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Presynthetic Redox Gated Metal-to-Insulator Transition and Photothermoelectric Properties in Nickel Tetrathiafulvalene-Tetrathiolate Coordination Polymers

Photothermoelectric (PTE) materials are promising candidates for solar energy harvesting and photodetection applications, especially for near-infrared (NIR) wavelengths. Although the processability and tunability of organic materials are highly advantageous, examples of organic PTE materials are comparatively rare and their PTE performance is typically limited by poor photothermal (PT) conversion. Here, we report the use of redox-active Sn complexes of tetrathiafulvalene-tetrathiolate (TTFtt) as transmetalating agents for the synthesis of presynthetically redox tuned NiTTFtt materials. Unlike the neutral material NiTTFtt, which exhibits n-type glassy-metallic conductivity, the reduced materials Li 1.2 Ni 0.4 [NiTTFtt] and [Li(THF) 1.5 ] 1.2 Ni 0.4 [NiTTFtt] (THF = tetrahydrofuran) display physical characteristics more consistent with p-type semiconductors. The broad spectral absorption and electrically conducting nature of these TTFtt-based materials enable highly efficient NIR-thermal conversion and good PTE performance. Furthermore, in contrast to conventional PTE composites, these NiTTFtt coordination polymers are notable as single-component PTE materials. As a result, the presynthetically tuned metal-to-insulator transition in these NiTTFtt systems directly modulates their PT and PTE properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A New Integrated Analysis Suite for Fast-Ion Study in KSTAR

Here, an integrated workflow for fast-ion analysis was developed by adapting the One Modeling Framework for Integrated Task (OMFIT) workflow manager to support a standard and unified analysis platform for KSTAR users. The newly established analysis suite offers a graphical user interface–based workflow to enable users to readily access and handle experimental data archived in various data formats and servers. Further, users can analyze the data by importing modules designed for conducting certain tasks, such as profile fitting, equilibrium reconstruction, and postprocessing of tokamak data. The procedures for preparing the inputs for fast-ion simulations are streamlined by a common workflow manager, which enables the parallel processing of various tasks to efficiently analyze large fast-ion datasets. The OMFIT platform comprises a flexible Python-based application that enables users to freely manipulate the Python scripts for applications that are unavailable in the standard workflow. The framework also offers mapping tools to translate the output data into the Integrated Modeling and Analysis Suite format to maintain application compatibility for future ITER burning plasma experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Verification and Validation of Open-Source Computational Fluid Dynamics Capabilities in MOOSE

The Multiphysics Object Oriented Simulation Environment (MOOSE) advances predictive modeling in nuclear research by simplifying the application design process and making modeling more efficient and accessible to researchers and the broader community. Because of MOOSE’s critical role in the scientific computation field, verification and validation are important to evaluate the reliability and credibility of MOOSE’s code, simulations, and models. To assess MOOSE’s Navier Stokes module and turbulence models, the following verification and validation University of Manchester ERCOFTAC cases were simulated in MOOSE, and the results were compared: Case 032 Turbulent Flow in a 2D Channel Case 079 Natural Convection in an Enclosed Cavity

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

A high-performance lung-inspired ceramic 3D-printed heat exchanger for high-temperature energy-efficient systems

The thermal-to-electric conversion efficiency of next-generation supercritical carbon dioxide and concentrated solar power plants is significantly augmented by operating at temperatures exceeding 1000 °C if durable, compact, high-temperature heat exchangers (HXs) are developed. Whereas metal 3D-printed HXs fail to operate under extreme temperature conditions, ceramic 3D-printed HXs are deemed promising candidates for high-temperature, highly oxidizing environments. Ceramic 3D-printed HXs, however, exhibit a high gas permeability issue through hot and cold separating walls due to an excessive non-volatile photopolymer content utilized. Here, in this work, a novel leak-free lung-inspired ceramic 3D-printed HX employing a highly complex heat transfer topology is introduced for high-temperature energy-efficient systems. The high permeability issue of ceramic 3D-printed HXs is fully eliminated through a uniform zinc-based coating. It was determined that the effective thermal conductivity of the sintered ceramic heat exchangers is affected by the coated layer. The high-temperature thermal and hydraulic characteristics of the lung-inspired ceramic 3D-printed HX are comprehensively examined and compared against a millichannel 3D-printed HX module. Experimental results indicated that the lung-inspired 3D-printed ceramic HX significantly outperforms its millichannel counterpart. The lung-inspired HX shows a volume-based power density of 8.2 MW/m3 at a hot-side inlet air temperature of 700°C, a 71 % improvement compared with that of the millichannel HX. More importantly, the higher thermal duty of the lung-inspired 3D-printed HX is realized at a lower normalized pressure drop penalty of 510 Pa/W, 22 % lower than that of the millichannel ceramic HX. This study accelerates the advancement of high-performance ceramic 3D-printed HXs with complex topologies for high-temperature energy-efficient systems and/or corrosive environments.

