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DOE OSTI2025

Iron XANES measurements of carbonates and phyllosilicates in CM chondrites: A record of redox conditions during aqueous alteration

Multiple generations of calcite and dolomite precipitated in CM chondrites during ice melting events that led to episodes of liquid water. Models and laboratory analysis have suggested a long-term transition from oxidizing to reducing conditions during aqueous alteration on the CM parent body. We found that synchrotron X-ray absorption near edge spectroscopy (XANES) can detect relative differences in the oxidation state of trace iron within these carbonates. In CM chondrites, previous work interpreted Mn abundance in calcite as an indicator of relatively early or late formation, and dolomite is understood to form relatively late. In the CM1 chondrite Meteorite Hills 01070, XANES maps reveal that Mn-poor calcite contains more oxidized iron relative to Mn-rich calcite. While these measurements of carbonates support increasing iron reduction with progressive aqueous alteration in MET 01070, comparison among different CM chondrites suggests a complex picture of redox evolution. In addition to carbonates, we performed XANES measurements of the phyllosilicate-rich matrix of Allan Hills 83,100. Pre-edge centroid analysis indicates that this CM1/2 has an oxidation state similar to typical CM2 chondrites. While additional measurements are warranted to confirm the full span of redox trends in CM carbonates, our data do not support a correlation between redox state and petrologic type.

Bailey, Elizabeth [Univ. of California, Santa Cruz↗

DOE OSTI2025

Search for dark matter produced in association with a Higgs boson decaying to a τ lepton pair in proton-proton collisions at $\sqrt{s}=13$ TeV

A search for dark matter particles produced in association with a Higgs boson decaying into a pair of τ leptons is performed using data collected in proton-proton collisions at a center-of-mass energy of 13 TeV with the CMS detector. The analysis is based on a data set corresponding to an integrated luminosity of 101 fb −1 collected in 2017–2018. No significant excess over the expected standard model background is observed. This result is interpreted within the frameworks of the 2HDM+a and baryonic Z′ benchmark simplified models. The 2HDM+a model is a type-II two-Higgs-doublet model featuring a heavy pseudoscalar with an additional light pseudoscalar. Upper limits at 95% confidence level are set on the product of the production cross section and the branching fraction for each of these two simplified models. Heavy pseudoscalar boson masses between 400 and 700 GeV are excluded for a light pseudoscalar mass of 100 GeV. For the baryonic Z′ model, a statistical combination is made with an earlier search based on a data set of 36 fb −1 collected in 2016. In this model, Z′ boson masses up to 1050 GeV are excluded for a dark matter particle mass of 1 GeV.

Dark Matter↗

DOE OSTI2023

Exact hopfion vortices in a 3D Heisenberg ferromagnet

Here, we find exact static soliton solutions for the unit spin vector field of an inhomogeneous, anisotropic three-dimensional Heisenberg ferromagnet. Each soliton is labeled by two integers n and m. It is a (modified) skyrmion in the z = 0 plane with winding number n, which twists out of the plane m times in the z-direction to become a 3D soliton. Here m arises due to the periodic boundary condition at the z-boundaries. We use Whitehead’s integral expression to find that the Hopf invariant of the soliton is an integer H = nm. It represents a hopfion vortex. Plots of the preimages of this topological soliton show that they are either unknots or nontrivial knots, depending on n and m. Any pair of preimage curves links H times, corroborating the interpretation of H as a linking number. We also calculate the exact energy of the hopfion vortex, and show that its topological lower bound has a sublinear dependence on H. Using Derrick’s scaling analysis, we demonstrate that the presence of a spatial inhomogeneity in the anisotropic interaction, which in turn introduces a characteristic length scale in the system, leads to the stability of the hopfion vortex.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Theoretical Evaluation of Metal–Ligand Bonding in Neptunium Compounds in Relation to 237 Np Mössbauer Spectroscopy

