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693 records · Page 39

Competing Effects of Network Architecture and Composition on Polydomain Liquid Crystal Elastomers

Main-chain liquid crystal elastomers (LCEs) are synthesized to investigate the interplay of the composition and network structure on LCE nematic-to-isotropic (N–I) transitions. We focus on networks synthesized from liquid crystalline oligomers reacted with tri- or tetrafunctional nonmesogenic cross-linker molecules. We find that coupling between mesogens and the polymer backbone increases with the degree of cross-linking. However, this enhanced coupling competes with mesogenic dilution arising from the cross-linker molecules to determine the N–I transition temperature (T NI ). When cross-linker molecules are dilute, the degree of cross-linking directly correlates to the change in T NI from the oligomer to LCE (ΔT NI ) through mesogen–backbone coupling. In this regime, ΔT NI ranges from 2.9 to 12.2 °C and 2.9–13.9 °C for tri- and tetrafunctional cross-linkers, respectively. At high cross-linker concentrations, deviations from this linear relationship appear. Further, the fractional mesogen content within an oligomer chain induces molecular weight-dependent mesogenic dilution effects arising from the flexible spacer molecules. Analysis of the N–I transition peak reveals a maximum latent heat per gram of mesogen (ΔH NI,mes ) for this system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Layer Deposited Aluminum‐Based Hybrid Resist for High‐Resolution Nanolithography and Direct Ultra‐High Aspect Ratio Pattern Transfer

Inorganic-containing hybrid photoresists are critical for next-generation extreme ultraviolet (EUV) lithography and angstrom-era semiconductor miniaturization. However, associated conventional solution processing struggles to achieve ultrathin, uniform films with high conformality and compositional control, limiting overall patterning performance. Here, this study reports the systematic lithographic patterning characterization of an Al-based hybrid resist synthesized via vapor-phase molecular layer deposition (MLD), using the trimethylaluminum (TMA) metal precursor and the hydroquinone (HQ) aromatic organic linker. The resist supports both sub-20 nm high-resolution nanolithography and virtually infinite silicon plasma etch selectivity. Lithographic performance studied using electron beam lithography (EBL) as a proxy for EUV shows that, under an optimized process adopting post-exposure bake, the resist achieves the best resolution of 15.4 nm linewidth under stringent 1:1 line-space high-density patterning—limited only by the minimum beam size of the EBL system. The resist also shows wide dose latitude and balanced performance in resolution, roughness, and sensitivity. The infinite silicon etch selectivity, stemming from spontaneous aluminum oxyfluoride passivation layer formation, enables fabrication of micrometer-tall, 40 nm-wide silicon nanofin structures using only a ≈30 nm-thick resist layer, without no hard mask. These results highlight the potential of MLD-based hybrid resists for developing next-generation resist materials for micro/nanoelectronics manufacturing.

36 MATERIALS SCIENCE↗

Effective radiative forcing of anthropogenic aerosols in E3SMv1: historical changes, causality, decomposition, and parameterization sensitivities

