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At least 883 records · Page 49

AI-assisted detector design for the EIC (AID(2)E)

Artificial Intelligence is poised to transform the design of complex, large-scale detectors like ePIC at the future Electron Ion Collider. Featuring a central detector with additional detecting systems in the far forward and far backward regions, the ePIC experiment incorporates numerous design parameters and objectives, including performance, physics reach, and cost, constrained by mechanical and geometric limits. This project aims to develop a scalable, distributed AI-assisted detector design for the EIC (AID(2)E), employing state-of-the-art multiobjective optimization to tackle complex designs. Supported by the ePIC software stack and using G EANT 4 simulations, our approach benefits from transparent parameterization and advanced AI features. The workflow leverages the PanDA and iDDS systems, used in major experiments such as ATLAS at CERN LHC, the Rubin Observatory, and sPHENIX at RHIC, to manage the compute intensive demands of ePIC detector simulations. Tailored enhancements to the PanDA system focus on usability, scalability, automation, and monitoring. Ultimately, this project aims to establish a robust design capability, apply a distributed AI-assisted workflow to the ePIC detector, and extend its applications to the design of the second detector (Detector-2) in the EIC, as well as to calibration and alignment tasks. Additionally, we are developing advanced data science tools to efficiently navigate the complex, multidimensional trade-offs identified through this optimization process.

97 MATHEMATICS AND COMPUTING↗

Development of a bi-solvent liquid scintillator with slow light emission

One of the most promising approaches for the next generation of neutrino experiments is the realization of large hybrid Cherenkov/scintillation detectors made possible by recent innovations in photodetection technology and liquid scintillator chemistry. The development of a potentially suitable future detector liquid with particularly slow light emission is discussed in the present publication. This cocktail is compared with respect to its fundamental characteristics (scintillation efficiency, transparency, and time profile of light emission) with liquid scintillators currently used in large-scale neutrino detectors. In addition, the optimization of the admixture of wavelength shifters for a scintillator with particularly high light emission is presented. Furthermore, the pulse-shape discrimination capabilities of the novel medium was studied using a pulsed particle accelerator driven neutron source. Beyond that, purification methods based on column chromatography and fractional vacuum distillation for the co-solvent DIN (Diisopropylnaphthalene) are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DUNE Photon Detection System

The Deep Underground Neutrino Experiment (DUNE) aims to provide a broad physics program primarily addressed to probing CP violation in the neutrino sector and identifying the neutrino mass hierarchy. The search for proton decay, the observation of supernova neutrino bursts, and the investigation of solar neutrinos represent other additional goals of DUNE experiment, which can be enhanced by the use and the high performances of the Photon Detection System (PDS). Using the technology based on liquid argon Time Projection Chamber (LArTPC), the experiment plans to observe neutrino interactions inside detectors located 1300 km away from the Long Baseline Neutrino Facility (LBNF) at Fermi National Accelerator Laboratory (FNAL), where the neutrinos are produced. The experiment consists of two main parts, respectively the far and near detectors. The far site will comprise four detector modules. The first module is constituted by a vertical drift single-phase LArTPC, while the second module provides a horizontal drift single-phase LArTPC. The configurations of the other modules are still under definition. Neutrino detection in LArTPCs is achieved by identifying the charge and light generated from its interactions with liquid argon. The wire planes of the instrumented anode and the PDS detect these signals, respectively. The PDS in the first two modules, detailed in the present document, uses a modified version of the so-called ARAPUCA technology, named X-ARAPUCA. This system consisting of a highly reflecting box with an entrance window made by dichroic filters and wavelength shifters, creates a trap to detect the VUV (128 nm) scintillation photons. The X-ARAPUCA of the first module is called Supercell, and it has dimensions of 488×100 mm 2 , while Megacell is the second module version, with an active area of 60×60 cm 2 . This latter configuration also represents a significant technological advancement. Since half of the modules are placed on the cathode at high voltage, they are powered and read out using innovative power-over-fiber (PoF) and signal-over-fiber (SoF) technologies. Meanwhile, the other half are installed in a membrane behind the field cage, with a total transparency of around 70%.

