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At least 811 records · Page 45

Interface structures of inclined ZnO thin film on (0 1 1)-MgO substrate with bulk-like optical properties

Combining different phase structure materials with unique properties to design novel devices plays a significant role in the development of modern electronics. Here, we explore the characteristics of this type of complex interface and epitaxy structures based on the coupling between hexagonal ZnO film and cubic MgO substrate. The ZnO film was prepared by the molecular beam epitaxy technique on the MgO (0 1 1) substrate. The analysis results from the in situ reflection high energy electron diffraction patterns, X-ray diffraction (XRD)-pole figures and high resolution transmission electron microscopy images demonstrate that the film exhibits two-fold symmetry domains with a growth direction deviated from c-axis at about 31º along the [0 1 0] MgO or [0 $\bar{1}$ 0] MgO azimuth. Despite the intertwined diffusion from Zn and Mg atoms in the interface, which is the possible origin of a blue shift of about 0.083 eV in the Photoluminescence (PL) spectrum, the inclined film shows a full width at half maximum value that is close to the reported value from the high quality film. Finally, this work hopefully provides useful insights to the design and exploration of the novel optoelectronic devices that involve the integration of materials with different structure and different properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Toward DMC Accuracy Across Chemical Space with Scalable Δ-QML

In the past decade, quantum diffusion Monte Carlo (DMC) has been demonstrated to successfully predict the energetics and properties of a wide range of molecules and solids by numerically solving the electronic many-body Schrödinger equation. With O(N 3 ) scaling with the number of electrons N, DMC has the potential to be a reference method for larger systems that are not accessible to more traditional methods such as CCSD(T). Assessing the accuracy of DMC for smaller molecules becomes the stepping stone in making the method a reference for larger systems. We show that when coupled with quantum machine learning (QML)-based surrogate methods, the computational burden can be alleviated such that quantum Monte Carlo (QMC) shows clear potential to undergird the formation of high-quality descriptions across chemical space. We discuss three crucial approximations necessary to accomplish this: the fixed-node approximation, universal and accurate references for chemical bond dissociation energies, and scalable minimal amons-set-based QML (AQML) models. Numerical evidence presented includes converged DMC results for over 1000 small organic molecules with up to five heavy atoms used as amons and 50 medium-sized organic molecules with nine heavy atoms to validate the AQML predictions. Finally, numerical evidence collected for Δ-AQML models suggests that already modestly sized QMC training data sets of amons suffice to predict total energies with near chemical accuracy throughout chemical space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Visualization of dynamic polaronic strain fields in hybrid lead halide perovskites

Excitation localization involving dynamic nanoscale distortions is a central aspect of photocatalysis, quantum materials and molecular optoelectronics. Experimental characterization of such distortions requires techniques sensitive to the formation of point-defect-like local structural rearrangements in real time. Here, we visualize excitation-induced strain fields in a prototypical member of the lead halide perovskites via femtosecond resolution diffuse X-ray scattering measurements. Here, this enables momentum-resolved phonon spectroscopy of the locally distorted structure and reveals radially expanding nanometre-scale strain fields associated with the formation and relaxation of polarons in photoexcited perovskites. Quantitative estimates of the magnitude and shape of this polaronic distortion are obtained, providing direct insights into the dynamic structural distortions that occur in these materials. Optical pump–probe reflection spectroscopy corroborates these results and shows how these large polaronic distortions transiently modify the carrier effective mass, providing a unified picture of the coupled structural and electronic dynamics that underlie the optoelectronic functionality of the hybrid perovskites.