The effective radiative forcing of anthropogenic aerosols (ERF aer ) is an important measure of the anthropogenic aerosol effects simulated by a global climate model. Here we analyze ERF aer simulated by the E3SMv1 atmosphere model using both century-long free-running atmosphere-land simulations and short nudged simulations. We relate the simulated ERF aer to characteristics of the aerosol composition and optical properties, and evaluate the relationships between key aerosol and cloud properties. In terms of historical changes from the year 1870 to 2014, our results show that the global mean anthropogenic aerosol burden and optical depth increase during the simulation period as expected, but the regional averages show large differences in the temporal evolution. The largest regional differences are found in the emission-induced evolution of the burden and optical depth of the sulfate aerosol: a strong decreasing trend is seen in the Northern Hemisphere high-latitude region after around 1970, while a continued increase is simulated in the tropics. Consequently, although the global mean anthropogenic aerosol burden and optical depth increase from 1870 to 2014, the ERF aer magnitude does not increase after around year 1970. The relationships between key aerosol and cloud properties (relative changes between preindustrial and present-day conditions) also show evident changes after 1970, diverging from the linear relationships exhibited for the period from 1870 to 2014. The ERF aer in E3SMv1 is relatively large compared to the recently published multi-model estimates; the primary reason is the large indirect aerosol effect (i.e., through aerosol-cloud interactions). Compared to other models, E3SMv1 features a stronger sensitivity of the cloud droplet effective radius to changes in the cloud droplet number concentration. Large sensitivity is also seen in the liquid cloud optical depth, which is determined by changes in both the effective radius and liquid water path. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 are found to have a strong correlation, as the evolution of anthropogenic sulfate aerosols affects both the liquid cloud formation and the homogeneous ice nucleation in cirrus clouds. The ERF aer estimates in E3SMv1 for the shortwave and longwave components are sensitive to the parameterization changes in both liquid and ice cloud processes. When the parameterization of ice cloud processes is modified, the top-of-atmosphere forcing changes in the shortwave and longwave components largely offset each other, so the net effect is negligible. This suggests that, to reduce the magnitude of the net ERF aer , it would be more effective to reduce the anthropogenic aerosol effect through liquid or mixed-phase clouds.

54 ENVIRONMENTAL SCIENCES↗

Scaling of the strange-metal scattering in unconventional superconductors

Marked evolution of properties with minute changes in the doping level is a hallmark of the complex chemistry that governs copper oxide superconductivity as manifested in the celebrated superconducting domes and quantum criticality taking place at precise compositions. The strange-metal state, in which the resistivity varies linearly with temperature, has emerged as a central feature in the normal state of copper oxide superconductors. The ubiquity of this behaviour signals an intimate link between the scattering mechanism and superconductivity. However, a clear quantitative picture of the correlation has been lacking. In this study we report the observation of precise quantitative scaling laws among the superconducting transition temperature (T c ), the linear-in-T scattering coefficient (A 1 ) and the doping level (x) in electron-doped copper oxide La 2-x Ce x CuO 4 (LCCO). High-resolution characterization of epitaxial composition-spread films, which encompass the entire overdoped range of LCCO, has enabled us to systematically map its structural and transport properties with unprecedented accuracy and with increments of Δx = 0.0015. Additionally, we have uncovered the relations T c ~ (x c - x) 0.5 ~ (A 1 $\square$ ) 0.5 , where x c is the critical doping in which superconductivity disappears and A 1 $\square$ is the coefficient of the linear resistivity per CuO 2 plane. The striking similarity of the T c versus A 1 $\square$ relation among copper oxides, iron-based and organic superconductors may be an indication of a common mechanism of the strange-metal behaviour and unconventional superconductivity in these systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Effective radiative forcing of anthropogenic aerosols in E3SM version 1: historical changes, causality, decomposition, and parameterization sensitivities