Neutrino detectors↗

Integrated assessment model diagnostics: key indicators and model evolution

Integrated assessment models (IAMs) form a prime tool in informing climate mitigation strategies. Diagnostic indicators that allow to compare these models can help to describe and explain differences in model projections. This also increases transparency and comparability. Earlier, the IAM community has developed an approach to diagnose models (Kriegler et al., 2015). Here we build on this, by proposing a selected set of well-defined indicators as a community standard, similar to metrics used for other modeling communities such as climate models. These indicators are the relative abatement index (RAI), emission reduction type index (ERT), inertia timescale (IT), fossil fuel reduction (FFR), transformation index (TI) and cost per abatement value (CAV). We apply the approach to 17 IAMs, including both older version as well as their latest versions, as applied in the IPCC 6th Assessment Report (AR6). The study shows that the approach can be easily applied and allows for comparison of model versions in time. The indicators and their trends can often be explained in terms of model characteristics and changes. We show that together, the set of six indicators can provide an useful indication of the main traits of the model and can roughly indicate the general model behavior. The results also show that there is often a considerable spread across the models. Interestingly, the diagnostic values often change for different model versions, but there does not seem to be a distinct trend across the different models.

54 ENVIRONMENTAL SCIENCES↗

Developing new pathways for energy and environmental decision-making in India: a review

Abstract India faces a dual challenge of economic development and responding to climate change. Although India’s per capita emissions are well below global average, the country is one of the world’s largest greenhouse gas emitters. Indian policymakers and stakeholders require high-quality data and research to assess low-emissions, sustainable development strategies. Peer-reviewed literature is a key source of this information and also a key venue for conversation amongst research leaders. This paper examines the recent peer-reviewed literature on India’s 2030 and 2050 pathways. We conducted a systematic literature review to identify key quantitative national modeling studies. From the 34 studies identified, we synthesized scenario data to draw common conclusions and identify critical research gaps. The main focus was on examining the coverage and the state of information available on low-carbon pathways. Overall, we find a few scenarios that are potentially consistent with a 2070 net-zero goal, but more limited assessment of pathways to reach net-zero emissions before this date. Mitigation pathways with greater ambition are required across all energy sectors to ensure a smooth transition to net-zero emissions by or before 2070. The scenarios confirm that reducing emissions to below 2 GtCO 2 yr −1 by mid-century would necessitate significant transformations of the Indian energy sector, such as, a decrease in unabated coal power capacity, transportation modal shift, and industrial process switching. The assessment also finds substantial differences in final energy estimates reported across studies, particularly in transportation. The lack of consistency in, and transparency about underlying drivers, assumptions, and even outputs across studies points to the critical need for the sorts of coordinated, multi-model studies that have proven exceptionally valuable for decision makers in other major emitting countries.

54 ENVIRONMENTAL SCIENCES↗

Climate and air pollution impacts of generating biopower from forest management residues in California

California faces crisis conditions on its forested landscapes. A century of aggressive logging and fire suppression in combination with conditions exacerbated by climate change have created an ongoing ecological, economic, and public health emergency. Between commercial harvests on California’s working forestlands and the increasing number of acres the state treats each year for fire risk reduction and carbon sequestration, California forests generate millions of tons of woody residues annually—residues that are typically left or burned in the field. State policymakers have turned to biomass electricity generation as a key market for woody biomass in the hope that it can support sustainable forest management activities while also providing low-carbon renewable electricity. However, open questions surrounding the climate and air pollution performance of electricity generation from woody biomass have made it difficult to determine how best to manage the risks and opportunities posed by forest residues. The California Biomass Residue Emissions Characterization (C-BREC) model offers a spatially-explicit life cycle assessment framework to rigorously and transparently establish the climate and air pollution impacts of biopower from forest residues in California under current conditions. The C-BREC model characterizes the variable emissions from different biomass supply chains as well as the counterfactual emissions from prescribed burn, wildfire, and decay avoided by residue mobilization. We find that the life cycle ‘carbon footprint’ of biopower from woody residues generated by recent forest treatments in California ranges widely—from comparable with solar photovoltaic on the low end to comparable with natural gas on the high end. This variation stems largely from the heterogeneity in the fire and decay conditions these residues would encounter if left in the field, with utilization of residue that would otherwise have been burned in place offering the best climate and air quality performance. California’s energy and forest management policies should account for this variation to ensure desired climate benefits are achieved.

