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At least 127 records · Page 7

A universal implementation of radiative effects in neutrino event generators

Due to the similarities between electron-nucleus (eA) and neutrino-nucleus scattering (νA), eA data can contribute key information to improve cross-section modeling in eA and hence in νA event generators. However, to compare data and generated events, either the data must be radiatively corrected or radiative effects need to be included in the event generators. We implemented a universal radiative corrections program that can be used with all reaction mechanisms and any eA event generator. Our program includes real photon radiation by the incident and scattered electrons, and virtual photon exchange and photon vacuum polarization diagrams. It uses the “extended peaking” approximation for electron radiation and neglects charged hadron radiation. This method, validated with GENIE, can also be extended to simulate νA radiative effects. This work facilitates data-event-generator comparisons used to improve νA event generators for the next-generation of neutrino experiments. Program Title: emMCRadCorr CPC Library link to program files:https://doi.org/10.17632/hmsxg82vnf.1 Developer's repository link:https://github.com/e4nu/emMCRadCorr Licensing provisions: AGPLv3 Programming language:C++ Nature of problem: Radiative effects can significantly modify the event kinematics and the resulting cross-sections. Such effects must be accounted for when comparing event generators to eA data. Existing radiative correction codes are tailored to specific processes and topologies, and are limited to a restricted phase space defined by the spectrometer acceptance. Therefore, a more general approach is required to apply radiative corrections to semi-inclusive and exclusive eA measurements. Solution method: Our program incorporates real photon radiation from both the incident and scattered electrons, as well as virtual photon exchange and photon vacuum polarization effects. It employs the “extended peaking” approximation for electron radiation while neglecting contributions from charged hadron radiation. The code is fully decoupled from event generator codes and can be used for all event generators in the market.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Joint Factorization of QCD and QED Radiation in Lepton-Hadron Scattering

The factorization theorem plays an important role in the analysis of high energy quantum chromodynamic (QCD) processes, separating the nonperturbative hadronic interaction into the universal parton distribution functions (PDFs) and fragmentation functions (FFs) and the process-dependent interactions into short distance perturbative calculations, with any interference power suppressed. With a virtual photon exchange, lepton-hadron deep inelastic scattering (DIS) provides an electromagnetic hard probe for the partonic structure of colliding hadrons and has played an important role in the development of QCD factorization. However, the collision induced QED radiation can change the momentum of the exchanged but unobserved virtual photon, making the photon-hadron frame, where the factorization formalism for DIS and semi-inclusive DIS (SIDIS) was derived, ill defined. A new analogous factorization approach has been introduced to separate the leading power process-independent QED radiative contributions to the single photon exchange by introducing lepton distribution functions (LDFs) and lepton fragmentation functions (LFFs), while process-dependent effects are perturbatively calculated with large logarithms removed [J. High Energ. Phys. 2021, 157 (2021)]. These LDFs and LFFs are considered global, as they appear in many different interactions, such as e+e-, DIS and SIDIS, so data from experiments can be used to fit and describe these functions across a wide range of lepton scattering. In this work, I will apply this new hybrid factorization approach to lepton-hadron DIS and SIDIS. For DIS, I derive the NLO short distance perturbative contribution to the cross section and demonstrate the effects the QED radiation has on the cross section using this approach using the CTEQ parameterization for the QCD functions. As part of the SIDIS analysis, I study the cross-section in two different kinematic regions: (1) the scattered lepton and observed hadron are not near back-to-back, and (2) they are close to back-to-back, where collinear QCD factorization works for (1) and TMD QCD factorization for (2) while collinear QED factorization works for both. As part of this work, I show the effects on the SIDIS cross section using fixed order calculations for the unpolarized structure function by first showing the effect of the radiative corrections on the main kinematic variables, especially how the internal transverse momentum is significantly correlated to the external angular dependence, and then the unpolarized structure function (or cross section) with matching between the descriptions for low and high transverse momentum. This work will impact the calculations for predictions for data from COMPASS and various Jefferson Lab experiments.