Abstract. The effective radiative forcing of anthropogenic aerosols (ERFaer) is an important measure of the anthropogenic aerosol effects simulated by a global climate model. Here we analyze ERFaer simulated by the E3SM version 1 (E3SMv1) atmospheric model using both century-long free-running atmosphere–land simulations and short nudged simulations. We relate the simulated ERFaer to characteristics of the aerosol composition and optical properties, and we evaluate the relationships between key aerosol and cloud properties. In terms of historical changes from the year 1870 to 2014, our results show that the global mean anthropogenic aerosol burden and optical depth increase during the simulation period as expected, but the regional averages show large differences in the temporal evolution. The largest regional differences are found in the emission-induced evolution of the burden and optical depth of the sulfate aerosol: a strong decreasing trend is seen in the Northern Hemisphere high-latitude region after around 1970, while a continued increase is simulated in the tropics. The relationships between key aerosol and cloud properties (relative changes between pre-industrial and present-day conditions) also show evident changes after 1970, diverging from the linear relationships exhibited for the period of 1870–1969. In addition to the regional differences in the simulated relationships, a reduced sensitivity in cloud droplet number and other cloud properties to aerosol perturbations is seen when the aerosol perturbation is large. Consequently, the global annual mean ERFaer magnitude does not increase after around 1970. The ERFaer in E3SMv1 is relatively large compared to the recently published multi-model estimates; the primary reason is the large indirect aerosol effect (i.e., through aerosol–cloud interactions). Compared to other models, E3SMv1 features large relative changes in the cloud droplet effective radius in response to aerosol perturbations. Large sensitivity is also seen in the liquid cloud optical depth, which is determined by changes in both the effective radius and liquid water path. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 are found to have a strong correlation, as the evolution of anthropogenic sulfate aerosols affects both the liquid cloud formation and the homogeneous ice nucleation in cirrus clouds (that causes a large effect on longwave ERFaer). As suggested by a previous study, the large ERFaer appears to be one of the reasons why the model cannot reproduce the observed global mean temperature evolution in the second half of the 20th century. Sensitivity simulations are performed to understand which parameterization and/or parameter changes have a large impact on the simulated ERFaer. The ERFaer estimates in E3SMv1 for the shortwave and longwave components are sensitive to the parameterization changes in both liquid and ice cloud processes. When the parameterization of ice cloud processes is modified, the top-of-model forcing changes in the shortwave and longwave components largely offset each other, so the net effect is negligible. This suggests that, to reduce the magnitude of the net ERFaer, it would be more effective to reduce the anthropogenic aerosol effect through liquid or mixed-phase clouds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Community Resilience Indicator Analysis: Commonly Used Indicators from Peer-Reviewed Research (Updated for Research Published 2003-2021)