54 ENVIRONMENTAL SCIENCES↗

Ultrafast infrared plasmon switching in aligned carbon-nanotube optical resonators

Reconfigurable plasmonic materials are crucial components in active photonic devices for optical communication, signal processing, and sensing applications. Certain candidates including transparent conducting oxides, small-bandgap semiconductors (i.e. Ge, InSb), and conducting polymers can exhibit switchable free carrier concentrations triggered by optical, electrical or thermal excitations. Here, we show that aligned films of single-walled carbon nanotubes (SWCNTs) can serve as all-optically tunable plasmonic material in the mid-infrared range, thereby adding them to the library of switchable plasmonic materials. Interband optical pumping with femtosecond laser pulses results in the photoexcitation of free charge carriers, which transiently blueshifts the plasmon resonances of patterned, periodic SWCNT nano-resonators spanning the mid-infrared spectral range from 1700 to 2700 cm -1 . Furthermore. the ultrafast plasmon modulation exhibits a nearly single-picosecond decay time, attributed to interband carrier relaxation and inter-tube charge transfer. Given that aligned films of SWCNTs have high thermal stability, excellent photostability, epsilon-near-zero property, and extremely large optical anisotropy, their dynamic tunability represents a promising pathway towards active optical devices in the technologically important mid-infrared range.

single-walled carbon nanotubes↗

Observation of well-defined Kohn-anomaly in high-quality graphene devices at room temperature

Abstract Due to its ultra-thin nature, the study of graphene quantum optoelectronics, like gate-dependent graphene Raman properties, is obscured by interactions with substrates and surroundings. For instance, the use of doped silicon with a capping thermal oxide layer limited the observation to low temperatures of a well-defined Kohn-anomaly behavior, related to the breakdown of the adiabatic Born–Oppenheimer approximation. Here, we design an optoelectronic device consisting of single-layer graphene electrically contacted with thin graphite leads, seated on an atomically flat hexagonal boron nitride substrate and gated with an ultra-thin gold layer. We show that this device is optically transparent, has no background optical peaks and photoluminescence from the device components, and no generation of laser-induced electrostatic doping (photodoping). This allows for room-temperature gate-dependent Raman spectroscopy effects that have only been observed at cryogenic temperatures so far, above all the Kohn-anomaly phonon energy normalization. The new device architecture, by decoupling graphene optoelectronic properties from the substrate effects, allows for observing quantum phenomena at room temperature.

Materials Science↗

An In Situ transmission electron microscopy study on the synergistic effects of Au-ion irradiation and high temperature on nuclear graphite microstructure

Abstract The combined effects of high-temperature and heavy-ion irradiation on Mrozowski cracks (MC) and nuclear graphite crystallographic dimensions have been studied using in situ heating and in situ ion-irradiation in the transmission electron microscope (TEM). Electron transparent lamella of nuclear graphite, IG-110, was irradiated using a 2.8 MeV Au beam at an ion flux of 3.991 ×10 10 ion cm −2 s −1 for 70 min at 800 °C. Upon high-temperature irradiation, Mrozowski crack closure was studied quantitatively. The analysis showed linear, positive expansion of nuclear graphite which is significantly different from the dimensional changes previously reported for low-dose neutron irradiation of nuclear graphite in which the material undergoes negative to positive expansion via a turnaround radiation dose. The trend of the thermal expansion coefficient (CTE) of pristine IG-110 in this study is consistent with previous reports in the 100 °C–800 °C temperature region in which the dimensional change ranges from negative to positive values.

