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At least 523 records · Page 29

Radiation effects in Mn+1AXn phases

M n+1 AX n phases exhibit unique laminated atomic structures that result in properties typical of both ceramics and metals. Due to their unusual characteristics, these materials have been proposed for use in a wide variety of industrial applications, including in nuclear reactors—both fission and fusion systems—where they will be exposed to extreme irradiation conditions and high temperatures. Recently, numerous studies have investigated radiation effects on the M n+1 AX n phases, revealing complex behavior—phase transformations, surface modification, and mechanical property changes—induced by ion or neutron irradiation over a range of temperatures. This review summarizes recent experimental and theoretical work on the response of the M n+1 AX n phases to irradiation and discusses the intrinsic controls on the radiation tolerance of these materials. Based on the review of the present body of work, a comprehensive understanding of the mechanisms of irradiation-induced structural modification and defect evolution in M n+1 AX n phases is developed, as well as proposed strategies for designing novel M n+1 AX n phases with enhanced performance under extreme irradiation conditions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Temperature and time effects of post-weld heat treatments on tensile properties and microstructure of Zircaloy-4

Opportunities exist to expand the application of Zircaloy-4 (Zry-4) into lower-temperature (<100°C) applications. Welded areas within these structures are potential failure points and post-weld heat treatments (PWHTs) are not yet standardized for application in this temperature range. Zry-4 tungsten inert gas (TIG) welds were given PWHTs from 450-900°C with hold times from 0.5-48 hours to investigate changes to tensile properties and microstructure. Treatment of 800°C for 1 hour was found to produce the most ductile material, measured by total elongation of the tensile bar (16.5%). Furthermore, both PWHT time and temperature were observed to increase total elongation, except in extreme (>800°C or >18hours) cases, but the effect of temperature was stronger. The second order cumulative annealing parameter shows a trend with tensile properties. Average grain sizes in the fusion zone and heat affected zone did not change under any of the PWHTs until the development of an undesirable blocky-alpha phase, which was only observed to form in the heat affected zones for hold times greater than 18hr at 800°C.

36 MATERIALS SCIENCE↗

Subdiffusive High-Pressure Hydrogen Gas Dynamics in Elastomers

We report elastomeric rubber materials serve a vital role as sealing materials in the hydrogen storage and transport infrastructure. With applications including O-rings and hose liners, these components are exposed to pressurized hydrogen at a range of temperatures, cycling rates, and pressure extremes. High-pressure exposure and subsequent rapid decompression often lead to cavitation and stress-induced damage of the elastomer due to localization of the hydrogen gas. Here, we use all-atom classical molecular dynamics simulations to assess the impact of compositional variations on gas diffusion within the commonly used elastomer ethylene–propylene–diene monomer (EPDM). With the aim to build a predictive understanding of precursors to cavitation and to motivate material formulations that are less sensitive to hydrogen-induced failure, we perform systematic simulations of gas dynamics in EPDM as a function of temperature, gas concentration, and cross-link density. Our simulations reveal anomalous, subdiffusive hydrogen motion at pressure and intermediate times. We identify two groups of gas with different mobilities: one group exhibiting high mobility and one group exhibiting low mobility due to their motion being impeded by the polymer. With decreasing temperatures, the low-mobility group shows increased gas localization, the necessary precursor for cavitation damage in these materials. At lower temperatures, increasing cross-link density led to greater hydrogen gas mobility and a lower fraction of caged hydrogen, indicating that increasing cross-link density may reduce precursors to cavitation. Finally, we use a two-state kinetic model to determine the energetics associated with transitions between these two mobility states.

36 MATERIALS SCIENCE↗

Comparing land surface temperature and mean radiant temperature for urban heat mapping in Philadelphia

Many cities are experiencing more frequent extreme heat during hot summers. With the rise of global temperature, the thermal comfort in urban areas become even worse. Quantitative information of the spatial distributions of urban heat has become increasingly important for resilience and adaptation to climate change in cities. This study compares satellite-derived land surface temperature (LST) and urban microclimate modeling-based mean radiant temperature (Tmrt) for mapping the urban heat distributions in Philadelphia, Pennsylvania, USA. Here, the LST was estimated based on Landsat 8 thermal imagery with a spatial resolution of around 100 m, while the Tmrt was simulated based on high resolution LiDAR and national aerial imagery program multispectral aerial imageries with a spatial resolution of 1 m. Result shows that both LST and Tmrt show a similar general pattern of the urban heat across the study area, while the Tmrt presents much more details of the heat variations street by street and neighborhood by neighborhood. The LST tends to have a stronger relationship with the Tmrt on building roofs, which are usually not the place for human activities. This studyprovides evidence for choosing more appropriate metrics in urban heat-related studies.