36 MATERIALS SCIENCE↗

Construction of generalized quasilinear diffusion coefficient using neural networks with physical restrictions

The quasilinear diffusion coefficient (D QL ) derived from our machine learning framework shows comparable trends with the ground truth D QL obtained from GENRAY-CQL3D simulations. Additionally, for the strong absorption cases, the radial current drive profiles generated using the D QL from our model exhibit consistent behavior with those obtained from the original simulation. These findings indicate the potential of our surrogate modeling approach with physical restrictions to replicate key wave–plasma interaction characteristics while reducing computational costs. Traditionally, calculating D QL for wave–particle interactions relies on computationally intensive wave simulations coupled with Fokker–Planck solvers. To address this challenge, we developed a machine learning-based surrogate model with physical restrictions derived from cold plasma theory and bounce-averaged damping effects. First, we establish the propagation domain of Lower Hybrid Waves in the (N∥, ρ) space by identifying the accessibility limit and determining the upper and lower bounds of N∥ using the Potential Power Deposition (PPD) method. Subsequently, leveraging a database constructed using Latin hypercube sampling alongside the underlying physical restrictions (e.g. PPD), machine learning methods including U-Net and Recurrent Neural Networks are employed to design a physics-restricted machine learning framework capable of reconstructing D QL .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Q3 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q3: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis. • Benchmark between two first wall heat flux mapping methods, identify importance of various heat flux sources and physics impact of using fully coupled CESOL vs post-analysis evaluation. 2. Generate medium fidelity parametrized CAD. • Generate parametrized CAD components for the CAT example case via either user-defined modules called within the geometry generation or by defeatured/parametrized CAD, including DCLL blanket matched to divertor boundary and magnets. Define materials, labels, and boundary conditions for passing the mesh to CFD tools. 3. Demonstrate multiphysics magnet analysis. • Demonstrate magnet analysis workflow called from the FREDA workflow, and 4. Demonstrate nuclear analysis. • Add model to OpenFOAM and/or other codes possibly including Diablo to account for tritium diffusion in solids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

In-situ synthesis of porous metal fluoride@carbon composite via simultaneous etching/fluorination enabled superior Li storage performance

Transition metal fluorides as Li-free conversion-type cathode materials have high theoretical specific capacities, however, their preparation strategy, sluggish electrochemical kinetic and poor cyclability have impeded their wide adoption in lithium-ion batteries. Herein, a facile in-situ synthesis of porous metal-fluoride-carbon composites is accomplished via simultaneous polytetrafluorethylene-based hard template etching and metal fluorination. This not only facilitates fast electron transfer and lithium-ion diffusion kinetics, but also buffers severe volume fluctuation during lithiation/delithation and enables the formation of a uniform and thin Li 2 CO 3 /LiF-rich cathode-electrolyte interphase. Here, as a proof of concept, the as-prepared porous FeF 3 @C (p-FeF 3 @C) indeed exhibits a high specific capacity of 230 mAh g -1 at 0.1 C together with an excellent capacity retention of 92.5% at 1 C for 200-cycles. Moreover, the practicality of the strategy is demonstrated by the superb electrochemical performance of the full-cells coupled with pre-lithiated graphite anodes. Therefore, the proposed novel synthetic strategy will enlighten the future design of high-performance metal-fluoride-carbon composites with porous structure for energy storage applications.

25 ENERGY STORAGE↗

Bond Selective Photochemistry at Metal Nanoparticle Surfaces: CO Desorption from Pt and Pd

The use of visible photon fluxes to influence catalytic reactions on metal nanoparticle surfaces has attracted attention based on observations of reaction mechanisms and selectivity not observed under equilibrium heating. These observations suggest that photon fluxes can selectively impact the rates of certain elementary steps, creating nonequilibrium energy distributions among various reaction pathways. However, quantitative studies validating these hypotheses on metal nanoparticle surfaces are lacking. Here, we examine the influence of continuous wave visible photon fluxes on the CO desorption rates from 1 to 2 nm diameter Pt and Pd nanoparticle surfaces supported on γ-Al 2 O 3 . Temperature-programmed desorption measurements quantified via diffuse reflectance infrared Fourier transform spectroscopy demonstrate that visible photon fluxes significantly enhanced the rate of CO desorption from Pt nanoparticles in a wavelength-dependent manner. 440 nm photons most efficiently promoted CO desorption from Pt nanoparticle surfaces, aligning with the excitation energy for the interfacial electronic transition within the Pt–CO bond. Conversely, visible photon fluxes had no measurable influence on CO desorption rates from Pd nanoparticle surfaces after accounting for photon-induced heating. Density functional theory calculations demonstrate that the Pt–CO bond exhibits a narrower LUMO resonance, stronger coupling between the photoexcitation and forces induced on the metal–C bond, and vibrational energy dissipation that more effectively couples to desorption as compared to Pd–CO. These results demonstrate the specificity photons provide in facilitating chemical reactions on metal nanoparticle surfaces and substantiate the idea that photon fluxes can steer processes and outcomes of catalytic reactions in ways not achievable by equilibrium heating.