The 237 Np Mössbauer isomer shift and quadrupole splitting (QS) are powerful probes for the metal–ligand bonding of neptunium, a 5f-element of vital importance in the nuclear fuel cycle. A large set of Np compounds with different oxidation states (III) to (VII) is studied to investigate, by first-principles calculations, isomer shifts and the QS trends in relation to the Np oxidation state. Natural Bond Orbital analysis reveals that in addition to donation bonding to the 5f shell, participation of the 6d and 7s neptunium shells in covalent (donation) bonding substantially impacts the isomer shifts. The isomer shift cannot be interpreted solely by the 5f shell electron count. The isomer shift for Np(II) compounds is estimated to be in the range of 31–34 mm/s, less positive than for Np(III) compounds. For the QS, density functional calculations fail to reproduce the quadrupole splitting for some Np(VI) ionic solids. A multiconfigurational wave function approach reproduces the observed QS trends. The calculations give a semiquantitative interpretation of the trends for Np oxidation states (V) to (VII). Furthermore, the contrasting QS for standard and “reverse” neptunyl(VI), at the opposite extremes of the observed QS scale, arises predominantly from the different crystal environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Bootstrapping the String Kawai-Lewellen-Tye Kernel

We show that a generalized version of the 4-point string theory KLT double-copy map is the most general solution to the minimal-rank double-copy bootstrap in effective field theory. This follows from significant restrictions of the 4-point map resulting from the 6-point bootstrap analysis. The generalized 4-point double-copy map is defined by a function with only two parameters times a simple function that is symmetric in s,t,u. The two parameters can be interpreted as independent choices of α', one for each of the two sets of amplitudes double-copied with the map. Specifically, each of those two sets of amplitudes must obey either the string monodromy relations or the field theory KK & BCJ relations; there are no other options. We propose a closed form of the new double-copy map that interpolates between the original KLT string double-copy and the open & closed string period integrals. The construction clarifies the "single-valued projection" property of the Riemann zeta-function values for the 4-point string theory double copy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Exploring the impact of Cr-doping on the crystallographic and magnetic structure of Mn 5 Si 3 antiferromagnetic alloy

Here, the role of Cr-doping on the structural and magnetic ground states of Mn 5 Si 3 alloy has been investigated through temperature-dependent neutron powder diffraction (NPD) and X-ray absorption fine structure (XAFS) techniques. All the Cr-doped alloys of nominal composition Mn 5-x Cr x Si 3 (for x = 0.05, 0.1, and 0.2) undergo two first-order magneto-structural phase transitions from hexagonal (space group: P6 3 /mcm) paramagnetic → orthorhombic (space group: Ccmm) collinear antiferromagnetic → orthorhombic (space group: Cc2m) non-collinear antiferromagnetic phase on cooling from room temperature. NPD studies at different constant temperatures indicate that both anti ferromagnetic phases are commensurate in nature and can be represented by q = (0,1,0) magnetic propagation vector for all the Cr-doped alloys. Such doping at the Mn-site results in a significant modification of the non-collinear antiferromagnetic structure (both moment size and orientation) and hence affects the unusual magnetic properties, like inverted hysteresis loop, thermomagnetic irreversibility, etc. The XAFS measurements were performed to interpret the local environment of doped Cr atoms in detail, which is critical for a microscopic understanding of the unusual properties of this class of Cr-doped Mn 5 Si 3 alloys. The analysis confirms the elemental state of Cr in the doped alloys and indicates a high degree of preservation of local crystallographic structure with varying Cr concentration and sample temperature. Doping induces intriguing changes in XAFS patterns, elucidated through different types of scattering mechanisms associated with the central absorbing Cr atom.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Search for a scalar partner of the top quark in the all-hadronic $t{\bar{t}}$ plus missing transverse momentum final state at $\sqrt{s}=13$ TeV with the ATLAS detector