36 MATERIALS SCIENCE↗

Gallium-doped zinc oxide: nonlinear reflection and transmission measurements and modeling in the ENZ region

Abstract Strong nonlinear materials have been sought after for decades for applications in telecommunications, sensing, and quantum optics. Gallium-doped zinc oxide is a II–VI transparent conducting oxide that shows promising nonlinearities similar to indium tin oxide and aluminum-doped zinc oxide for the telecommunications band. Here we explore its nonlinearities in the epsilon near zero (ENZ) region and show n 2,eff values on the order of 4.5 × 10 −3 cm 2 GW −1 for IR pumping on 200–300 nm thin films. Measuring nonlinear changes in transmission and reflection with a white light source probe in the near-IR while exciting in the near-IR provides data in both time and wavelength. Three films varying in thickness, optical loss, and ENZ crossover wavelength are numerically modeled and compared to experimental data showing agreement for both dispersion and temporal relaxation. In addition, we discuss optimal excitation and probing wavelengths occur around ENZ for thick films but are red-shifted for thin films where our model provides an additional degree of freedom to explore. Obtaining accurate nonlinear measurements is a difficult and time-consuming task where our method in this paper provides experimental and modeled data to the community for an ENZ material of interest.

Ball, Adam (ORCID:0000000318167813)↗

Passive radiative thermal management using phase-change metasurfaces

Abstract Realizing innovative composite materials with passive thermal management capabilities and minimal ecological footprints is a challenging but much sought-after goal that would have a transformative effect on renewable energy sciences. We demonstrate an environmentally friendly metasurface utilizing vanadium dioxide (VO 2 ) that offers responsiveness to ambient temperature and potentially long-term stability. The metasurface enables passive thermal management by self-adjusting its absorptivity and emissivity response over a broad bandwidth ranging from visible to mid-infrared (IR) wavelengths. Above the VO 2 phase transition the metasurface exhibits increased mid-IR emissivity and reduced visible/near-IR absorptivity, creating an efficient radiative emission channel in the first atmospheric transparency window with reduced absorption of solar radiation. In contrast, below VO 2 ’s transition temperature, the metasurface increasingly absorbs sun light while minimizing mid-IR radiative heat losses. Moreover, a functional silicon layer eliminates the need for an additional capping layer commonly employed to protect VO 2 from environmental degradation. The additional protective layer often impedes the use and performance of VO 2 based devices in terrestrial as well as spacecraft applications. Therefore, the proposed durable and eco-friendly metasurface will be an excellent candidate for essential passive thermal regulation systems across residential and terrestrial applications.

42 ENGINEERING↗

Colossal grain growth in Cd(Se,Te) thin films and their subsequent use in CdTe epitaxy by close-spaced sublimation

Many technologies deposit thin films on inexpensive substrates, resulting in small grains due to classic nucleation and grain growth theory. For example, state-of-the-art solar cells are made by depositing CdSeTe and CdTe layers on inexpensive glass coated with nanocrystalline transparent conducting oxides (TCOs), like SnO 2 . Characteristically, the grain size of these films is on the order of the film thickness, i.e. a few microns. CdTe small-grain films have poor electro-optical properties and require CdCl 2 passivation which fails to fully passivate grain boundaries, causes carrier compensation, and prevents implementing other II–VI alloys and materials to improve performance. Here, we present a method to increase grain size to 1 mm in CdSe x Te 1-x thin films deposited on glass/TCO substrates without CdCl 2 treatment. The colossal grain growth is driven by mechanisms distinct from classic nucleation, grain growth, and Ostwald ripening and only occurs at low selenium content (x ~ 0.1). We also demonstrate how these films can serve as templates for subsequent large-grain epitaxy of other compositions like CdTe, again without exposure to CdCl 2 . The results open new paths for thin film solar cell technology, and thin film devices in general.