54 ENVIRONMENTAL SCIENCES↗

$In-situ$ synchrotron x-ray diffraction and thermal expansion of TiB2 up to ~3050 °C

There is an increasing interest in understanding the performance and properties of ultra-high temperature ceramics due to their high melting points (<3000 °C) that make them promising for extreme environment applications. In-situ high temperature X-ray diffraction experiments were performed on TiB 2 beads up to ~3050 °C. For these experiments, TiB 2 powders were fabricated into spherical beads via gel casting methods and densified in a high temperature graphite furnace. These sample beads were then levitated in a conical nozzle levitator with reducing atmosphere (3% H 2 -Ar) while being heated using a 400 W CO 2 laser. During levitation a collimated synchrotron X-ray source was used to perform in-situ, temperature-dependent structural characterizations. The anisotropic coefficients of thermal expansion of TiB 2 were characterized as a function of temperature up to ~3050 °C. Elucidation of these properties are critical for the advancement of TiB 2 ceramics and other transition metal di-borides for use in high temperature applications such as hypersonic platforms, nuclear reactors, and atmospheric re-entry.

36 MATERIALS SCIENCE↗

Formation of a simple cubic antiferromagnet through charge ordering in a double Dirac material

Following the topological classification of electronic phases, interest has grown in materials with unique electronic or magnetic properties driven by topology and interactions. Here, in this study, we report that the topologically nontrivial mixed valent intermetalllic EuPd 3 S 4 undergoes long-range charge ordering at 𝑇 𝐶⁢𝑂 = 340 K wherein 𝐽 = 7/2 Eu 2+ and Van Vleck 𝐽 = 0 Eu 3+ ions on a body-centered-cubic lattice separate into two interpenetrating simple cubic sublattices. The reduced symmetry transmutes 8-fold double Dirac states into 4-fold Dirac states and leads to a simple cubic Heisenberg antiferromagnet with G-type antiferromagnetic order for 𝑇 <⁢ 𝑇 𝑁 = 2.85⁢(6) K. While time reversal symmetry is broken, its combination with nearest neighbor lattice translation can form a nonsymmorphic symmetry preserving the 4-fold Dirac point. The application of a magnetic field yields a spin flop transition at the lowest temperatures but, as a consequence of the extreme isotropy of Eu, that phase transition turns into a cross-over at higher temperatures. Our work demonstrates how charge order modifies topology in EuPd 3 S 4 and exposes an archetypal simple cubic Heisenberg antiferromagnet.

Berry, Tanya [Johns Hopkins Univ., Baltimore, MD (↗

Boundary correlators and the Schwarzian mode

The effective low temperature dynamics of near-extremal black holes is governed by the quantum fluctuations of the Schwarzian mode of JT gravity. Utilizing as a proxy a planar charged black hole in asymptotically Anti-de-Sitter spacetime, we investigate the effects of these fluctuations on a probe scalar field. The corresponding holographic real-time boundary correlators are computed following a holographic renormalization procedure, using the dubbed gravitational Schwinger-Keldysh geometry (grSK) and known exact results of boundary correlators from the near-horizon region. This analysis gives rise to a retarded Green’s function that decays as a power law for late Lorentzian times. Its analytic structure indicates the presence of a branch cut in the complex frequency domain at finite temperature. These features are a non-perturbative hallmark that prevails as long as the planar transverse space is kept compact.