42 ENGINEERING↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Identification of Blue Horizontal Branch Stars with Multimodal Fusion

Blue Horizontal Branch stars (BHBs) are ideal tracers to probe the global structure of the milky Way (MW), and the increased size of the BHB star sample could be helpful to accurately calculate the MW's enclosed mass and kinematics. Large survey telescopes have produced an increasing number of astronomical images and spectra. However, traditional methods of identifying BHBs are limited in dealing with the large scale of astronomical data. A fast and efficient way of identifying BHBs can provide a more significant sample for further analysis and research. Therefore, in order to fully use the various data observed and further improve the identification accuracy of BHBs, we have innovatively proposed and implemented a Bi-level attention mechanism-based Transformer multimodal fusion model, called Bi-level Attention in the Transformer with Multimodality (BATMM). The model consists of a spectrum encoder, an image encoder, and a Transformer multimodal fusion module. The Transformer enables the effective fusion of data from two modalities, namely image and spectrum, by using the proposed Bi-level attention mechanism, including cross-attention and self-attention. As a result, the information from the different modalities complements each other, thus improving the accuracy of the identification of BHBs. The experimental results show that the F1 score of the proposed BATMM is 94.78%, which is 21.77% and 2.76% higher than the image and spectral unimodality, respectively. It is therefore demonstrated that higher identification accuracy of BHBs can be achieved by means of using data from multiple modalities and employing an efficient data fusion strategy.

79 ASTRONOMY AND ASTROPHYSICS↗

Upgrade of the mechanically pumped CO 2 two-phase cooling system for the alpha magnetic spectrometer on the international space station

This study describes the successful upgrade of a mechanically pumped CO 2 two-phase cooling system in space by designing a new pump module for the Alpha Magnetic Spectrometer-02 on the International Space Station. Key factors for mission success are emphasized, including achieving high coolant filling accuracy within 10% of the target and maintaining system stability within ±1 °C. The impact of adding radiators to improve cooling efficiency is examined, and it is found that operating multi-radiators out-of-phase does not significantly affect system reliability. The centrifugal pump design is shown to allow for better lubricant circulation, while the in-house designed controller incorporates protective measures to prevent cavitation, overheating, and over-current. Further, this research advances the understanding of circulation loop systems and their upgrades in space and demonstrates the potential for extending the lifetime of space-borne mechanically pumped two-phase cooling systems.

42 ENGINEERING↗

Guest-Controlled Incommensurate Modulation in a Meta-Rigid Metal–Organic Framework Material

Structural transitions of host systems in response to guest binding dominate many chemical processes. We report an unprecedented type of structural flexibility within a meta-rigid material, MFM-520, which exhibits a reversible periodic-to-aperiodic structural transition resulting from a drastic distortion of a [ZnO 4 N] node controlled by the specific host–guest interactions. The aperiodic crystal structure of MFM-520 has no three-dimensional (3D) lattice periodicity but shows translational symmetry in higher-dimensional (3 + 2)D space. In this work, we have directly visualized the aperiodic state which is induced by incommensurate modulation of the periodic framework of MFM-520·H 2 O upon dehydration to give MFM-520. Filling MFM-520 with CO 2 and SO 2 reveals that, while CO 2 has a minimal structural influence, SO 2 can further modulate the structure incommensurately. MFM-520 shows exceptional selectivity for SO 2 under flue-gas desulfurization conditions, and the facile release of captured SO 2 from MFM-520 enabled the conversion to valuable sulfonamide products. MFM-520 can thus be used as a highly efficient capture and delivery system for SO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electron–phonon physics from first principles using the EPW code

EPW is an open-source software for ab initio calculations of electron–phonon interactions and related materials properties. The code combines density functional perturbation theory and maximally localized Wannier functions to efficiently compute electron–phonon coupling matrix elements, and to perform predictive calculations of temperature-dependent properties and phonon-assisted quantum processes in bulk solids and low-dimensional materials. Here, we report on significant developments in the code since 2016, namely: a transport module for the calculation of charge carrier mobility under electric and magnetic fields using the Boltzmann transport equation; a superconductivity module for calculations of phonon-mediated superconductors using the anisotropic multi-band Eliashberg theory; an optics module for calculations of phonon-assisted indirect transitions; a module for the calculation of small and large polarons without supercells; and a module for calculating band structure renormalization and temperature-dependent optical spectra using the special displacement method. For each capability, we outline the methodology and implementation and provide example calculations.