A search for direct pair production of scalar partners of the top quark (top squarks or scalar third-generation up-type leptoquarks) in the all-hadronic $t{\bar{t}}$ plus missing transverse momentum final state is presented. The analysis of 139 $\hbox {fb}^{-1}$ of ${\sqrt{s}=13}$ TeV proton–proton collision data collected using the ATLAS detector at the LHC yields no significant excess over the Standard Model background expectation. To interpret the results, a supersymmetric model is used where the top squark decays via ${\tilde{t}} \rightarrow t^{(*)} {\tilde{\chi }}^0_1$ t ~ → t ( * ) χ ~ 1 0 , with $t^{(*)}$ t ( * ) denoting an on-shell (off-shell) top quark and ${\tilde{\chi }}^0_1$ χ ~ 1 0 the lightest neutralino. Three specific event selections are optimised for the following scenarios. In the scenario where $m_{{\tilde{t}}}> m_t+m_{{\tilde{\chi }}^0_1}$ m t ~ > m t + m χ ~ 1 0 , top squark masses are excluded in the range 400–1250 GeV for ${\tilde{\chi }}^0_1$ χ ~ 1 0 masses below 200 GeV at 95% confidence level. In the situation where $m_{{\tilde{t}}}\sim m_t+m_{{\tilde{\chi }}^0_1}$ m t ~ ~ m t + m χ ~ 1 0 , top squark masses in the range 300–630 GeV are excluded, while in the case where $m_{{\tilde{t}}}< m_W+m_b+m_{{\tilde{\chi }}^0_1}$ m t ~ < m W + m b + m χ ~ 1 0 (with $m_{{\tilde{t}}}-m_{{\tilde{\chi }}^0_1}\ge 5$ m t ~ - m χ ~ 1 0 ≥ 5 GeV), considered for the first time in an ATLAS all-hadronic search, top squark masses in the range 300–660 GeV are excluded. Limits are also set for scalar third-generation up-type leptoquarks, excluding leptoquarks with masses below 1240 GeV when considering only leptoquark decays into a top quark and a neutrino.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Performing k eff Validation of As-Loaded Criticality Safety Calculations Using UNF-ST&DARDS: Applicable Experiment Selection

The general method for performing validation of as loaded criticality safety calculations using UNF ST&DARDS is presented in a paper by Clarity, which includes a description of the UNF-ST&DARDS system. Proof-of-principle analyses were performed in the summer of 2019 for MPC-32 dual purpose canisters (DPCs) containing pressurized water reactor (PWR) fuel assemblies. Summaries of these results are presented in this and a companion paper for this conference. The current paper describes the TSUNAMI-IP calculations performed to select applicable experiments for validation of 11 MPC-32 DPCs. The companion paper discusses the TSUNAMI-3D calculations used to generate sensitivity data to support the experiment selections discussed here. Experiment selection is based on the sensitivity/uncertainty (S/U) methods used to validate criticality safety calculations of as-loaded DPCs containing pressurized water reactor (PWR) spent nuclear fuel (SNF). This process has been demonstrated and is summarized in this paper. The approach is similar to that used in NUREG/CR-7109, which provides an approach for validation of PWR burnup credit (BUC), including major and minor actinides and major fission products. The premise of S/U-based validation is that applicable experiments—those having a similar bias to a given application system—will have similar sensitivities for each isotope and reaction in the two systems. It is assumed that cross sections with larger uncertainties are more likely to contain data errors which contribute to the bias. The integral index c k thus propagates the system sensitivities with the nuclear covariance data to calculate a correlation coefficient representing the similarity of the two systems. In this work, a c k value of 0.8 or higher is interpreted as identifying an experiment with sufficient similarity for use in validation. This paper presents a brief summary of the characteristics of the 11 MPC-32 DPCs used in the proof of-principle analysis for as-loaded criticality safety calculation validation and an overview of the critical experiment suite with which each of these DPC models was compared. A summary and discussion of c k results is also presented, followed by conclusions and a discussion of future work to be performed for validation of UNF ST&DARDS as-loaded criticality safety calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

DEMO-FTES: Development, Monitoring, and Control of Fracture Thermal Energy Storage in Crystalline Rock Formations (CRADA Final Report)

The DEMO-FTES project investigated the feasibility of Fracture Thermal Energy Storage (FTES) as a seasonal energy storage solution in crystalline rock formations. FTES leverages hydraulically induced fractures to exchange heat between circulating fluids and the surrounding rock mass, enabling long-term thermal energy retention due to the high specific heat and low thermal conductivity of rock. This approach has the potential to reduce heating and cooling energy demands and enhance building energy resilience. The project combined dimensional analysis, numerical modeling, laboratory experiments, and meso-scale field tests to evaluate FTES performance and advance its technology readiness level from 3 to 5. Scaling analysis identified key dimensionless parameters governing heat transfer and fluid flow, ensuring laboratory and field tests were representative of larger-scale systems. Numerical simulations using TOUGH and iTOUGH2 frameworks supported experiment design and interpretation, modeling fracture geometry, thermal-hydraulic behavior, and thermo-mechanical coupling. Laboratory tests at EPFL involved creating single and multiple fractures in 25 cm cubic samples of Gabbro and Granite under true triaxial stress.