In 2017, FEMA’s National Integration Center (NIC) Technical Assistance (TA) Branch identified a need to establish a data-driven basis for prioritizing locations for TA investment and guiding local emergency management planning. To achieve this goal, FEMA tasked Argonne National Laboratory (Argonne) with identifying commonly used indicators of community resilience across the landscape of published peer-reviewed research. FEMA and Argonne completed the first Community Resilience Indicator Analysis (CRIA) in 2018 and repeated the process in 2022. The CRIA process begins with a literature review and cataloguing of published peer-reviewed assessment methodologies on social vulnerability and community resilience. The literature review findings are then filtered by inclusion criteria established by the CRIA research team to ensure the methodologies are: (1) Quantitative, (2) Data and methodology are publicly available, (3) Calculated at the county level or lower, (4) Examine generalized hazard risk (rather than a singular hazard), and (5) Focused on pre-disaster community conditions. After this, the research team identifies the commonly used indicators across these methodologies and selects the best data source for each indicator. Finally, the research team bins the data for visual display, conducts a correlation analysis and creates a composite index, the FEMA Community Resilience Index (FEMA CRI). In 2018, the CRIA identified eight resilience and vulnerability assessment methodologies and 20 commonly used indicators (indicators used in three or more of the eight methodologies). The FEMA CRI in 2018 was created from these 20 indicators and was produced for at the county level. The 2022 CRIA updated the literature review to expand the list of methodologies examined and followed the same process, resulting in an analysis of 14 methodologies published between 2003 and 2021 and 22 indicators identified as commonly used (indicators used in five or more of the 14 methodologies). In 2022, the research team produced the FEMA CRI at the county and the census tract levels. To make the CRIA data more accessible and more actionable, each individual indicator and the FEMA CRI is binned and included in FEMA’s Resilience Analysis and Planning Tool (RAPT). RAPT enables emergency managers and community partners to quickly visualize relative differences in potential resilience by county, tribe and census tract. By reviewing the data for each of these 22 indicators individually, emergency managers can gain insights for targeted outreach strategies, planning, mitigation investments and response and recovery operations. Communities, regional governments and others can use this data to better understand potential challenges to resilience. As the social science field of examining and validating indicators of resilience evolves, FEMA will update RAPT to provide emergency managers and community partners with additional data and tools to inform planning, mitigation, response and recovery. It is important to understand that the role of the emergency manager is not to change or to “improve” the data, but to plan appropriately for the community characteristics reflected in the data. These datasets are community characteristics that researchers have identified as important considerations for resilience. For example, people with disabilities may have greater challenges to be resilient to disasters. If a community has a high population of people with disabilities, the emergency manager(s) may need to create tailored preparedness outreach programs and strategies to ensure those residents have support if evacuation is necessary. Rather than label these indicators as an absolute measure of resilience, FEMA considers “potential challenges to resilience” a better frame to understand these indicators. Everyone is vulnerable to disasters. While scholars theorize that certain characteristics may make an individual or a household more socially vulnerable, the data does not reflect measures that individuals and/or communities have taken to address potential challenges, such as emergency management planning and outreach or household preparedness measures. To aid emergency managers in understanding how to use these indicators, calling them potential challenges to resilience supports a more positive and strategic application of the data in all phases of emergency management.