Cammarota, Justin [Univ. of Kentucky, Lexington, K

Strong Sensitivity of Simulated Biomass Burning Aerosol Transport and Radiative Effects Over the South Atlantic to Carbonaceous Aerosol Aging and Particle Density

Biomass burning aerosol (BBA) impacts climate through aerosol‐cloud‐radiation interactions, but models disagree on the sign and magnitude of BBA radiative effects. We quantify the sensitivity of BBA radiative effects and transport to three BBA‐relevant processes and properties: parameterized oxidative aging of organic aerosol (OA), a combined change to black carbon (BC) density and the method for calculating aerosol refractive index, and reduction in OA density. We evaluate Unified Model simulations against two aircraft campaigns from summer 2017 over the Southeast Atlantic. The model generally performs well, such that discrepancies between the observational data sets may sometimes limit the precision of the evaluation. Our newly developed aging parameterization reproduces observed OA:BC mass ratios well and allows modeled OA:BC to decrease with smoke age, but increases bias in aerosol extinction and changes the BBA radiative effect little (+0.12 W m -2 ). We calculate aerosol refractive index using either a volume‐weighted component average or the Maxwell‐Garnett (MG) mixing assumption, which represents BC as small inclusions in a host material. Compared to MG mixing, the volume‐weighted average refractive index and reduced BC density increase aerosol absorption, substantially increasing the total BBA radiative effect (+2.66 W m -2 ) and amount of BBA transported across the ocean through BC self‐lofting. Reducing OA density to better match literature values changes the total BBA radiative effect by −1.96 W m -2 . Changes to direct radiative effects exceed changes to cloud radiative effects. Our findings emphasize the sensitivity of aerosol radiative effects and transport to these processes and properties, which we suggest could be improved in climate models.

Southeast Atlantic

Electron Beam Irradiation for Water Treatment of Per- and Polyfluoroalkyl Substances (PFAS)

Per- and polyfluoroalkyl substances (PFAS) are widely used but are now considered a water contamination risk. Fermi National Accelerator Laboratory’s IARC group has demonstrated that passing water through electron beam radiation can destroy PFAS. This project aims to develop a process to scale the system for bulk water treatment. The key is efficient radiation usage, ensuring that all water receives only the minimum dose. Software was developed for this purpose, consisting of a computational fluid dynamics model (CFD) in COMSOL, which calculates particle trajectories through the radiation area. A MATLAB script integrates the radiation dose of these particles, and statistical analysis is performed to evaluate the radiation utilization efficiency. These models are validated with a flow test where colored dye is injected and optically tracked. Radiation dose is measured by testing under an e-beam to measure the degradation of a PFAS analog.

Mueller, Scott [Northern Illinois U.]

Characterization of Organosulfates and Organonitrates in Vertically Resolved Aerosols over the Southern Great Plains Field Campaign Report

Aerosol is the largest individual source of uncertainty in assessing the Earth’s radiative balance due to poorly understood aerosol processes and aerosol-cloud interactions. Thus, to constrain aerosol’s climate impacts, it is critical to understand aerosol compositions at high elevations. Organic material accounts for about 20-80% of total aerosol mass in the atmosphere and is known to play a key role in aerosol processes and cloud formation. In prior research, characterization of aerosol molecular composition has been mostly carried out at ground level. In these ground-level measurements, total speciated organosulfates and organonitrates may contribute significantly to organic aerosol mass on the order of 10-40%, most of which are from abundant biogenic volatile organic compounds such as isoprene and monoterpenes. Organosulfates and organonitrates have also been shown to be present in substantial amounts in cloud water, suggesting that they can be transported and/or directly formed at high elevations. On the other hand, the less common and more expensive aircraft studies have performed high-altitude measurements, but were often limited in the number of different altitudes sampled and in sample collection under consistent conditions. Therefore, the vertical distributions of key aerosol components such as organosulfates and organonitrates are not well understood and have not been extensively studied. Nevertheless, it is important to understand how organosulfates and organonitrates in aerosols are distributed, transformed, participate in aqueous-phase processes, and interact with high-altitude clouds.