25 ENERGY STORAGE↗

DOE OSTI2023

Geogenic, Anthropogenic, and Authigenic Minerals Hosting Arsenic and Antimony in Yellowknife Bay Sediments

Abstract Yellowknife Bay (Great Slave Lake, Northwest Territories, Canada) is a water body valued by surrounding communities for its subsistence, recreational, and cultural use. Located directly downstream of the former Giant Mine and Con Mine, Yellowknife Bay has received inputs from mine waste streams enriched in arsenic (As), antimony (Sb), and metals since the late 1930s. Lake sediments in Yellowknife Bay provide a record of metal(loid) contamination from aerially deposited roaster stack emissions, mine effluent, and Giant Mine tailings. A sediment sampling program was conducted in Yellowknife Bay to characterize As and Sb mineralogy using scanning electron microscopy-mineral liberation analysis. Mineralogical analysis of As- and Sb-hosted minerals in nine sediment cores suggests that arsenic trioxide (As2O3), originally deposited during the period of peak-mining emissions, has since been transformed into authigenic sulfides (interpreted to be realgar) down core from peak-mining emissions. Arsenic has also been attenuated by iron (Fe)-oxyhydroxides and roaster-generated iron oxides up-core from peak-mining emissions, near the sediment–water interface. The Sb-bearing minerals appear to be stable in Yellowknife Bay sediments, with no conclusive evidence of post-depositional mobility having been identified. The observed prevalence of arsenic trioxide in surface sediments proximal to Giant Mine suggests that As and Sb contamination is ongoing, likely from terrestrial weathering of contaminated soils and shoreline outcrops. Arsenic-bearing oxide minerals prevalent in surface sediments may become unstable should redox conditions in the hypolimnion change; prolonged anoxia could destabilize the As hosting minerals and release As to bottom waters. Therefore, long-term monitoring of the water column, including hypolimnion conditions, in Yellowknife Bay is recommended.

Mineralogy↗

DOE OSTI2022

Technical and Economic Evaluation of the First Ever Polymer Flood Field Pilot to Enhance the Recovery of Heavy Oils on Alaska's North Slope via Machine Assisted History Matching

Polymer flooding has become globally established as a potential enhanced oil recovery method for heavy oils. To determine whether this technology may be useful in developing the substantial heavy oil resources on the Alaska North Slope, a polymer flood field pilot commenced at the Milne Point Unit in August 2018. This study seeks to evaluate the results of the field pilot on a technical and economic basis. A reservoir simulation model is constructed and calibrated to predict the oil recovery performance of the pilot through machine-assisted reservoir simulation techniques. To replicate the early water breakthrough observed during waterflooding, transmissibility contrasts are introduced into the simulation model, forcing viscous fingering effects. In the ensuing polymer flood, these transmissibility contrasts are reduced to replicate the restoration of injection conformance during polymer flooding. Transmissibility contrasts are later reinstated to replicate fracture overextension interpreted in one of the producing wells. The calibrated simulation models produced at each stage of the history matching process are used to forecast oil recovery. These forecasts are used as input for economic analysis, incremental to waterflooding expectations. The simulation forecasts indicate that polymer flooding significantly increases the heavy oil production for this field pilot compared to waterflooding alone, yielding attractive project economics. However, meaningful variations between simulation scenarios demonstrate that a simulation model is only valid for prediction if flow behavior in the reservoir remains consistent with that observed during the history matched period. Critically, this means that a simulation model calibrated for waterflooding may not fully capture the technical and economic benefits of an enhanced oil recovery process such as polymer flooding. Subsequently, the simulation model and economic model are used in conjunction to conduct a sensitivity analysis for polymer flood design parameters, from which recommendations are provided for both the continued operation of the current field pilot and future polymer flood designs. The results demonstrate that a higher polymer concentration can be injected due to the development of fractures in the reservoir. The throughput rate should remain high without exceeding operating constraints. A calculated point-forward polymer utilization parameter demonstrates the decreasing efficiency of the polymer flood at later times in the pattern life. Future projects will benefit from starting polymer injection earlier in the pattern life. A pattern with tighter horizontal well spacing will observe a greater incremental benefit from polymer flooding.