99 GENERAL AND MISCELLANEOUS↗

Technical Evaluation of Accelerated Basin De-Inventory Material Addition to Sludge Batch 11 (Rev. 1)

The Accelerated Basin De-inventory (ABD) program involves discarding spent nuclear fuel that is currently stored in L-Basin to the Defense Waste Processing Facility (DWPF) for vitrification. The first ABD discards will occur during the preparation of Sludge Batch (SB) 11. Savannah River Mission Completion has requested that the Savannah River National Laboratory assess the technical gaps related to the increased gadolinium poisoning requirement and the impacts of performing the Low Temperature Aluminum Dissolution (LTAD) process in Tank 51 with H-Canyon discards present. The following summarizes the evaluation of the impacts of increasing the quantity of gadolinium (and related topics) from what was previously evaluated in the SRNL studies of gadolinium-poisoned ABD material solubility, the overall ABD flowsheet review, and increasing the fissile mass loading in glass: 1) Based on literature surveys, there is no indication that organic interactions with gadolinium will be significant at the high pH (typically >13) conditions of the Concentration, Storage, and Transfer Facilities. Any interactions of gadolinium with organics in DWPF are not expected to adversely impact DWPF or downstream facilities. Thus, there is little-to-no residual risk from organic interactions with gadolinium [Gap closed]; 2) Adding depleted uranium to ABD material, targeting 235 U enrichment of 4.90% within each transfer window, will mitigate potential impacts from an increase in soluble 235 U enrichment during sludge washing and LTAD. The plan to take advantage of previous transfers and allow 235 U enrichment of >5% during the final transfer window carries a risk that Tank 51 supernate will have a 235 U enrichment of >5%, which should be evaluated for acceptance; 3) Increasing the gadolinium mass ratio to 3.0:1 Gd: 235 U(eq SLU ) should lead to the same or higher partitioning of gadolinium into the solid phase within the DWPF Chemical Process Cell, resulting in both liquid and solid phases with expected partitioning of Gd consistent with the prior solubility study [Gap closed for SB11]; 4) There are no expected impacts on DWPF melt temperature and melter operations due to the minimal ~0.2 weight percent (wt%) increase in Gd concentration relative to previous sludge batches [Gap closed for SB11]; 5) As observed previously, Gd is expected to enter the off-gas system via physical entrainment, but at a slightly higher concentration than what was observed for SB9 melter off-gas pluggage deposits (0.07 wt%) [Gap closed for SB11] ; 6) There are no expected impacts on DWPF recycle or the Recycle Collection Tank glycolate destruction process. [Gap closed for SB11]; 7) Gd is projected to be a trace component in the SB11 glass (<0.5 wt%) and can be ignored for process control. Trace components do not significantly impact glass durability, thus the conclusions of the previous Product Consistency Test evaluation at a fissile mass loading of 2,500 g fissile/m3 glass still applies to SB11. The ~0.1 wt% increase in Gd2O3 concentration relative to the previous study will not impact the predictability of SB11 glass with the DWPF Product Composition Control System (PCCS) models for durability or the acceptability of glass according to the Waste Acceptance Product Specifications (WAPS) criterion for product consistency [Gap closed for SB11]; 8) No additional Toxicity Characteristic Leaching Procedure testing is necessary for SB11 and the hazardous waste specification of the SB11 DWPF waste form is unchanged after the addition of the ABD stream [Gap closed for SB11]. The following summarizes the evaluation of the impacts of adding two-thirds of the ABD material to Tank 51 prior to LTAD: 1) The addition of two-thirds of the ABD increases overall aluminum mass from 1.39×10 4 kg to 1.64×10 4 kg (15.5% ABD Al). The form of the insoluble portion of the Al resulting from ABD addition should be the more readily dissolved Al(OH) 3 and amorphous forms. The portion of the ABD aluminum that is processed by LTAD is expected to be completely soluble, thus requiring that less of the boehmite in the sludge be dissolved to reach the same Al target in the SB. [Gap closed for SB11]; The expected LTAD impact on other components, as related primarily to the components in ABD, are discussed. Gd is expected to remain insoluble during LTAD and not impact the solubility of other components. [Gap closed for SB11]; The addition of two-thirds of the ABD increases overall projected SB11 uranium mass from 4,740 kg to 13,100 kg (63% ABD U) and the projected plutonium mass from 86.0 kg to 89.5 kg (3.9% ABD Pu). The addition of all of the ABD increases overall projected SB11 uranium mass from 4,740 kg to 16,100 kg (70% ABD U) and the projected plutonium mass from 86.0 kg to 90.4 kg (5.3% ABD Pu). The 235 U enrichment will be ≤5%. The fissile uranium will be adequately poisoned by Gd and the fissile Pu will be adequately poisoned by Fe from the sludge. [Gap closed for SB11]; There is a low risk that ABD addition will impact the rheology or pumpability of the slurry. There is a low but higher risk of ABD addition prior to LTAD impacting the settling rate; Based on the evaluation of adding two-thirds of the ABD material and all of the ABD material prior to the LTAD process, there is no volume or mass limit that would need to be imposed on ABD additions prior to LTAD. [Gap closed for SB11]. Revision 1 of this report addresses a variation on the ABD additions and LTAD strategy where sodium hydroxide additions for LTAD may be performed intermittently or concurrently with an ABD addition window. The proposed change does not alter the conclusions of this evaluation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)