desorption↗

Coupled cluster benchmarks of large noncovalent complexes: The L7 dataset as well as DNA–ellipticine and buckycatcher–fullerene

In this work, benchmark binding energies for dispersion-bound complexes in the L7 dataset, the DNA–ellipticine intercalation complex, and the buckycatcher–C60 complex with 120 heavy atoms using a focal-point method based on the canonical form of second-order Møller−Plesset theory (MP2) and the domain based local pair natural orbital scheme for the coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] extrapolated to the complete basis set (CBS) limit are reported. This work allows for increased confidence given the agreement with respect to values recently obtained using the local natural orbital CCSD(T) for L7 and the canonical CCSD(T)/CBS result for the coronene dimer (C2C2PD). Therefore, these results can be considered pushing the CCSD(T)/CBS binding benchmark to the hundred-atom scale. The disagreements between the two state-of-the-art methods, CCSD(T) and fixed-node diffusion Monte Carlo, are substantial with at least 2.0 (∼10%), 1.9 (∼5%), and 10.3 kcal/mol (∼25%) differences for C2C2PD in L7, DNA–ellipticine, and buckycatcher–C60, respectively. Such sizable discrepancy above “chemical accuracy” for large noncovalent complexes indicates how challenging it is to obtain benchmark binding interactions for systems beyond small molecules, although the three up-to-date density functionals, PBE0+D4, ωB97M-V, and B97M-V, agree better with CCSD(T) for these large systems. In addition to reporting these values, different basis sets and various CBS extrapolation parameters for Hartree–Fock and MP2 correlation energies were tested for the first time in large noncovalent complexes with the goal of providing some indications toward optimal cost effective routes to approach the CBS limit without substantial loss in quality.

Ballesteros, Francisco (ORCID:0000000325732307)↗

Numerical thermalization in 2D PIC simulations: Practical estimates for low-temperature plasma simulations

The process of numerical thermalization in particle-in-cell (PIC) simulations has been studied extensively. It is analogous to Coulomb collisions in real plasmas, causing particle velocity distributions (VDFs) to evolve toward a Maxwellian as macroparticles experience polarization drag and resonantly interact with the fluctuation spectrum. This paper presents a practical tutorial on the effects of numerical thermalization in 2D PIC applications. Scenarios of interest include simulations, which must be run for many thousands of plasma periods and contain a population of cold electrons that leave the simulation space very slowly. This is particularly relevant to many low-temperature plasma discharges and materials processing applications. We present numerical drag and diffusion coefficients and their associated timescales for a variety of grid resolutions, discussing the circumstances under which the electron VDF is modified by numerical thermalization. Though the effects described here have been known for many decades, direct comparison of analytically derived, velocity-dependent numerical relaxation timescales to those of other relevant processes has not often been applied in practice due to complications that arise in calculating thermalization rates in 1D simulations. Using these comparisons, we estimate the impact of numerical thermalization in several examples of low-temperature plasma applications including capacitively coupled plasma discharges, inductively coupled plasma discharges, beam plasmas, and hollow cathode discharges. Finally, we discuss possible strategies for mitigating numerical relaxation effects in 2D PIC simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Negligible magnetic losses at low temperatures in liquid phase epitaxy grown Y 3 Fe 5 O 12 films