54 ENVIRONMENTAL SCIENCES

Strategies to mitigate urban heat: Effects on overheating and cloud formation

This study evaluates the effectiveness of various urban heat island (UHI) overheating mitigation strategies and their associated impacts on urban cloud dynamics and thermal processes. This study shows cloud-resolving and urban-resolving modeling results estimating the impact of Houston-Galveston heat mitigation scenarios and other resilient strategies contemplated in the Climate Adaptation Plan and Resilient Houston reports. The simulated scenarios include high intensity green rooftops, rooftop photovoltaic solar panels, enhanced urban irrigation, white/cool roofs and roads, and street trees. We contrast the adaptation scenarios against a present baseline case, a no city scenario and a larger and denser city as projected by the Houston-Galveston Area Council for 2045. During the daytime, cooling strategies such as cool roofs, cool roads, and green roofs exhibit superior performance in mitigating urban overheating. At night, enhanced urban irrigation emerges as the most effective cooling intervention. Cooling strategies significantly reduce sensible heat flux partitioning during the day, a process that reduces the uplift of air, suppressing the formation of urban shallow cumulus clouds. The extent of urban cloud mixing ratio is reduced in proportion to the decrease in sensible heating. Under the BEP-Tree scenario, which includes wind effects and evapotranspiration driven by a stomatal conductance model, urban trees demonstrated negligible environmental cooling effects and minimal urban cloud modifications. In contrast, the scenarios with more urban cooling and higher latent heat fluxes led to suppressed urban clouds. The net cooling effect achieved by the heat mitigation strategies is influenced by a combination of indirect processes, including the reduction of downwelling longwave radiation flux, due to reduced cloud presence, while some warming is attributed to a modest increase in shortwave radiation that offsets the cooling benefit. Additionally, reduced heat dissipation, weakened thermal gradients, and diminished vertical mixing over urban areas further moderate the cooling potential. These findings highlight the pivotal role of clouds and moist atmospheric processes in shaping the UHI effect and offer insights for designing more effective urban cooling strategies.

albedo changes

Predicting Radiation-Induced Plutonium Redox Chemistry using Multiscale Modeling Methods

Over the the last 70 years plutonium (Pu) has been integral in the development of several technologies that have changed the world, yet our fundamental understanding of its chemistry is still far from complete. This is a testament to this element?s unique and complex properties, such as its ability to coexist as multiple oxidation states in aqueous solution. Careful manipulation of plutonium oxidation states is essential in the study and utilization of its rich chemistry. To achieve this level of control, a comprehensive mechanistic understanding of radiation-induced plutonium redox chemistry is critical due to the unavoidable exposure of plutonium to ionizing radiation fields, both inherent and from in-process applications. For this reason, we have developed an experimentally evaluated multi-scale computer model for the prediction of gamma radiation-induced Pu(IV) redox chemistry in concentrated nitric acid solutions (1.0, 3.0, and 6.0 M).

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA

Non-Equilibrium Actinide Radiation Chemistry and the Nuclear Fuel Cycle

Actinides are inherently unstable elements that frequently coexist with other radioisotopes, generating intense ionizing radiation fields that drive the formation of non equilibrium oxidation states. These transient species exert a profound mechanistic influence on the radiation response of actinide containing systems due to their unique redox chemistry. Despite their importance, they remain poorly understood, yet such insight is essential for advancing actinide science and accurately predicting radiation driven behavior. Actinide separations—critical for nuclear energy technologies, strategic deterrence, space exploration, and nuclear medicine—depend on precise control of actinide oxidation states to recover targeted elements from complex matrices such as used nuclear fuel. However, during these processes, actinides, their coordination complexes, and the separation media are all exposed to intense, multicomponent (alpha, beta, gamma, etc.) radiation fields that can alter process efficiency, selectivity, and chemical stability. Understanding, controlling, and mitigating radiation induced reactions is therefore key to innovating and optimizing next generation separation technologies. This seminar will provide an overview of the nuclear fuel cycle and non equilibrium actinide radiation chemistry in the context of recovering actinides from used nuclear fuel, with a particular emphasis on direct dissolution–based reprocessing strategies. We will explore time resolved electron pulse radiolysis and alpha and gamma dose accumulation studies, integrated with multiscale computational modeling, to elucidate the molecular level roles of radiation driven, non equilibrium actinide species in process performance and in the radiolytic stability of organic ligands used for actinide recovery. These insights offer new pathways for designing advanced separation methods and next generation solvent systems, with broad implications for the future of the nuclear fuel cycle.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C