2D Gravity↗

Temperature and Strain Sensing Characteristics of a 128° YX-Cut LiNbO 3 Rayleigh-Mode SAW Sensor From Room to Cryogenic Temperatures

Accurate, passive, and wireless monitoring of cryogenic hardware is essential for high-energy physics, space propulsion, and biomedical instrumentation. Here, this study quantifies the coupled temperature-strain behavior of Rayleigh-mode surface acoustic-wave (SAW) delay-line sensors fabricated on 128° YX-cut LiNbO 3 . A nonlinear finite element (FE) model incorporating Varshni-based elastic constants, higher-order thermal expansion, and temperature-dependent piezo- and dielectric coefficients was developed and validated experimentally between 280K and 80K. Free-standing (first test condition) and bonded/wired (second test condition) devices exhibited indistinguishable thermal responses; the average temperature coefficient of delay (TCD) in the critical cryogenic range from 130K down to 80K differed by only 0.15 ppm/K (0.32%), confirming that bonding-induced stress is negligible. Over 280-80K the measured TCD was 61.77 ppm/K, while the FE model predicted an equivalent temperature coefficient of frequency (TCF) of −62.74 ppm/K with an overall coefficient of determination R2 = 0.998. In the critical cryogenic interval 130-80K the TCD fell to 47.66 ppm/K, indicating improved thermal stability at low temperature. Controlled loading (0-300 με) revealed a strain coefficient of delay (SCD) that rises from 0.53 ± 0.02 ppm/με at 300K to 1.05 ± 0.02 ppm/με at 80K. This modest sensitivity confirms that, for temperature sensing, strain is a second-order perturbation above 135K but must be compensated at deeper cryogenic levels. Overall, this work establishes a predictive multiphysics model together with repeatable wired measurements that confirm the suitability of SAW sensors for temperature and strain monitoring in extreme cryogenic environments, while also providing a baseline for future wireless implementations.

25 ENERGY STORAGE↗

Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0

Abstract. Wildfires are becoming an increasing challenge to the sustainability of boreal peatland (BP) ecosystems and can alter the stability of boreal carbon storage. However, predicting the occurrence of rare and extreme BP fires proves to be challenging, and gaining a quantitative understanding of the factors, both natural and anthropogenic, inducing BP fires remains elusive. Here, we quantified the predictability of BP fires and their primary controlling factors from 1997 to 2015 using a two-step correcting machine learning (ML) framework that combines multiple ML classifiers, regression models, and an error-correcting technique. We found that (1) the adopted oversampling algorithm effectively addressed the unbalanced data and improved the recall rate by 26.88 %–48.62 % when using multiple datasets, and the error-correcting technique tackled the overestimation of fire sizes during fire seasons; (2) nonparametric models outperformed parametric models in predicting fire occurrences, and the random forest machine learning model performed the best, with the area under the receiver operating characteristic curve ranging from 0.83 to 0.93 across multiple fire datasets; and (3) four sets of factor-control simulations consistently indicated the dominant role of temperature, air dryness, and climate extreme (i.e., frost) for boreal peatland fires, overriding the effects of precipitation, wind speed, and human activities. Our findings demonstrate the efficiency and accuracy of ML techniques in predicting rare and extreme fire events and disentangle the primary factors determining BP fires, which are critical for predicting future fire risks under climate change.

54 ENVIRONMENTAL SCIENCES↗

The hazard components of representative key risks. The physical climate perspective