Yttrium iron garnet (Y 3 Fe 5 O 12 ; YIG) has a unique combination of low magnetic damping, high spin-wave conductivity, and insulating properties that make it a highly attractive material for a variety of applications in the fields of magnetics and spintronics. While the room-temperature magnetization dynamics of YIG have been extensively studied, there are limited reports correlating the low-temperature magnetization dynamics to the material structure or growth method. Here, in this study, we investigate liquid phase epitaxy grown YIG films and their magnetization dynamics at temperatures down to 10 K. We show there is a negligible increase in the ferromagnetic resonance linewidth down to 10 K, which is unique when compared with YIG films grown by other deposition methods. From the broadband ferromagnetic resonance measurements, polarized neutron reflectivity, and scanning transmission electron microscopy, we conclude that these liquid phase epitaxy grown films have negligible rare-earth impurities present, specifically the suppression of Gd diffusion from the Gd 3 Ga 5 O 12 (GGG) substrate into the Y 3 Fe 5 O 12 film, and therefore negligible magnetic losses attributed to the slow-relaxation mechanism. Overall, liquid phase epitaxy YIG films have a YIG/GGG interface that is five times sharper and have ten times lower ferromagnetic resonance linewidths below 50 K than comparable YIG films by other deposition methods. Thus, liquid phase epitaxy grown YIG films are ideal for low-temperature experiments/applications that require low magnetic losses, such as quantum transduction and manipulation via magnon coupling.

36 MATERIALS SCIENCE↗

Radiation GRMHD Models of Accretion onto Stellar-mass Black Holes. II. Super-Eddington Accretion

We present a comprehensive analysis of super-Eddington black hole accretion simulations that solve the GRMHD equations coupled with angle-discretized radiation transport. The simulations span a range of accretion rates, two black hole spins, and two magnetic field topologies, and include resolution studies as well as comparisons with nonradiative models. Super-Eddington accretion flows consistently develop geometrically thick disks supported by radiation pressure, regardless of magnetic field configuration. Radiation generated in the inner disk drives substantial outflows, forming conical funnel regions that limit photon escape and result in very low radiation efficiency. The accretion flows are highly turbulent, with thermal energy transport dominated by radiation advection rather than diffusion. Angular momentum is primarily carried outward by Maxwell stress, with turbulent Reynolds stress playing a subdominant role. Both strong and weak jets are produced. Strong jets arise from sufficient net vertical magnetic flux and rapid black hole spin, and they can effectively evacuate the funnel, enabling radiation to escape through strong geometric beaming. In contrast, weak jets fail to clear the funnel, which becomes obscured by radiation-driven outflows and leads to distinct observational signatures. Spiral structures are observed in the plunging region, behaving like density waves. These super-Eddington models are applicable to a variety of astronomical systems, including ultraluminous X-ray sources, little red dots, and black hole transients.

79 ASTRONOMY AND ASTROPHYSICS↗

Interfacial Hydrogen-Bond Dynamics in Transition Metal Compounds

Understanding how water behaves when confined within atomic layers of active transition-metal carbides, nitrides, and carbonitrides is essential for uncovering the fundamental principles needed to engineer solid–liquid interfaces at the atomic scale. Yet, how lattice element chemistry and surface termination groups collectively regulate the structure and mobility of such interlayer water remains poorly understood. Here, we present a composition-controlled investigation of interlayer water dynamics in layered transition-metal nitride, carbide, and carbonitride systems using a systematic integration of quasi-elastic neutron scattering (QENS), ab initio molecular dynamics (AIMD) simulations, and density functional theory (DFT) calculations. QENS measurements show that nitride-rich systems host mobile, translationally diffusing water with thermally activated self-diffusion coefficients on the order of 10 –10 m 2 s –1 , whereas mixed C/N lattices confine water to localized, nontranslational motion that is insensitive to temperature. AIMD and DFT reveal that lattice C/N chemistry and surface functional group composition reshape the first hydration layer by modulating the surface electronic structure and termination-dependent hydrogen-bond networks, leading to pronounced differences in water ordering and thermal resilience. On the other hand, fully carbide systems exhibit intermediate behavior, highlighting that water mobility is not primarily controlled by the hydration level alone but by the coupling between lattice composition and surface chemistry. Overall, this study establishes how surface chemistry and lattice composition jointly control interfacial hydrogen bond dynamics, offering a mechanistic framework for designing transition-metal layered materials with tailored interfacial transport properties.