36 MATERIALS SCIENCE↗

Prehydrodynamic evolution and its impact on quark-gluon plasma signatures

State-of-the-art hydrodynamic models of heavy-ion collisions have considerable theoretical model uncertainties in the description of the very early prehydrodynamic stage. Here we add a new computational module, K T Iso, that describes the prehydrodynamic evolution kinetically, based on the relativistic Boltzmann equation with collisions treated in the isotropization time approximation. As a novelty, K T Iso allows for the inclusion and evolution of initial-state momentum anisotropies. To maintain computational efficiency K T Iso assumes strict longitudinal boost invariance and allows collisions to isotropize only the transverse momenta. We use it to explore the sensitivity of hadronic observables measured in relativistic heavy-ion collisions to initial-state momentum anisotropies and microscopic scattering during the prehydrodynamic stage.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks

The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO 2 between ecosystems and the atmosphere, offering a unique opportunity to study ecosystem responses to climate change. NEE is the difference between the total CO 2 release due to all respiration processes (RECO), and the gross carbon uptake by photosynthesis (GPP). These two gross CO 2 fluxes are derived from EC measurements by applying partitioning methods that rely on physiologically based functional relationships with a limited number of environmental drivers. However, the partitioning methods applied in the global FLUXNET network of EC observations do not account for the multiple co-acting factors that modulate GPP and RECO flux dynamics. To overcome this limitation, we developed a hybrid data-driven approach based on combined neural networks (NN C-part ). NN C-part incorporates process knowledge by introducing a photosynthetic response based on the light-use efficiency (LUE) concept, and uses a comprehensive dataset of soil and micrometeorological variables as fluxes drivers. We applied the method to 36 sites from the FLUXNET2015 dataset and found a high consistency in the results with those derived from other standard partitioning methods for both GPP (R 2 > .94) and RECO (R 2 > .8). High consistency was also found for (a) the diurnal and seasonal patterns of fluxes and (b) the ecosystem functional responses. NNC-part performed more realistic than the traditional methods for predicting additional patterns of gross CO 2 fluxes, such as: (a) the GPP response to VPD, (b) direct effects of air temperature on GPP dynamics, (c) hysteresis in the diel cycle of gross CO 2 fluxes, (d) the sensitivity of LUE to the diffuse to direct radiation ratio, and (e) the post rain respiration pulse after a long dry period. In conclusion, NN C-part is a valid data-driven approach to provide GPP and RECO estimates and complementary to the existing partitioning methods.

54 ENVIRONMENTAL SCIENCES↗

Scaling Up: Demonstrating Risk Reduction and Cost Compression for Commercial Heat Pump Water Heaters - CRADA 625 (Abstract)

Commercial heat pump water heater (CHPWH) systems significantly decarbonize the commercial and multifamily sectors by eliminating the reliance on gas-fired water heating. CHPWH systems are also well suited to include load shift controls that enable load-up and shed commands for supporting grid reliability and time-of-use pricing structure. However, they have not had wide adoption due to factors including price, complexity, and perceived risk. Although CHPWHs have been available in the US for decades, they have not made significant market gains in part because the systems have required significant and costly engineering design expertise and proved lackluster performance. Successful widespread market adoption requires a different approach; a shift from the current custom specialized expertise project design and installation to a repeatable approach that requires little specialized knowledge or expertise and can deliver persistent performance. Using this type of holistic systems approach requires effectively integrating four CHPWH system key components: primary air-to-water heat pumps; primary thermal storage tanks, a temperature maintenance system, and a control system which has capabilities to manage the primary heat pump cycles, any back-up, supplemental, or temperature maintenance heating, alarms, and grid connectivity allowing for demand response (DR), and/or load shifting. The project team has developed and will implement a suite of tools to support faster, less expensive, and more reliable field installations of CHPWH technology and with the resulting data used to further improve the tool set. These tools include: (1) A tool for optimizing system size and costs. (2) A tool that predicts annual energy use and overall system efficiency. (3) The Advanced Water Heater Specification (AWHS 8.0) defining the components of a full CHPWH system addressing performance requirements by climate zone. (4) The Qualified Products List: (QPL) of approved products that meet the specifications requirements. (5) Training materials including online on-demand modules, instructor-led training, and virtual interactive video tours of CHPWH installations in multifamily buildings. Demonstration site identification in low-income buildings in underserved communities is currently underway. Preliminarily, the team anticipates having three demonstrations in the Pacific Northwest and three in the Northeast for a total of six sites. After the demonstration sites are finalized, and M&V instrumentation installations are complete, the team will gather performance data and confirm whether the CHPWH systems perform as predicted and use the data to improve the existing tools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