The framework of Representative Key Risks (RKRs) has been adopted by the Intergovernmental Panel on Climate Change Working Group II in order to categorize, assess and communicate a wide range of regional and sectoral key risks, expected to become severe as a consequence of the potentially detrimental convergence of changing climate conditions, exposure and vulnerability of human and natural systems, and responses through (mal)adaptation measures. Other papers in this special issue treat each of eight RKRs by holistically assessing their current status and future evolution as a result of this convergence. However, their treatment cannot always organize such assessment according to a systematic gradation of climatic changes, often times having to extrapolate the big-picture evolution of risk from either qualitative effects of “low” medium” and “high” warming, or limited/focused analysis of the consequences of particular mitigation choices (e.g., benefits of limiting warming to 1.5 or 2C). In this study we offer as systematic a representation as possible – given current literature and assessments – of the future evolution of the hazard components of RKRs. We draw on the assessment of changes in climatic impact-drivers relevant to RKRs described in the 6th Assessment Report by Working Group 1 (WGI) supplemented when needed by more recent literature. We identify the relevant hazards for each RKR, based upon the WGII authors’ assessment, and we report on their current state and expected future changes in magnitude, intensity and/or frequency, linking these changes to Global Warming Levels to the extent possible. For some of these quantities - like regional trends in oceanic and atmospheric temperature and precipitation, some heat and precipitation extremes, permafrost thaw and Northern Hemisphere snow cover - a strong and quantitative relationship with global average temperature change has been assessed. For others - like frequency and intensity of tropical cyclones and extra-tropical storms, and fire weather - the link to increasing global temperatures can only be described qualitatively. For some processes - like the behavior of ice-sheets, or changes in circulation dynamics - large uncertainties about the effects of different levels of warming remain, and for a few others - like ocean pH and air pollution - the composition of the scenario of anthropogenic emissions is most relevant, rather than the warming reached. In almost all cases, however, the basic message remains that every small increment in CO2 concentration in the atmosphere and associated warming will bring changes in climate phenomena that will contribute to increasing risk of impacts on human and natural systems when these changes happen in conjunction with these systems’ conditions of exposure and vulnerability, and in lack of effective adaptation. Our picture of the evolution of RKR-relevant climatic impact-drivers complements and enriches the treatment of RKRs in the other papers in at least two ways: by filling in an often only cursory or limited representation of the physical climate aspects driving impacts, and by providing a fuller representation of their future possible evolution which represents an important component – if never the only one – of the potential future evolution of risk severity.

54 ENVIRONMENTAL SCIENCES↗

Silica nanocluster binding rate coefficients from molecular dynamics trajectory calculations

Oxide nanoparticle growth from vapor phase precursors occurs in high temperature aerosol reactors first via the formation of nanoclusters, which are nanometer-scale condensed-phase species composed of 10 1 -10 2 atoms. The binding rate for nanoclusters, defined as the rate at which two nanoclusters collide with and stick to one another, is hence of interest in predicting nanoparticle size distribution functions in an aerosol. We have utilized molecular dynamics (MD) trajectory calculations to determine the homogeneous (equal-sized) and heterogeneous (disparate-sized) binding rate coefficients of SiO2 (silica) nanoclusters composed of 18, 144, and 333 atoms. MD trajectory calculations incorporated all-atom models of nanoclusters using a combined Born–Huggins–Mayer-Lennard-Jones potential model, which accounts for both short range interactions and electrostatic interactions. MD calculations were utilized to determine the binding probability as a function of both initial relative velocity and impact parameter; integration of the binding probability across impact parameter and relative velocity space yields the binding rate coefficient. MD trajectory calculations reveal that the most common type of encounters between nanoclusters leading to binding are grazing collisions, i.e. instances where collision would not occur without induced dipole potential influences. The resulting binding rate coefficients are found to be extremely weakly dependent on system temperature, which is in contrast to the use of rate coefficient models which are the product of a hard-sphere collision rate coefficient and a constant enhancement factor (leading to a rate coefficient proportional to the square root of temperature). Enhancement factors defined from MD trajectory calculations fall in the range of 3–9 as system temperature decreases from 1500 K to 300 K. Furthermore, such large values suggest that potential interactions need to be considered when modeling oxide nanocluster growth in the gas phase.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Electrical conductivity of Sn at high pressure and temperature

To date, temperature and conductivity have many outstanding implications in extreme environments but are yet to be fully understood under high pressure and temperature dynamic conditions. Here, we introduce an approach to provide high quality electrical conductivity results under dynamic loading conditions. Emphasis is given to address the skin depth effect's influence in a dynamic loading experiment by using thin films. The thin film samples in this study were at least 100 times thinner than previous samples in dynamic electrical conductivity experiments, increasing the current density to its full potential across the sample's entire cross section. Consideration of the skin depth accounts for at minimum a 4× scaling factor to the final electrical conductivity result that has been neglected in previous dynamic electrical conductivity studies. We also obtained improved signal-to-noise ratio with custom diagnostics optimized for better electrical impedance matching. Furthermore, these considerations were applied to Sn to assess electrical conductivity at elevated pressure and temperature. The high signal-to-noise ratio with reduced skin depth influence results in Sn allowing observation of the conductivity changes related to solid-to-solid and solid-to-liquid phase transitions. Additionally, we calculate the Sn thermal conductivity using the Wiedemann-Franz law for our experiments and compare against thermal transport dependent temperature measurements from previous work.