Hydration↗

Dynamics of superconducting qubit relaxation times

Superconducting qubits are a leading candidate for quantum computing but display temporal fluctuations in their energy relaxation times T 1 . This introduces instabilities in multi-qubit device performance. Furthermore, autocorrelation in these time fluctuations introduces challenges for obtaining representative measures of T 1 for process optimization and device screening. These T 1 fluctuations are often attributed to time varying coupling of the qubit to defects, putative two level systems (TLSs). In this work, we develop a technique to probe the spectral and temporal dynamics of T 1 in single junction transmons by repeated T 1 measurements in the frequency vicinity of the bare qubit transition, via the AC-Stark effect. Across 10 qubits, we observe strong correlations between the mean T 1 averaged over approximately nine months and a snapshot of an equally weighted T 1 average over the Stark shifted frequency range. These observations are suggestive of an ergodic-like spectral diffusion of TLSs dominating T 1 , and offer a promising path to more rapid T 1 characterization for device screening and process optimization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Accelerated Materials Design for Molten Salt Technologies Using Innovative High-Throughput Methods

The focus of the project is on building an innovative accelerated materials design platform for molten salt technologies using novel high-throughput methods coupled to data analytics. The main objectives is to predict a FeCrMnNi alloy compositional space with better corrosion resistance than stainless steel 316 and identify new molten salt corrosion mechanisms. The project demonstrates the feasibility to use high-throughput methods coupled to data analytics to accelerate alloy design for extreme environments applications. Using a trained and tested machine learning (ML) model, 2000 FeCrMnNi alloy corrosion rate in molten chloride salts were predicted and a compositional field with corrosion rate lower than 316 stainless steel was identified. The ML model interpretability unveiled multiple features of importance in the model prediction. Some features were expected to be of relative significance, such as work function, surface energy and alloy electronegativity, and the ML model interpretability analysis confirmed those. On the other hand, the most important feature is the diffusion coefficient of Ni in the bulk alloy which indicates that a surface diffusion mechanism plays an important role in the overall corrosion mechanism in molten salts.

36 MATERIALS SCIENCE↗

Anthropogenic extremely low volatility organics (ELVOCs) Govern the Growth of Molecular Clusters over the Southern Great Plains during the Springtime

New particle formation (NPF) and growth govern cloud condensation nuclei (CCN) concentrations in many regions. The mechanisms governing the nucleation of molecular clusters vary substantially in different regions of the atmosphere. Additionally, the growth of these clusters from ~2 to 20 nm sizes is often governed by the availability of extremely low volatility organic vapours (ELVOCs). While the pathways to ELVOC formation from the oxidation of biogenic monoterpenes with ozone is better understood, the chemical and mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are not well understood. We integrate measurements and three-dimensional regional model simulations with the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to understand the processes governing new particle formation and growth and secondary organic aerosol (SOA) formation during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign at the Southern Great Plains (SGP) observatory in Oklahoma, and contrast it with a site within the Bankhead National Forest (BNF), Alabama in Southeast USA, where 5-year long measurements will begin in 2024. Simulations show that nucleation rates are at least an order of magnitude higher at SGP compared to BNF during the springtime days (April 28 and May 14, 2016), largely due to lower H2SO4 concentrations at BNF, which are needed for nucleation. In addition, the larger CS at BNF (compared to SGP) increase the loss of molecular clusters by coagulation to pre-existing particles. Among the 8 different nucleation mechanisms in WRF-Chem, we find that the amine+H2SO4 nucleation mechanism dominates at the SGP site, while the pure organic ion induced nucleation mechanism dominates over BNF. Through various WRF-Chem sensitivity simulations, we find that anthropogenic ELVOCs are critical for explaining the growth of newly formed particles and the resulting number size distribution observed near the surface at the SGP site during the daytime. In addition, we show that treating organic particles as semisolid, with strong diffusion-limited uptake of organic vapours, brings model predictions into closer agreement with the observed evolution of particle size distribution. Simulations also predict that anthropogenic SOA, formed by the oxidation of aromatic volatile organic compounds (VOCs), is the dominant organic aerosol component at SGP, while biogenic SOA dominates particle composition at the BNF site in Southeast USA on these days.