We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.

02 PETROLEUM↗

Diagnostics: Chapter 8 of the special issue: on the path to tokamak burning plasma operation

This chapter presents the activity conducted by the ITPA topical group (TG) on Diagnostics over about the last 15 years. Following a general introduction of the ITER Diagnostics led by their measurement roles, the document is organized in several subchapters detailing the design support, research and development activity conducted by each of the specialist working groups (WGs) of the TG. Please note that the magnetic diagnostics were supported at the TG without a specific WG. Their status is included in the general introduction. In the following some highlights of the subchapter’s contents are provided. Recent advances in ITER first wall (FW) diagnostics for the measurements of plasma-metallic wall interaction in support of the ITER research plan are reported. An InfraRed imaging Video Bolometer for ITER has been developed and tested on several tokamaks to measure the radiated power loss. A laser-induced breakdown spectroscopy (LIBS) technique which utilizes a pulsed laser beam to ablate locally by forming a crater, will measure local tritium inventory in the FW material. Real-time Residual Gas Analyzers will measure the neutral gas composition in a divertor port and an equatorial port during plasma operation. Due to the full metallic FW environment, the plasma-wall interaction in ITER will face several challenges such as the compromised radiated power and divertor heat flux measurements by reflection. Ray tracing and analysis codes have been developed to eliminate and correct the effects of reflection in the measurements. The characteristics of the reflecting surfaces depending on the roughness and angle of the incidence have been measured by dedicated experiments, and the results were applied to the reflection elimination. For the measurement of the metallic impurity radiation induced by eroded metallic atoms, a vacuum ultraviolet spectrometer has been developed and tested. An extensive thermonuclear diagnostic suite will be required to support the operation of ITER and the planned experimental program for future burning plasma experiments. Due to the harsh environmental conditions, the implementation of diagnostic systems in ITER is a major challenge. These conditions include high levels of neutron and gamma fluxes, neutron heating, particle bombardment. Therefore, the selection and design of diagnostic systems must take into account a number of phenomena previously unseen in diagnostic design. For this reason, the measurement of neutrons and confined or lost fast ions, with particular emphasis on alpha particles, is critical to ITER. The diagnostics associated with these measurements will be important for future plasma-burning experiments at ITER. The high neutron emission and very large plasma size in ITER make neutron diagnostics the main diagnostic method used to measure plasma parameters such as fusion power, fusion power density, ion temperature, energy of fast ions and their spatial distributions in the plasma core. Active spectroscopy techniques are methods where a neutral particle beam is injected into the plasma and information on plasma parameters is extracted from the measurement of line emission resulting from the beam-plasma interaction, either by plasma ions or by beam atoms. Spatial localization is achieved by crossing the beamline and multiple observation lines. The ITER plasma will be a high temperature, moderately dense, fully ionized collisional plasma. The plasma facing surfaces are principally metallic being fashioned from beryllium or tungsten but many other elements, arising from either structural or from operational needs, may enter this plasma. The energy range of the emitted photons range from meV (infra-red) to multi keV (x-rays) and originate from all areas of the plasma volume. The primary role of passive emission diagnostics is to identify what is in the plasma from spectral signatures. Extracting quantitative information from these measurements such as impurity content, ion temperature, rotation, degree of detachment and radiated power depends on calibrated instruments, a physics model of the atomic and molecular processes and plasma transport and an analysis workflow that takes into account environmental effects such as reflections. The particular needs for ITER have prompted a multi-machine, many-year effort to address all these aspects and this chapter reviews the work on diagnostic design, experiments and new analysis techniques. An overview of the laser diagnostics to be implemented on ITER is also provided in this paper. This includes descriptions of the Thomson scattering in the core, edge and divertor regions, polarimetry and interferometry diagnostics used for measuring plasma density and also measurements of helium density in the divertor using Laser Induced Flourescence. Techniques which can allow improvements on current measurements are also addressed in particular expanding poloidal polarimetry measurements to measure field fluctuations and proposed use of dispersion interferometery which has a number of advantages over existing methods. This paper identifies particular areas where further research and testing on existing tokamaks is useful even at this advanced stage to inform the design of diagnostics for ITER. Outstanding areas of concern for the implementation of laser diagnostics, in particular with a view to reliable operation are identified. An overview of the latest developments of microwave diagnostic systems and techniques is given. The primary focus is the contributions for ITER—the next step burning plasma experiment—which is supplemented by describing recent progress of techniques applicable for fusion experiments beyond ITER. The contributions are intentionally kept concise, and are being supplemented by a rich list of references for further studies. Radiation induced effects are receiving continuous and well-deserved attention of the ITER diagnostic community and they are in many cases one of the primary design drivers of the ITER diagnostic systems. The paper summarizes recent progress in this area