36 MATERIALS SCIENCE↗

Mg x Zn 1−x O contact to CuGa 3 Se 5 absorber for photovoltaic and photoelectrochemical devices

Abstract CuGa 3 Se 5 is a promising candidate material with wide band gap for top cells in tandem photovoltaic and photoelectrochemical (PEC) devices. However, traditional CdS contact layers used with other chalcopyrite absorbers are not suitable for CuGa 3 Se 5 due to the higher position of its conduction band (CB) minimum. Mg x Zn 1− x O (MZO) is a transparent oxide with adjustable band gap and CB position as a function of magnesium composition, but its direct application is hindered by CuGa 3 Se 5 surface oxidation. Here, MZO is investigated as a contact (n-type ‘buffer’ or ‘window’) material to CuGa 3 Se 5 absorbers pretreated in Cd 2+ solution, and an onset potential close to 1 V vs reversible hydrogen electrode in 10 mM hexaammineruthenium (III) chloride electrolyte is demonstrated. The Cd 2+ surface treatment changes the chemical composition and electronic structure of the CuGa 3 Se 5 surface, as demonstrated by photoelectron spectroscopy measurements. The performance of CuGa 3 Se 5 absorber with Cd 2+ treated surface in the solid-state test structure depends on the Zn/Mg ratio in the MZO layer. The measured open circuit voltage of 925 mV is promising for tandem PEC water splitting with CuGa 3 Se 5 /MZO top cells.

36 MATERIALS SCIENCE↗

A comparative analysis of US state-level policies and programs to advance energy justice

Abstract The US energy system is undergoing massive changes that have environmental, technological, and societal implications. Decisions and actions taken now will dramatically alter the trajectory of our future energy system. Though new technologies can lessen the dangers of anthropogenic climate change, an effective and sustainable transition requires addressing social justice issues as a priority. To this end, many states have implemented policies and programs that address energy justice. A formal survey of state-level energy justice policies and programs is needed to better understand the methods used to assist communities targeted and the impacts of these efforts. Such an analysis should include an analysis of the metrics used to judge the effectiveness of the enacted policies and programs. In this paper, we analyze the energy justice policies and programs of seven different US states. From this analysis, we identify three important aspects of state energy policies. First, most policies and programs do not articulate their goals, nor cite metrics to judge their successes. This lack of transparency and accountability is a major roadblock to truly just solutions. Second, states focus on a very narrow range of solutions for energy justice issues. The most prevalent being utility bill assistance, which does not address the systemic and enduring challenges faced by many low-income or historically marginalized communities. Lastly, comprehensive energy policy does not acknowledge and address housing, employment, education, and healthcare inequities that exacerbate energy system inequities. The work presented in this paper sheds light on the progress of state-level energy justice policies and programs across the United States, and we argue more work needs to be done to understand best practices in energy justice policymaking.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Femtosecond laser fabrication of nanograting-based distributed fiber sensors for extreme environmental applications

Abstract The femtosecond laser has emerged as a powerful tool for micro- and nanoscale device fabrication. Through nonlinear ionization processes, nanometer-sized material modifications can be inscribed in transparent materials for device fabrication. This paper describes femtosecond precision inscription of nanograting in silica fiber cores to form both distributed and point fiber sensors for sensing applications in extreme environmental conditions. Through the use of scanning electron microscope imaging and laser processing optimization, high-temperature stable, Type II femtosecond laser modifications were continuously inscribed, point by point, with only an insertion loss at 1 dB m −1 or 0.001 dB per point sensor device. High-temperature performance of fiber sensors was tested at 1000 °C, which showed a temperature fluctuation of ±5.5 °C over 5 days. The low laser-induced insertion loss in optical fibers enabled the fabrication of a 1.4 m, radiation-resilient distributed fiber sensor. The in-pile testing of the distributed fiber sensor further showed that fiber sensors can execute stable and distributed temperature measurements in extreme radiation environments. Overall, this paper demonstrates that femtosecond-laser-fabricated fiber sensors are suitable measurement devices for applications in extreme environments.