Leveraging transfer learning and leaf spectroscopy for leaf trait prediction with broad spatial, species, and temporal applicability

Accurate and reliable prediction of leaf traits is crucial for understanding plant adaptations to environmental variation, monitoring terrestrial ecosystems, and enhancing comprehension of functional diversity and ecosystem functioning. Currently, various approaches (e.g., statistical, physical models) have been developed to estimate leaf traits through hyperspectral remote sensing and leaf spectroscopy. However, the absence of high-performing, transferable, and stable models across various domains of space, plant functional types (PFTs) and seasons hinder our ability to quantify and comprehend spatiotemporal variations in leaf traits. This study proposes robust and highly transferable models for better predicting leaf traits with hyperspectral reflectance. Initially, three datasets were assembled, pairing common leaf traits — chlorophyll (Chla+b), carotenoids (Ccar), leaf mass per area (LAM), equivalent water thickness (EWT) — with leaf spectra measurements collected across diverse geographic locations in the U.S. and Europe, PFTs, and seasons. Measurements were acquired using spectroradiometers (e.g., ASD FieldSpec 3/4/Pro and SVC HR-1024i) with integrating spheres, leaf clips, and contact probes. Here, we then developed transfer learning-based hybrid models that incorporated the domain knowledge of radiative transfer models (RTMs) through pretraining processes and were well-constrained by fine-tuning with field measurements. Through comparison with other state-of-the-art statistical models, including partial-least squares regression (PLSR) and Gaussian Process Regression (GPR), as well as pure physical models, we found that the proposed transfer learning models achieved better predictive performance and higher transferability. Specifically, compared to other statistical models and pure RTMs, the transfer learning model exhibited higher coefficient of determination (R 2 ) values with range of 0.01 to 0.79, lower normalized root mean square error (NRMSE) with range of 0.06 % to 33.25 % in model performance. Additionally, the models exhibited improved transferability, with higher R 2 values range from 0.04 to 0.32, lower NRMSE range from 0.08 % to 30.81 %. The findings underscore that transfer learning models through integrating domain knowledge from RTMs and limited observations, can harness the advantages of both RTMs and statistical models and serve as a promising approach for effectively predicting leaf traits.

59 BASIC BIOLOGICAL SCIENCES

Fixed-Site KAZR b1 Data Processing Report: 2025

The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility has been operating Ka-band ARM Zenith Radars (KAZRs) at each of its permanent observatories for at least the past 10 years. Data collected by the KAZRs is used to explore various cloud processes in different climatological regimes including marine stratocumulus clouds at the Eastern North Atlantic (ENA) site, arctic clouds at the North Slope of Alaska (NSA) site, and mid-latitude continental clouds at the Southern Great Plains (SGP) site.

54 ENVIRONMENTAL SCIENCES

Element Formation in Radiation-hydrodynamics Simulations of Kilonovae

Abstract Understanding the details of r -process nucleosynthesis in binary neutron star merger (BNSM) ejecta is key to interpreting kilonova observations and identifying the role of BNSMs in the origin of heavy elements. We present a self-consistent, two-dimensional, ray-by-ray radiation-hydrodynamic evolution of BNSM ejecta with an online nuclear network (NN) up to a timescale of days. For the first time, an initial numerical relativity ejecta profile composed of the dynamical component and spiral-wave and disk winds is evolved including detailed r -process reactions and nuclear heating effects. A simple model for the jet energy deposition is also included. Our simulation highlights that the common approach of relating in postprocessing the final nucleosynthesis yields to the initial thermodynamic profile of the ejecta can lead to inaccurate predictions. Moreover, we find that neglecting the details of the radiation-hydrodynamic evolution of the ejecta in nuclear calculations can introduce deviations of up to 1 order of magnitude in the final abundances of several elements, including very light and second r -process peak elements. The presence of a jet affects element production only in the innermost part of the polar ejecta, and it does not alter the global nucleosynthesis results. Overall, our analysis shows that employing an online NN improves the reliability of nucleosynthesis and kilonova light-curve predictions.