CACTUS: CO 2 Aerogel Capture Towards Utilization and Sequestration

The CACTUS project aimed to develop a novel solid sorbent and sorption module prototype for direct air capture (DAC) of carbon dioxide, by a moisture-swing adsorption (MSA) mechanism. Because MSA uses changes in humidity, not temperature to switch the sorbent from capturing CO 2 to releasing concentrated CO 2 it is > 4X more energy-efficient than the thermal swing process. The goal was to develop a sorbent with a CO 2 capture capacity of 1 mmol CO 2 /g sorbent (or 0.75 mmol CO 2 /g structured sorbent), at a projected scaled cost of < $\$$15/kg sorbent and demonstration of a path to < $\$$100/ton CO 2 . At the end of the project, we achieved 0.8 mmol CO 2 /g sorbent powders, 0.37 mmol CO 2 /g structured sorbent (50% of target), at a projected cost of $\$$29/kg sorbent and an estimated cost of $\$$160/ton CO 2 . The key innovation was SRI’s patented polymer aerogel synthesis platform, which was adapted to produce a nanoporous aerogel with a high density of CO 2 -adsorbing quaternary ammonium groups. This research discovered a new ammonium polymer sorbent and identified a chemical path for its fabrication. The new process solved the monomer immiscibility challenge encountered with the initial method (ammonium is hydrophilic and the crosslinker is hydrophobic). The team fabricated structured sorbent sheets consisting of a non-woven porous substrate impregnated with ammonium polymer and demonstrated its operation in custom made breakthrough test setup MSA DAC built at SRI, and which operates similarly to the envisioned large-scale CO 2 capture plant, to provide data for techno-economic analysis (TEA). TEA sensitivity analysis indicated that ∼$\$$100/ton CO 2 can be achieved if the target capacity of 0.75 mmol CO 2 /g structured sorbent is met. Also identified routes to decrease sorbent manufacturing cost to ∼$\$$19/kg by reducing amounts and recycling the organic solvents. More work is needed on transitioning process manufacturing from powders (which showed a capacity of up to 0.8 mmol/g sorbent) to structured sheets which showed a capacity of 0.37 mmol CO 2 /g structured sorbent (or 0.44 mmol/g sorbent if one excludes the inert porous substrate). This is likely due to different micro/nano-structure of the sorbent and material processing constraints at the laboratory scale. Sorbent cycling studies (> 100 cycles) are needed to investigate its performance stability over time.

99 GENERAL AND MISCELLANEOUS↗

A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling

Numerical solvers of partial differential equations (PDEs) have been widely employed for simulating physical systems. However, the computational cost remains a major bottleneck in various scientific and engineering applications, which has motivated the development of reduced-order models (ROMs). Recently, machine-learning-based ROMs have gained significant popularity and are promising for addressing some limitations of traditional ROM methods, especially for advection dominated systems. In this chapter, we focus on a particular framework known as Latent Space Dynamics Identification (LaSDI), which transforms the high-fidelity data, governed by a PDE, to simpler and low-dimensional latent-space data, governed by ordinary differential equations (ODEs). These ODEs can be learned and subsequently interpolated to make ROM predictions. Each building block of LaSDI can be easily modulated depending on the application, which makes the LaSDI framework highly flexible. In particular, we present strategies to enforce the laws of thermodynamics into LaSDI models (tLaSDI), enhance robustness in the presence of noise through the weak form (WLaSDI), select high-fidelity training data efficiently through active learning (gLaSDI, GPLaSDI), and quantify the ROM prediction uncertainty through Gaussian processes (GPLaSDI). We demonstrate the performance of different LaSDI approaches on Burgers equation, a non-linear heat conduction problem, and a plasma physics problem, showing that LaSDI algorithms can achieve relative errors of less than a few percent and up to thousands of times speed-ups.