Wang, Mohan (ORCID:0000000166784993)↗

Explainable physics-based constraints on reinforcement learning for accelerator optimization

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at Jefferson Lab. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment. In addition, we find that the introduction of a physics-based surrogate enables our RL algorithms to reliably converge for difficult high-dimensional accelerator optimization environments.

explainability↗

Decision support for United States—Canada energy integration is impaired by fragmentary environmental and electricity system modeling capacity

The renewable energy transition is leading to increased electricity trade between the United States and Canada, with Canadian hydropower providing firm lower-carbon power and buffering variability of wind and solar generation in the U.S. However, long-term power purchase agreements and transborder transmission projects are controversial, with two of four proposed transmission lines between Quebec, Canada and the northeast U.S. cancelled since 2018. Here, we argue that controversies are exacerbated by a lack of open-source data and tools to understand tradeoffs of new hydropower generation and transmission infrastructure in comparison to alternatives. This gap includes impacts that incremental transmission and generation projects have on the economics of the entire system, for example, how new transmission projects affect exports to existing markets or incentivize new generation. We identify priority areas for data synthesis and model development, such as integrating linked hydropower and hydrologic interactions in energy system models and openly releasing (by utilities) or back-calculating (by researchers) hydropower generation and operational parameters. Publicly available environmental (e.g. streamflow, precipitation) and techno-economic (e.g. costs, reservoir size,) data can be used to parameterize freely usable and extensible models. Existing models have been calibrated with operational data from Canadian utilities that are not publicly available, limiting the range of scientific and commercial questions these tools have been used to answer and the range of parties that have been involved. Studies conducted using highly resolved, national-scale public data exist in other countries, notably, the United States, and demonstrate how greater transparency and extensibility can drive industry action. Improved data availability in Canada could facilitate approaches that (1) increase participation in decarbonization planning by a broader range of actors; (2) allow independent characterizations of environmental, health, and economic outcomes of interest to the public; and (3) identify decarbonization pathways consistent with community values.

13 HYDRO ENERGY↗

A mixed, unified forward/inverse framework for earthquake problems: fault implementation and coseismic slip estimate

SUMMARY We introduce a new finite-element (FE) based computational framework to solve forward and inverse elastic deformation problems for earthquake faulting via the adjoint method. Based on two advanced computational libraries, FEniCS and hIPPYlib for the forward and inverse problems, respectively, this framework is flexible, transparent and easily extensible. We represent a fault discontinuity through a mixed FE elasticity formulation, which approximates the stress with higher order accuracy and exposes the prescribed slip explicitly in the variational form without using conventional split node and decomposition discrete approaches. This also allows the first order optimality condition, that is the vanishing of the gradient, to be expressed in continuous form, which leads to consistent discretizations of all field variables, including the slip. We show comparisons with the standard, pure displacement formulation and a model containing an in-plane mode II crack, whose slip is prescribed via the split node technique. We demonstrate the potential of this new computational framework by performing a linear coseismic slip inversion through adjoint-based optimization methods, without requiring computation of elastic Green’s functions. Specifically, we consider a penalized least squares formulation, which in a Bayesian setting—under the assumption of Gaussian noise and prior—reflects the negative log of the posterior distribution. The comparison of the inversion results with a standard, linear inverse theory approach based on Okada’s solutions shows analogous results. Preliminary uncertainties are estimated via eigenvalue analysis of the Hessian of the penalized least squares objective function. Our implementation is fully open-source and Jupyter notebooks to reproduce our results are provided. The extension to a fully Bayesian framework for detailed uncertainty quantification and non-linear inversions, including for heterogeneous media earthquake problems, will be analysed in a forthcoming paper.

58 GEOSCIENCES↗