that complicates interpretation of soot measurements and leads to a fundamental inconsistency in the nature of the soot material that is modeled versus what is being measured when using non-intrusive, optical techniques. In the work presented here, previously reported data on two canonical sooting ethylene-air premixed flames at 1 atm pressure are interpreted via a new analysis approach that combines soot optical dispersion coefficient measurements with soot carbonization kinetics. This analytical approach explicitly accounts for the production of poorly ordered soot precursor particle mass and its carbonization over time in the flames, providing a clear distinction between the formation rate of precursor particles and their transformation into ordered, solid soot particulate mass. In particular, the results of the analysis show that the precursor particles form much earlier in the flame than the majority of the carbonized soot and their formation rate is two to three times faster than that of ordered soot. The results also show that particle agglomeration begins when the particles are at an intermediate state of carbonization. In conclusion, these results offer a valuable new interpretation of these important datasets and should lead to substantial improvements in the development and calibration of quantitative soot models.

Soot formation↗

Operando Neutron Imaging of Reaction Extent and Particle Swelling Informs Limiting Factors for Salt Hydrate Thermochemical Energy Storage

Salt hydrates are a promising thermochemical energy storage medium that stores heat through the reversible uptake (hydration) and release (dehydration) of water vapor. Our study deploys operando neutron imaging to investigate salt hydrate performance with high spatial resolution (42 μm pixels). For flow over a packed bed with diffusion-driven transport, measurements reveal the formation of a solid diffusion layer due to particle swelling for the pure SrBr2 salt. In contrast, the SrBr2–vermiculite composite exhibits significantly less swelling and more than a 2-fold increase in the apparent water vapor diffusivity. For axial flow through a packed bed, neutron imaging confirms theoretically predicted transitions from a moving reaction front to a homogeneous profile with an increase in humid air flow rate. Our study establishes neutron imaging as a powerful technique to advance fundamental understanding of thermochemical systems and help guide composite material design.

Kinzer, Bryan [ORNL] (ORCID:0000000337804910)↗

Wafer-Free Crystalline Silicon Solar Cells (CRADA Final Report)

This CRADA project, based on the DOE Solar Energy Technologies Office (SETO) Solar Prize Voucher program, helped Leap Photovoltaics to develop methodologies to immobilize Si particles by permanently attaching them to an Al-coated substrate and thereby forming carrier-selective electrical contacts to the Si particles. The bigger goal was to help Leap Photovoltaics develop these immobilized and contacted particle arrays into relatively efficient, inexpensive, and industrially relevant solar cells. By using Si particles instead of wafers in a solar cell absorber layer, one can avoid costs associated with growing monocrystalline Si ingots, then diamond-sawing them into wafers, then processing wafers into cells – a mainstream practice in today's high-efficiency Si cell and module technology. Monocrystalline or polycrystalline Si particles can be obtained in various ways: for example, Si kerf from wafer sawing is monocrystalline; recycled Si cell wafers can be ball-milled into particles; particles can be grown using various gas-phase techniques (mostly from SiH4). These Si particles can be assembled onto a substrate and serve as an absorber layer for the solar cell, absorbing photons to generate photocarriers. The challenge with this technique is to collect photocarriers from individual Si particles, with separation of photogenerated electrons to the negative cell’s electrode and positive photogenerated holes to the positive electrode. Therefore, each particle must have two isolated, carrier-selective contacts: one for electrons and one for holes. Plus, particles need to be immobilized onto a solid substrate. The goal of this work was focused on the immobilization of Si particles and creating hole-selective contact to them at the same time, using industrially relevant Si photovoltaic (PV) cell technology: screen printing of Al back-surface field electrodes. This is used in the mainstream Propane Education and Research Council (PERC) technology for hole-collecting contacts at the back of the cell. The work performed at NREL consisted of screen printing of Al metal paste on substrates, spreading Si particles onto it, and thermally processing the structures to form hole-collecting contacts. The final structures were investigated by scanning electron microscopy (SEM) after focused ion beam (FIB) cross-sectioning and polishing. The work was done jointly by NREL staff and Leap Photovoltaics (Leap PV) employees stationed at NREL. The samples were then taken to Leap PV for further processing. Training the Leap PV employee on various NREL techniques (laser cutting, screen printing, thermal processing, characterization) was part of the scope.

14 SOLAR ENERGY↗

Decoding Gas Evolution Pathways and Interfacial Chemistry in Layered Oxide Cathodes for Safer Sodium‐Ion Batteries

Sodium-ion batteries (SIBs) are attractive for the low cost and abundance of sodium. Yet, gas evolution—a critical challenge in SIBs—remains underexplored. Here, online electrochemical mass spectrometry is used to probe gas evolution in layered oxide cathodes with various compositions, cutoff voltages, dopants, and particle morphologies. Compared to LiNiO 2 (LNO), NaNiO 2 releases more gas, even at lower states of charge, due to the higher covalency of Ni─O bond caused by the more ionic Na─O bond through the inductive effect. Among Co, Mn, Al, and Mg, Mn and Mg doping suppress gas release most effectively by enhancing the metal-oxygen bond strength. NaNi 1/3 Fe 1/3 Mn 1/3 O 2 (NFM) cathodes synthesized via coprecipitation (CP-NFM) and solid-state routes exhibit distinct particle morphologies; CP-NFM exhibits more gas evolution, yet secondary particle morphology helps reduce it through differential cathode-electrolyte reactivity between inner and outer primary particles. Among Li, Ti, Mg, and Cu doping in NFM, Li has the largest effect, reducing gas levels comparable to LNO. Nuclear magnetic resonance and X-ray photoelectron spectroscopies reveal that electrolyte solvent decomposition mainly produces organic-rich cathode-electrolyte interphase (CEI) rather than soluble species. NaPF 6 salt further exacerbates cathode-electrolyte reactions, forming surface Na 2 O species. The findings provide actionable guidance for designing safer, durable SIBs.