Keith, Cody↗

DOE OSTI2023

Experimental Observations of the Topology of Convolutional Neural Network Activations

Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of parameters associated with a series of transformations defined by the model architecture resulting in high-dimensional, difficult to interpret internal representations of input data. As DNNs become more ubiquitous across multiple sectors of our society, there is increasing recognition that mathematical methods are needed to aid analysts, researchers, and practitioners in understanding and interpreting how these models' internal representations relate to the final classification. In this paper we apply cutting edge techniques from TDA with the goal of gaining insight towards interpretability of convolutional neural networks used for image classification. We use two common TDA approaches to explore several methods for modeling hidden layer activations as high-dimensional point clouds, and provide experimental evidence that these point clouds capture valuable structural information about the model's process. First, we demonstrate that a distance metric based on persistent homology can be used to quantify meaningful differences between layers and discuss these distances in the broader context of existing representational similarity metrics for neural network interpretability. Second, we show that a mapper graph can provide semantic insight as to how these models organize hierarchical class knowledge at each layer. These observations demonstrate that TDA is a useful tool to help deep learning practitioners unlock the hidden structures of their models.

topological data analysis, deep learning↗

DOE OSTI2020

Comparison of equilibrium climate sensitivity estimates from slab ocean, 150-year, and longer simulations

We compare equilibrium climate sensitivity (ECS) estimates from pairs of long (= 800-year) control and abruptly quadrupled CO2 simulations with shorter (150, 300 year) coupled atmosphere-ocean simulations and Slab Ocean Models (SOM). Consistent with previous work, ECS estimates from shorter coupled simulations based on annual averages for years 1-150 underestimate those from SOM (-8% ± 13%) and long (-14% ± 8%) simulations. Analysis of only years 21-150 improved agreement with SOM (-2% ± 14%) and long (-8% ± 10%) estimates. Use of pentadal averages for years 51-150 results in improved agreement with long simulations (-4% ± 11%). While ECS estimates from current generation US models based on SOM and coupled annual averages of years 1-150 range from 2.6°C to 5.3°C, estimates based longer simulations of the same models range from 3.2°C to 7.0°C. Such variations between methods argues for caution in comparison and interpretation of ECS estimates across models.

Dunne, John P.↗

DOE OSTI2021

Real time evolution for ultracompact Hamiltonian eigenstates on quantum hardware

In this work we present a detailed analysis of variational quantum phase estimation (VQPE), a method based on real-time evolution for ground and excited state estimation on near-term hardware. We derive the theoretical ground on which the approach stands, and demonstrate that it provides one of the most compact variational expansions to date for solving strongly correlated Hamiltonians. At the center of VQPE lies a set of equations, with a simple geometrical interpretation, which provides conditions for the time evolution grid in order to decouple eigenstates out of the set of time evolved expansion states, and connects the method to the classical filter diagonalization algorithm. Further, we introduce what we call the unitary formulation of VQPE, in which the number of matrix elements that need to be measured scales linearly with the number of expansion states, and we provide an analysis of the effects of noise which substantially improves previous considerations. The unitary formulation allows for a direct comparison to iterative phase estimation. Our results mark VQPE as both a natural and highly efficient quantum algorithm for ground and excited state calculations of general many-body systems. We demonstrate a hardware implementation of VQPE for the transverse field Ising model. Further, we illustrate its power on a paradigmatic example of strong correlation (Cr2 in the SVP basis set), and show that it is possible to reach chemical accuracy with as few as ~50 timesteps.