Magistrelli, Fabio (ORCID:0009000509767851)

Navigating the Noise: Bringing Clarity to ML Parameterization Design With O $\boldsymbol{\mathcal{O}}$(100) Ensembles

Abstract Machine‐learning (ML) parameterizations of subgrid processes (here of turbulence, convection, and radiation) may one day replace conventional parameterizations by emulating high‐resolution physics without the cost of explicit simulation. However, uncertainty about the relationship between offline and online performance (i.e., when integrated with a large‐scale general circulation model) hinders their development. Much of this uncertainty stems from limited sampling of the noisy, emergent effects of upstream ML design decisions on downstream online hybrid simulation. Our work rectifies the sampling issue via the construction of a semi‐automated, end‐to‐end pipeline for size ensembles of hybrid simulations, revealing important nuances in how systematic reductions in offline error manifest in changes to online error and online stability. For example, removing dropout and switching from a Mean Squared Error to a Mean Absolute Error loss both reduce offline error, but they have opposite effects on online error and online stability. Other design decisions, like incorporating memory, converting moisture input from specific humidity to relative humidity, using batch normalization, and training on multiple climates do not come with any such compromises. Finally, we show that ensemble sizes of may be necessary to reliably detect causally relevant differences online. By enabling rapid online experimentation at scale, we can empirically settle debates regarding subgrid ML parameterization design that would have otherwise remained unresolved in the noise.

Lin, Jerry [Department of Earth System Sciences Un

3D hybrid fluid-particle jet simulations and the importance of synchrotron radiative losses

Context. Relativistic jets in active galactic nuclei are known for their exceptional energy output, and imaging the synthetic synchrotron emission of numerical jet simulations is essential for a comparison with observed jet polarization emission. Aims. Through the use of 3D hybrid fluid-particle jet simulations (with the PLUTO code), we overcome some of the commonly made assumptions in relativistic magnetohydrodynamic (RMHD) simulations by using non-thermal particle attributes to account for the resulting synchrotron radiation. Polarized radiative transfer and ray-tracing (via the RADMC-3D code) highlight the differences in total intensity maps when (i) the jet is simulated purely with the RMHD approach, (ii) a jet tracer is considered in the RMHD approach, and (iii) a hybrid fluid-particle approach is used. The resulting emission maps were compared to the example of the radio galaxy Centaurus A. Methods. We applied the Lagrangian particle module implemented in the latest version of the PLUTO code. This new module contains a state-of-the-art algorithm for modeling diffusive shock acceleration and for accounting for radiative losses in RMHD jet simulations. The module implements the physical postulates missing in RMHD jet simulations by accounting for a cooled ambient medium and strengthening the central jet emission. Results. We find a distinction between the innermost structure of the jet and the back-flowing material by mimicking the radio emission of the Seyfert II radio galaxy Centaurus A when considering an edge-brightened jet with an underlying purely toroidal magnetic field. We demonstrate the necessity of synchrotron cooling as well as the improvements gained when directly accounting for non-thermal synchrotron radiation via non-thermal particles.

79 ASTRONOMY AND ASTROPHYSICS

Towards modelling AR Sco: generalized particle dynamics and strong radiation-reaction regimes

Numerical simulations of relativistic plasmas have become more feasible, popular, and crucial for various astrophysical sources with the availability of computational resources. The necessity for high-accuracy particle dynamics is especially highlighted in pulsar modelling due to the extreme associated electromagnetic fields and particle Lorentz factors. Including the radiation-reaction force in the particle dynamics adds even more complexity to the problem, but is crucial for such extreme astrophysical sources. We have also realized the need for such modelling concerning magnetic mirroring and particle injection models proposed for AR Sco, the first white dwarf pulsar. This paper demonstrates the benefits of using higher-order explicit numerical integrators with adaptive time-step methods to solve the full particle dynamics with radiation-reaction forces included. We show that for standard test scenarios, namely various combinations of uniform E- and B-fields and a static dipole B-field, the schemes we use are equivalent to and in extreme field cases outperform standard symplectic integrators in accuracy. We show that the higher-order schemes have massive computational time improvements due to the adaptive time-steps we implement, especially in non-uniform field scenarios and included radiation reaction where the particle gyro-radius rapidly changes. When balancing accuracy and computational time, we identified the adaptive Dormand–Prince eighth-order scheme to be ideal for our use cases. The schemes we use maintain accuracy and stability in describing the particle dynamics and we indicate how a charged particle enters radiation-reaction equilibrium and conforms to the analytical Aristotelian Electrodynamics expectations.