36 MATERIALS SCIENCE↗

Tailoring the coefficient of thermal expansion of ternary nickel alloys through compositional control and non-contact measurements

The majority of microelectromechanical systems (MEMS) are made of silicon, however, future applications will be used in extreme environments, especially at elevated temperatures, and require materials with enhanced properties. Use of metal alloys in these applications will require microscale manufacturability, a balance of physical and mechanical properties and dimensional stability. Here in this paper, we emphasized dimensional stability by reducing the coefficient of thermal expansion (CTE) and present an optical non-contact method for measuring the thermal expansion of planar thin films. A combinatorial approach was employed to determine the CTE of nickel-molybdenum-tungsten (Ni-Mo-W) sputter deposited films over a range of compositions, and the addition of Mo and W is shown to significantly decrease and provide a route for tailoring the CTE with compositional control. Ni-Mo-W alloys were revealed to have CTE values ranging from 8–12 × 10 -6 /°C, matching that of commercial glass substrates that are employed in numerous MEMS devices.

36 MATERIALS SCIENCE↗

A NEA review on innovative structural materials solutions, including advanced manufacturing processes for nuclear applications based on technology readiness assessment

The Nuclear Energy Agency (NEA) Expert Group on Innovative Structural Materials (EGISM) was established in 2008 under the guidance of the Nuclear Science Committee (NSC). Its objectives are to conduct joint and comparative studies to support the development, selection and characterisation of innovative structural materials that can be implemented in advanced nuclear fuel cycles, under long service lifetime and extreme conditions, such as high temperature, high dose/dose rate and corrosive chemical environments. In this context of growing interest and initiatives, the EGISM initiated at the beginning of 2018 an activity among its members to: Identify, in a non-exhaustive way, the currently existing programs on innovative materials and fabrication processes in NEA member countries and China; Establish a first cartography of the activities that are underway on these topics and identify common subjects and thematic; Propose a Technology Readiness Level scale to estimate the maturity of both innovative materials and fabrication processes; Carry out a reflection on what the enablers are to quickly climb this TRL scale, as well as the obstacles, in order to identify solutions to overcome them. This paper first gives definitions shared between the EGISM members on what are considered as advanced structural materials solutions. Next, some international initiatives for the accelerated development of high performance materials are presented both in non-nuclear and nuclear fields. Then, the methodology adopted for technology readiness assessment is explained. A non-exhaustive synthesis of the projects identified among the EGISM members on innovative structural materials and advanced manufacturing solutions such as additive manufacturing is presented. The TRL level of these projects is evaluated. A focus is also made on some of these projects to illustrate and explain the TRLs chosen as well as highlighting enablers or obstacles identified to climbing up the TRL scale.

36 MATERIALS SCIENCE↗

Ultrafast Spin Crossover in a Room-Temperature Ferrimagnet: Element-Specific Spin Dynamics in Photoexcited Cobalt Ferrite

Transition metal complexes capable of photoinduced spin crossover have been greatly investigated because of their potential to enable ultrafast optical control of information processing. Yet, any real application of photoswitchable molecules requires that spin crossover be paired with additional functionality such as long-range magnetic order. Important advances combining these functions are notably reported for a number of bimetallic Prussian Blue analogues; however, to date, PBA-based magnetic photoswitches can only operate below 150 K due to loss of magnetic order. In contrast, cobalt ferrite is a ferrimagnetic semiconductor with a Curie temperature of 790 K and extremely favorable magnetic properties by comparison to state-of-the-art PBAs. The mixed valence electronic structure of cobalt ferrite is reminiscent of cobalt–iron PBA, which is a well-known photoswitch. To investigate the potential for photoswitching in this material, we employ transient XUV spectroscopy to probe charge and spin dynamics with element-specific resolution on the femtosecond time scale. Results show that 400 nm light excites a metal-to-metal charge transfer transition, which drives the crossover of high-spin Co 2+ to low-spin Co 3+ with a time constant of 405 ± 29 fs and an internal quantum efficiency of unity. This result establishes the existence of efficient photoswitching in a new class of robust ferrimagnetic spinel ferrites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanoprecipitates to Enhance Radiation Tolerance in High-Entropy Alloys