Klymko, Katherine↗

DOE OSTI2023

Using deep machine learning to interpret proton radiography data from a pulsed power experiment

Deep machine learning is used to analyze a proton radiograph from a tin pulsed power experiment and determine density values for each pixel in the image. Two promising convolutional neural network architectures that have proven to be effective for image analysis in other applications are applied to analyze a proton radiograph and find density values. The process of creating a suitable training dataset is described, involving the Lagrangian hydrodynamic model used for simulations of the experiment, the proton radiography forward model to make synthetic images for training, and the manner in which data augmentation is used to expand the resulting image dataset. It is shown that machine learning not only produces a reasonable density field but is also able to predict features in the density field that are suggested by the proton radiograph but not captured by simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Effect of inoculation with prion dilutions within the dynamic range of ELISA absorbance on prion incubation period

This study examines the effect of various infectious prion titers within the dynamic range as measured by ELISA on incubation period. We inoculated ovinized transgenic mice with seven decreasing dilutions of a fast-incubating scrapie strain. The highest inoculum group was a 20% w/v brain homogenate from a sheep with scrapie. The subsequent six inoculum dilutions ranged from the highest ELISA optical density reading of 4.000 to a dilution where scrapie prions were not detectable by ELISA. Multiple comparison analysis demonstrated variation in the incubation periods between some inoculum groups. Incubation periods were similar between inoculum groups unless their optical density differed by more than ≈2 units of absorbance. These data will inform the interpretation of future studies that compare incubation periods in experimentally inoculated animals for TSE research.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Advances in Multimodal Characterization of Structural Materials

The myriad detectors and instruments now available for materials characterization provide researchers with an ever-growing suite of tools to probe material behavior. Progress in the development of instrumentation and workflows that enable the collection, and leverage the potential, of various data modalities have provided novel insights into material behavior. Using data across multiple length scales, or performing complementary analyses of in situ and ex situ data, can help reveal a more complete picture of dynamic processes or material structure. However, the accurate combination, or fusion, of these disparate data modalities presents new challenges. Differences in resolution, as well as the varying length scales at which physical phenomena are exploited to generate these data, necessitate novel approaches to accurately interpret and combine these data. Furthermore, the papers within this special topic focus on the collection and fusion of multimodal data to better understand structural materials. From new frameworks and workflows for data segmentation and analysis, process monitoring, enhancing simulations, or interrogating mechanical response, these papers reveal the potential benefits of utilizing multimodal data.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Deep desert aquifers as an archive for Mid- to Late Pleistocene hydroclimate: An example from the southeastern Mediterranean

Many efforts have been made to illuminate the nature of past hydroclimates in semi-arid and arid regions, where current and future shifts in water availability have enormous consequences on human subsistence. Deep desert aquifers, where groundwater is stored for prolonged periods, might serve as a direct record of major paleo-recharge events. To date, groundwater-based paleoclimate reconstructions have mainly focused on a relatively narrow timescale (up to ∼40 kyr), limited by the relatively short half-life of the widely used radiocarbon (5.73 kyr). Here we demonstrate the usage of deep regional aquifers in the arid southeastern Mediterranean as a hydroclimate archive for earlier Mid-to-Late Pleistocene epochs. State-of-the-art dating tools, primarily the 81 Kr radioisotope (t 1/2 = 229 kyr), were combined with other atmosphere-derived tracers to illuminate the impact of four distinguishable wetter episodes over the past 400 kyr, with differences in climatic conditions and paleo-recharge locations. Variations in stable water isotope composition suggest moisture transport from more proximal (Mediterranean) and distal (Atlantic) sources to different parts of the region at distinct times. Large variability in the computed noble gas-based recharge temperature (NGT), ranging ~15–30 °C, cannot be explained by climate variations solely, and points to different recharge pathways, including geothermal heating in the deep unsaturated zone and recharge from high-elevation (colder) regions. The obtained groundwater record complements and enhances the interpretation of other terrestrial archives in the arid region, including a contribution of valuable information regarding the moisture source origin as reflected in the deuterium-excess values, which is unattainable from the common practice analysis of calcitic cave deposits. We conclude that similar applications in other deep (hundred-m-order) regional groundwater systems (e.g., the Sahara desert aquifers) can significantly advance our understanding of long-term (up to 1 Myr) paleo-hydroclimate in arid regions, including places where no terrestrial remnants, such as cave, lake, and spring sediments, are available.

Atom Trap Trace Analysis↗