25 ENERGY STORAGE↗

Computing chemical potentials with machine-learning-accelerated simulations to accurately predict thermodynamic properties of molten salts

The successful design and deployment of next-generation nuclear technologies heavily rely on thermodynamic data for relevant molten salt systems. However, the lack of accurate force fields and efficient methods has limited the quality of thermodynamic predictions from atomistic simulations. Here we propose an efficient free energy framework for computing chemical potentials, which is the central free energy quantity behind many thermodynamic properties. We accelerate our simulations without sacrificing accuracy by using machine learning interatomic potentials trained on density functional theory (DFT) data. Using lithium chloride as our model system, we compute chemical potentials with DFT-accuracy for solid and liquid phases by transmuting ions into noninteracting particles. Notably, in the liquid phase, we demonstrate consistency whether we transmute one ion pair or the entire system into ideal gas particles. By locating the temperature where the chemical potential of solid and liquid phases cross, we predict a melting point of 880 ± 18 K for lithium chloride, which is remarkably close to the experimental value of 883 K. With this successful demonstration, we lay the foundation for high-throughput thermodynamic predictions of many properties that can be derived from the chemical potentials of the minority and majority components in molten salts.

Gibson, Luke D. [Oak Ridge National Laboratory (OR↗

Beam test performance studies of CMS Phase-2 Outer Tracker module prototypes

A new tracking detector will be installed as part of thePhase-2 upgrade of the CMS detector for the high-luminosity LHC era.This tracking detector includes the Inner Tracker, equipped withsilicon pixel sensor modules, and the Outer Tracker, consisting ofmodules with two parallel stacked silicon sensors. The Outer Trackerfront-end ASICs will be able to correlate hits from chargedparticles in these two sensors to perform on-module discriminationof transverse momenta (p$_{T}$). The p$_{T}$information is generated at a frequency of 40 MHz and will be usedin the Level-1 trigger decision of CMS. Prototypes of theso-called 2S modules were tested at the Test Beam Facility at DESYHamburg between 2019 and 2020. These modules use the finalfront-end ASIC, the CMS Binary Chip (CBC), and for the firsttime the Concentrator Integrated Circuit (CIC), optical readoutand on-module power conversion. In total, seven modules were tested,one of which was assembled with sensors irradiated with protons. Animportant aspect was to show that it is possible to read out modulessynchronously. A cluster hit efficiency of about 99.75 % wasachieved for all modules. The CBC p$_{T}$ discriminationmechanism has been verified to work together with the CIC andoptical readout. The measured module performance meets therequirements for operation in the upgraded CMS tracking detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Novel indium phosphide charged particle detector characterization with a 120 GeV proton beam

Thin film detectors which incorporate semiconductor materials other than silicon have the potential to build upon their unique material properties and offer advantages such as faster response times, operation at room temperature, and radiation hardness. To explore the possibility, promising candidate materials were selected, and particle tracking detectors were fabricated. An indium phosphide detector with a metal-intrinsic-metal structure has been fabricated for particle tracking. The detector was tested using radioactive sources and a high energy proton beam at Fermi National Accelerator Laboratory. In addition to its simplistic design and fabrication process, the indium phosphide particle detector showed a very fast response time of hundreds of picoseconds for the 120 GeV protons, which are comparable to the ultra-fast silicon detectors. This fast-timing response is attributed to the high electron mobility of indium phosphide. Such material properties can be leveraged to build novel detectors with superlative performance.

47 OTHER INSTRUMENTATION↗

LeaPP: Learning Pathways to Polymorphs through Machine Learning Analysis of Atomic Trajectories

Understanding the mechanisms underlying crystal nucleation and growth is crucial for many technological applications. Due to the short length and time scales involved, crystal nucleation is often studied using molecular simulations. Most existing approaches to extract the nucleation mechanism from simulations focus on the analysis of static snapshots of the configurations, potentially overlooking subtle local fluctuations and the history of the particles involved in the formation of solid nuclei. Here, in this work, we propose a novel methodology called LeaPP that categorizes nucleation trajectories based on the temporal information of their constituent particles. We leverage the time evolution of the local environment of the crystallizing particles to encapsulate the relationship between the structure and dynamics and distinguish between different evolving particle paths. Identification of the distinct particle paths further enables characterizing the nucleation trajectories into different pathways. Collectively, LeaPP provides a more nuanced understanding of nucleation through an unsupervised approach with lesser dependence on traditional order parameters. Furthermore, the pathways identified by LeaPP are predictive of the resulting polymorph. We demonstrate LeaPP on three different systems─Lennard-Jones-like particles, Ni 3 Al, and water on surfaces. The general methodology underlying LeaPP─considering the time evolution of the building blocks─applies to a wide range of self-assembly problems.

36 MATERIALS SCIENCE↗