The growth of advanced energy technologies for power generation is enabled by the design, development, and integration of structural materials that can withstand extreme environments, such as high temperatures, radiation damage, and corrosion. High-entropy alloys (HEAs) are a class of structural materials in which suitable chemical elements in four or more numbers are mixed to typically produce single-phase concentrated solid solution alloys (CSAs). Many of these alloys exhibit good radiation tolerance like limited void swelling and hardening up to relatively medium radiation doses (tens of displacements per atom (dpa)); however, at higher radiation damage levels (>50 dpa), some HEAs suffer from considerable void swelling limiting their near-term acceptance for advanced nuclear reactor concepts. In this study, we developed a HEA containing a high density of Cu-rich nanoprecipitates distributed in the HEA matrix. The Cu-added HEA, NiCoFeCrCu 0.12 , shows excellent void swelling resistance and negligible radiation-induced hardening upon irradiation up to high radiation doses (i.e., higher than 100 dpa). The void swelling resistance of the alloy is measured to be significantly better than NiCoFeCr CSA and austenitic stainless steels. Density functional theory simulations predict lower vacancy and interstitial formation energies at the coherent interfaces between Cu-rich nanoprecipitates and the HEA matrix. The alloy maintained a high sink strength achieved via nanoprecipitates and the coherent interface with the matrix at a high radiation dose (~50 dpa). From our experiments and simulations, the effective recombination of radiation-produced vacancies and interstitials at the coherent interfaces of the nanoprecipitates is suggested to be the critical mechanism responsible for the radiation tolerance of the alloy. Furthermore, the materials design strategy based on incorporating a high density of interfaces can be applied to high-entropy alloy systems to improve their radiation tolerance.

36 MATERIALS SCIENCE↗

A Decadal Hybrid GCM Simulation Using Deep‐Learning‐Based Cloud and Convection Parameterization Generalized to a Warm Climate

A critical challenge for machine‐learning (ML) parameterization in global climate models (GCMs) is to achieve stable, accurate simulations under climates not seen during training. Previous studies have demonstrated promising offline performance and year‐long online stability in aquaplanet simulations but have encountered difficulties in real geography and under climate warming. Here we report that a GCM with real geography configuration using neural‐network‐based cloud and convection parameterization, trained exclusively with present‐day climate data, successfully performs a stable, decade‐long simulation of a warm climate with +4 K sea surface temperature (SST). The neural network (NN) is based on Han et al. (2023, https://doi.org/10.1029/2022ms003508 ) with additional inputs. The simulation captures the global precipitation distribution, surface temperatures, vertical atmospheric structures, and extreme precipitation very well, closely matching simulations from both the superparameterized CAM (SPCAM) and the conventional CAM5 in the warm climate without accuracy degradation compared to those in the baseline climate. Moreover, it produces a climate response to +4 K SST in atmospheric thermodynamic states and circulations similar to those from SPCAM and CAM5. Prognostic ablation tests on NN input variables show that the NN without convective memory as input suffers from numerical instability, and the NN without considering radiative variables and land fraction as input, or with reduced training samples produce less accurate results. To our knowledge, this is the first time an ML parameterization successfully achieves online extrapolation to a warm climate without using additional warm‐climate data for training. It demonstrates the potential of ML‐driven parameterizations for credible long‐term climate projections.

Atmosphere model↗

Rapid and efficient hydrogen clathrate hydrate formation in confined nanospace

Clathrate hydrates are crystalline solids characterized by their ability to accommodate large quantities of guest molecules. Although CH 4 and CO 2 are the traditional guests found in natural systems, incorporating smaller molecules (e.g., H 2 ) is challenging due to the need to apply higher pressures to stabilize the hydrogen-bonded network. Another critical limitation of hydrates is the slow nucleation and growth kinetics. Here, we show that specially designed activated carbon materials can surpass these obstacles by acting as nanoreactors promoting the nucleation and growth of H 2 hydrates. The confinement effects in the inner cavities promote the massive growth of hydrogen hydrates at moderate temperatures, using pure water, with extremely fast kinetics and much lower pressures than the bulk system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