focusing primarily on the ITER diagnostics but in some cases provides also outlook for the possible solutions for even more demanding radiation environment of fusion reactors beyond ITER. Despite advancements in the area of modeling and simulation of various radiation induced effects, experimental testing in a nuclear environment as close as possible to the target one is still seen as unavoidable for proper qualification of particular diagnostic functional elements. Recent advancement within three diagnostic areas: optical diagnostics, magnetics and bolometers is covered. Encouraging results on qualification of silica glass vacuum window assemblies are presented. In the area of magnetic sensors, progress of irradiation tests performed on ITER in-vessel LTCC inductive sensors is presented with outlook for novel technological approaches to inductive sensors utilizing thick printing and photolithography technologies being highlighted. Summary of advancements in the area of steady state magnetic field sensors based on Hall effect is given. New results of neutron irradiation test of the ITER borosilicate glass inserts for vacuum electrical feedthroughs are summarized finding negligible swelling at target level of neutron fluence. Off-line irradiation tests of fiber optic current sensors for plasma current measurement demonstrated that both for gamma doses up to 5 MGy and a total neutron fluence up to 10 15 cm −2 , radiation induced changes are still compatible with required measurement accuracy on ITER. The ITER bolometers are given as an example how considering radiation effects may influence the diagnostic design. Finally, outlook for future main R&D directions is outlined. All optical and laser-based diagnostics in ITER will be using mirrors to guide plasma radiation toward detectors, cameras and sensors. In the hostile plasma, radiation and particle environment the optical characteristics of diagnostic mirrors will degrade directly affecting the entire performance of involved diagnostic systems. An assessment of factors affecting mirror performance is provided. Among the prime adverse factors are deposition of plasma impurities, sputtering of mirror surface and steam ingress in the vicinity of mirrors. Within the International Tokamak Physics Activity with active support by ITER central team and domestic agencies, the structured research and development (R&D) program on mitigation of risks for diagnostic mirrors is underway. Within this program the mirror material development, the passive mitigation of mirror degradation by using diagnostic ducts and shutters along with an active mirror recovery program comprising the in-situ mirror cleaning and calibration is underway. Recent developments in diagnostic mirror R&D are described in this Chapter along with an example of their implementation of R&D solutions in ITER Infrared Thermography diagnostic. An assessment of still open engineering and physics questions, considerations on mirror risks during an early phase of ITER operation are given along with an overview of diagnostic mirror evolution in the late ITER operation stage toward the demonstration fusion power plant. Several crucial areas of diagnostic R&D outlined in ITER Research Plan are addressed. The basic control groups in a fusion reactor can be broken-down in five categories: (1) plasma position, magnetic configuration, and plasma current control, (2) profile control and confinement optimization, (3) MHD control and suppression, (4) edge dissipation control, radiation and plasma exhaust control and (5) break-down optimization. These categories are coupled via the physics (a control action in one domain will affect the other domains) and via shared actuators (e.g. ECRH for impurity accumulation avoidance, current density distribution control and MHD suppression). Consequently, a supervisory control system should determine the priority of the various control tasks, their couplings, and the interfaces with the safety and interlock system. For the systematic development of the various controllers taking the complexity of the plasma and the control system into account, a model-based approach is required. A short historical overview is given of the developments in systems and control theory and control engineering with special emphasis on those developments that are most relevant for Nuclear Fusion research and operation. An overview is given of the state of the field of fusion plasma control for the control categories. It will be shown how synthetic diagnostics are being developed in ITER and how they are used in diagnostic design and design validation and how they can be in model-based controller synthesis using relatively simple models. In modern control methods, multiple diagnostics are used to constrain relatively simple models. The constrained models provide an estimate for the state. This opens the route to state controllers, such as model predictive control. A major challenge in nuclear fusion research is the coherent combination of data from heterogeneous diagnostics and modeling codes for machine control and safety as well as physics studies. Measured data from different diagnostics often provide information about the same subset of physical parameters. Additionally, information provided by some diagnostics might be needed for the analysis of other diagnostics. A joint analysis of complementary and redundant data allows, e.g. to improve the reliability of parameter estimation, to increase the spatial and temporal resolution of profiles, to obtain synergistic effects, to consider diagnostics interdependencies and to find and resolve data inconsistencies. Physics-based modeling and parameter relationships provide additional information improving the treatment of ill-posed inversion problems. A coherent combination of all kind of available information within a probabilistic framework allows for improved data analysis results. The concept of integrated data analysis (IDA) in the framework of Bayesian probability theory is outlined and contrasted with conventional data analysis. Components of the probabilistic approach are summarized and specific ingredients beneficial for data analysis at fusion devices are discussed.

ITER↗