Shrivastava, ManishKumar B.↗

Visible-Light-Driven, Iridium-Catalyzed Hydrogen Atom Transfer: Mechanistic Studies, Identification of Intermediates, and Catalyst Improvements

The harvesting of visible light is a powerful strategy for the synthesis of weak chemical bonds involving hydrogen that are below the thermodynamic threshold for spontaneous H 2 evolution. Piano-stool iridium hydride complexes are effective for the bluelight- driven hydrogenation of organic substrates and contrathermodynamic dearomative isomerization. In this work, a combination of spectroscopic measurements, isotopic labeling, structure–reactivity relationships, and computational studies has been used to explore the mechanism of these stoichiometric and catalytic reactions. Photophysical measurements on the iridium hydride catalysts demonstrated the generation of long-lived excited states with principally metal-to-ligand charge transfer (MLCT) character. Transient absorption spectroscopic studies with a representative substrate, anthracene revealed a diffusion-controlled dynamic quenching of the MLCT state. The triplet state of anthracene was detected immediately after the quenching events, suggesting that triplet–triplet energy transfer initiated the photocatalytic process. The key role of triplet anthracene on the post-energy transfer step was further demonstrated by employing photocatalytic hydrogenation with a triplet photosensitizer and a HAT agent, hydroquinone. DFT calculations support a concerted hydrogen atom transfer mechanism in lieu of stepwise electron/proton or proton/electron transfer pathways. Kinetic monitoring of the deactivation channel established an inverse kinetic isotope effect, supporting reversible C(sp 2 )–H reductive coupling followed by rate-limiting ligand dissociation. Mechanistic insights enabled design of a piano-stool iridium hydride catalyst with a rationally modified supporting ligand that exhibited improved photostability under blue light irradiation. The complex also provided improved catalytic performance toward photoinduced hydrogenation with H 2 and contra-thermodynamic isomerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Validation of a comprehensive first-principles-based framework for predicting the performance of future stellarators

This paper presents the validation of the GENE-KNOSOS-Tango framework for recovering both the steady-state plasma profiles in the considered radial domain and selected turbulence trends in a stellarator. This framework couples the gyrokinetic turbulence code GENE, the neoclassical transport code KNOSOS, and the transport solver Tango in a multi-timescale simulation feedback loop. Ion-scale kinetic-electron and electron-scale adiabatic-ion flux-tube simulations were performed to evolve the density and temperature profiles for four OP1.2b W7-X scenarios. The simulated density and temperature profiles showed good agreement with the experimental data using a reasonable set of boundary conditions. Equally important was the reproduction of observed trends for several turbulence properties, such as density fluctuations and turbulent heat diffusivities. Key effects were also touched upon, such as electron-scale turbulence and the neoclassical radial electric field shear. The validation of the GENE-KNOSOS-Tango framework enables credible predictions of physical phenomena in stellarators and reactor performance based on a given set of edge parameters.

Gyrokinetic simulations↗

Thermophysical properties of the Ghareb formation relevant for nuclear waste disposal

The Ghareb formation, a shallowly buried porous chalk in Israel, is currently a candidate for nuclear waste disposal. The potential repository is somewhat unique for its host rock and emplacement in shallow (500 m) engineered large diameter boreholes. Herein, the thermal properties of the Ghareb are determined to support design and performance assessment; the relevant properties measured are thermal conductivity, specific heat capacity, thermal diffusivity, and thermal expansion coefficient along with their relationship with varying temperature. For the temperature range of 40 to 275 °C, the thermal conductivity ranges from 0.30 to 1.10 W/m·K, the thermal diffusivity ranges from 0.20 to 0.72 mm 2 /s, and volumetric heat capacity ranges from 0.86 to 2.00 MJ/m 3 ·K. Thermal strain measurements were used to estimate the linear thermal expansion coefficient to be 6·10 –4 –9·10 –2 °C -1 from 40 to 300 °C. These measured properties were used in a thermomechanical model to estimate near-field stresses an hour and 10 years after waste emplacement; the borehole was found to be stable. Thermal loading after 10 years was predicted to elevate local pore pressures by 1–1.5 MPa. The laboratory measurements coupled with analyses are the first attempts at performance assessment characterization for this first of its kind potential repository setting with this chosen host rock.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