Computational Engineering, Finance, and Science (c↗

Tailorable Multi–Modular Pore–Space–Partitioned Vanadium Metal–Organic Frameworks for Gas Separation

Currently, few porous vanadium metal-organic frameworks (V-MOFs) are known and even fewer are obtainable as single crystals, resulting in limited information on their structures and properties. Here this work demonstrates remarkable promise of V-MOFs by presenting an extensible family of V-MOFs with tailorable pore geometry and properties. The synthesis leverages inter-modular synergy on a tri-modular pore-partitioned platform. New V-MOFs show a broad range of structural features and sorption properties suitable for gas storage and separation applications for C 2 H 2 /CO 2 , C 2 H 6 /C 2 H 4 , and C 3 H 8 /C 3 H 6 . The c/a ratio of the hexagonal cell, a measure of pore shape, is tunable from 0.612 to 1.258. Other tunable properties include pore size from 5.0 to 10.9 Å and surface area from 820 to 2964 m 2 g –1 . With C 2 H 2 /CO 2 selectivity from 3.3 to 11 and high uptake capacity for C 2 H 2 from 65.2 to 182 cm 3 g –1 (298K, 1 bar), an efficient separation is confirmed by breakthrough experiments. The near-record high uptake for C 2 H 6 (166.8 cm 3 g –1 ) contributes to the promise for C 2 H 6 -selective separation of C 2 H 6 /C 2 H 4 . The multi-module pore expansion enables transition from C 3 H 6 -selective to more desirable C 3 H 8 -selective separation with extraordinarily high C 3 H 8 uptake (254.9 cm 3 g –1 ) and high separation potential (1.25 mmol g –1 ) for C 3 H 8 /C 3 H 6 (50:50 v/v) mixture.

36 MATERIALS SCIENCE↗

Neutral Mode Dominates the Forced Global and Regional Surface Temperature Response in the Past and Future

Abstract Using a large suite of Green's function perturbation experiments, we construct the emergent dynamical operator for surface temperature and extract the most excitable mode. The leading mode turns out to be the most dominant mode excited by the climate forcing of doubling CO 2 , alone capturing 56% of the total spatial variances of the surface temperature response. The pattern of the leading mode is partly organized by the atmospheric annular modes in both hemispheres, and further modulated by the feedbacks from ocean circulations. Though derived from a single model, the leading mode can capture the spatio‐temporal variabilities of the global mean surface temperature over the past century in both the CMIP6 model simulations and observations. Moreover, the leading mode is most efficiently excited by radiative forcings from the midlatitude bands centered around 45°N and 25°S, where most human activities take place, suggesting the potency of human influence on the climate change.

54 ENVIRONMENTAL SCIENCES↗

Design, upgrade and characterization of the silicon photomultiplier front-end for the AMIGA detector at the Pierre Auger Observatory

AMIGA (Auger Muons and Infill for the Ground Array) is an upgrade of the Pierre Auger Observatory to complement the study of ultra-high-energy cosmic rays (UHECR) by measuring the muon content of extensive air showers (EAS). It consists of an array of 61 water Cherenkov detectors on a denser spacing in combination with underground scintillation detectors used for muon density measurement. Each detector is composed of three scintillation modules, with 10 m 2 detection area per module, buried at 2.3 m depth, resulting in a total detection area of 30 m 2 . Silicon photomultiplier sensors (SiPM) measure the amount of scintillation light generated by charged particles traversing the modules. In this paper, the design of the front-end electronics to process the signals of those SiPMs and test results from the laboratory and from the Pierre Auger Observatory are described. Compared to our previous prototype, the new electronics shows a higher performance, higher efficiency and lower power consumption, and it has a new acquisition system with increased dynamic range that allows measurements closer to the shower core. The new acquisition system is based on the measurement of the total charge signal that the muonic component of the cosmic ray shower generates in the detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Statistical Performance Analysis on Approximately 320 Perovskite Single- and Two-Junction Solar Cells and Modules from >30 Global Sources

As perovskite photovoltaics (PV) advance from the laboratory to commercial prototypes, their accurate and reliable performance testing is becoming increasingly important. The well documented dynamic response of perovskite solar cells to an external applied voltage has led to the development of steady-state performance measurement methods; however, these methods have not been widely adopted by the perovskite PV community. A key reason for this is that steady-state measurement methods take tens of minutes to complete, as opposed to conventional "fast" current-voltage (I-V) measurements usually lasting a few seconds. Fast I-Vs arise from a snapshot, almost always not a steady-state condition of the device; however, given their widespread use, the question arises: how do performance parameters of perovskite PV compare when measured with fast I-V and with a steady-state method? We compile results from ca. 320 perovskite PV cells and modules, including single junction, and two-terminal perovskite-perovskite and perovskite-Si tandems, and show that fast I-Vs can provide a useful measure of the open-circuit voltage of the devices, while the short-circuit current and the overall efficiency can be widely misestimated. We discuss implications of these findings on performance testing protocols and propose possible options for fast and accurate testing of perovskite PV.

asymptotic↗