79 ASTRONOMY AND ASTROPHYSICS

Towards modelling AR Sco: calibration – reproducing high-energy pulsar emission and testing convergence to Aristotelian electrodynamics

In recent years, kinetic simulations have been crucial to further our understanding of pulsar electrodynamics. Yet, due to the large-scale separation between the gyro-period and the stellar rotation period, resolving the particle gyration has been computationally unfeasible for realistic pulsar parameters. The main aim of this work is comparing our gyro-phase-resolved model with a gyro-centric pulsar model, where our model solves the general equations of motion with included radiation reaction using a higher order numerical solver with adaptive time-steps. Specifically, we aim to (i) reproduce a pulsar’s high-energy emission maps, namely one with 10 per cent of the surface B-field strength of Vela, and the spectra produced by an independent gyro-centric pulsar emission model; and (ii) test convergence of these results to the radiation-reaction limit of Aristotelian electrodynamics. (iii) Additionally, we identify the effect that a large $E_{\parallel }$-field has on the trajectories and radiation calculations. We find that we can reproduce the curvature radiation emission maps and spectra well, using 10 per cent field strengths of the Vela pulsar and injecting our particles at a higher altitude in the magnetosphere. Using sufficiently large $E_{\parallel }$-fields, our numeric results converge to the analytic radiation-reaction limit trajectories. Additionally, we illustrate the importance of accounting for the $\mathbf {E}\times \mathbf {B}$-drift in the particle trajectories and radiation calculations, validating the Harding and collaborators’ model approach. Lastly, we found that our model deals very well with the high-radiation-reaction and high-field regimes present in pulsars.

79 ASTRONOMY AND ASTROPHYSICS

Non-Equilibrium Actinide Radiation Chemistry and the Nuclear Fuel Cycle

Invited John and Naomi Fackler Lectureship in Chemistry and English seminar at Valparaiso University, IN, USA. Actinides are inherently unstable elements that frequently coexist with other radioisotopes, generating intense ionizing radiation fields that drive the formation of non-equilibrium oxidation states. These transient species exert a profound mechanistic influence on the radiation response of actinide-containing systems due to their unique redox chemistry. Despite their importance, they remain poorly understood, yet such insight is essential for advancing actinide science and accurately predicting radiation-driven behavior. Actinide separations—critical for nuclear energy technologies, strategic deterrence, space exploration, and nuclear medicine—depend on precise control of actinide oxidation states to recover targeted elements from complex matrices such as used nuclear fuel. However, during these processes, actinides, their coordination complexes, and the separation media are all exposed to intense, multicomponent (alpha, beta, gamma, etc.) radiation fields that can alter process efficiency, selectivity, and chemical stability. Understanding, controlling, and mitigating radiation-induced reactions is therefore key to innovating and optimizing next-generation separation technologies. This seminar will provide an overview of the nuclear fuel cycle and non-equilibrium actinide radiation chemistry in the context of recovering actinides from used nuclear fuel, with a particular emphasis on direct-dissolution–based reprocessing strategies. We will explore time-resolved electron pulse radiolysis and gamma dose accumulation studies to elucidate the molecular-level roles of radiation-driven, non-equilibrium actinide species in process performance and in the radiolytic stability of organic ligands used for actinide recovery. These insights offer new pathways for designing advanced separation methods and next-generation solvent systems, with broad implications for the future of the nuclear fuel cycle.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C

Radiation Effects on Network on Chips (NoC) Laboratory Directed Research and Development (LDRD) project

This project was motivated by State-of-the-Art (SOTA) technology that incorporates Network on Chips (NOC) for efficient data communication across the various computer kernels. For example, on the AMD Versal Field Programmable Gate Arrays (FPGA), an NoC has been incorporated for fast data communication from the programmable logic and other computer kernels (processing system, adaptable intelligence engines, etc.). The radiation effects on the legacy technology of this FPGA, such as the programmable logic, are well understood, and established methods exist to measure cross-sections when new families/generations are released; however, newly incorporated technologies, such as the NoC, are not fully understood and could introduce new failure points into the mission space.

36 MATERIALS SCIENCE