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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Supplementary Data for "Evaluation of the Economic Implications of Varied Pressure Drawdown Strategies Generated Using a Real-time, Rapid Predictive, Multi-fidelity Model for Unconventional Oil and Gas Wells" by Bello, K., Vikara, D., Sheriff, A., Viswanathan, H., Carr, T., Sweeney, M., O'Malley, D., Marquis, M., Vactor, R.T., and Cunha, L.

The Bello et al. study evaluates the impact of contrasting pressure drawdown on gas productivity and the resulting economics of a well in the Marcellus Shale of the Appalachian Basin. This research applies a techno-economic analysis approach to help identify potential ways pressure management strategies can be used to improve cumulative recovery of hydraulically fractured horizontal wells while maintaining project profitability. Gas production forecast outlook scenarios of the Marcellus Shale Energy and Environment Laboratory Laboratory's MIP-3H well were generated under varying pressure drawdowns using two approaches: 1) a novel physics-informed machine learning (PIML) workflow and 2) via traditional reservoir simulation in Computer Modeling Group’s (CMG) GEM Compositional & Unconventional Simulator. Cash flow and other economic metrics of interest were compiled on the production outlook using the U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) Unconventional Shale Well Economic Model (UShWEM).The sheets within this Microsoft ExcelTM workbook provide the economic metric outputs for the baseline condition and the one-at-a-time (OAT) sensitivity analysis of UShWEM's input parameters for each of the production scenarios evaluated.

Fracture Network Model↗
DOE OSTI2022

Building a better framework for evaluating human well-being impacts in global change analysis: The example of energy security

Human well-being can be greatly impacted by the global environmental and socio-economic change captured in Integrated Models of Global Change (IMGCs). Though most IMGCs address some aspects of well-being, their underlying modeling approach and ‘philosophy’ differ widely, and some key elements – like energy security – are omitted. In this report, we describe a project in which we set out to a create a framework through which the well-being dimensions of the household are connected to key drivers of socio-economic and environmental change – and how the needed metrics, data and modeling methods can be brought to bear. We focus on the well-being dimensions of energy, and lay out the necessary elements to capturing household energy security – using household energy burden as the relevant metric. We begin by showing the conceptual linkage of energy burden to environmental drivers like temperature change, using a simple and straightforward conceptual framework. We then go further to use the example of GCAM-USA to show how some key analytical features of the model can provide insight into how energy security across different groups can change along alternative pathways to sustainability. We compare our preliminary assessment of household energy burden to existing data and suggest further steps to improve and refine this analysis in future research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Unconventional Wells Interference: Supervised Machine Learning for Detecting Fracture Hits

The primary objective of the study was development of a machine learning (ML)-based workflow for fracture hit (“frac hit”) detection and monitoring using shale oil-field data such as drilling surveys, production history (oil and produced water), pressure, and fracking start time and duration records. The ML method takes advantage of long short-term memory (LSTM) and multilayer perceptron (MLP) neural networks to identify the frac hits due to hydraulic communication between the fracking child well(s) and the producing parent well(s) within the same pad (intra-pad interaction) and/or on different pads (inter-pad interaction). It utilizes time series of pressure and production data from within a pad and from adjacent pads. The workflow can capture time variable features of frac hits when the model architecture is deep and wide enough, with enough trainable parameters for deep learning and feature extraction, as demonstrated in this paper by using training and testing subsets of the field data from selected neighboring pads with over a couple of hundred wells. The study was focused on frac-hit interaction among paired wells and demonstrated that the ML model, once trained, can predict the frac-hit probability.

58 GEOSCIENCES↗
DOE OSTI2020

Effect of Computational Schemes on Coupled Flow and Geo-Mechanical Modeling of CO 2 Leakage through a Compromised Well

Carbon capture, utilization, and storage (CCUS) describes a set of technically viable processes to separate carbon dioxide (CO 2 ) from industrial byproduct streams and inject it into deep geologic formations for long-term storage. Legacy wells located within the spatial domain of new injection and production activities represent potential pathways for fluids (i.e., CO 2 and aqueous phase) to leak through compromised components (e.g., through fractures or micro-annulus pathways). The finite element (FE) method is a well-established numerical approach to simulate the coupling between multi-phase fluid flow and solid phase deformation interactions that occur in a compromised well system. We assumed the spatial domain consists of a three-phases system: a solid, liquid, and gas phase. For flow in the two fluids phases, we considered two sets of primary variables: the first considering capillary pressure and gas pressure (PP) scheme, and the second considering liquid pressure and gas saturation (PS) scheme. Fluid phases were coupled with the solid phase using the full coupling (i.e., monolithic coupling) and iterative coupling (i.e., sequential coupling) approaches. The challenge of achieving numerical stability in the coupled formulation in heterogeneous media was addressed using the mass lumping and the upwinding techniques. Numerical results were compared with three benchmark problems to assess the performance of coupled FE solutions: 1D Terzaghi’s consolidation, Liakopoulos experiments, and the Kueper and Frind experiments. We found good agreement between our results and the three benchmark problems. For the Kueper and Frind test, the PP scheme successfully captured the observed experimental response of the non-aqueous phase infiltration, in contrast to the PS scheme. These exercises demonstrate the importance of fluid phase primary variable selection for heterogeneous porous media. We then applied the developed model to the hypothetical case of leakage along a compromised well representing a heterogeneous media. Considering the mass lumping and the upwinding techniques, both the monotonic and the sequential coupling provided identical results, but mass lumping was needed to avoid numerical instabilities in the sequential coupling. Additionally, in the monolithic coupling, the magnitude of primary variables in the coupled solution without mass lumping and the upwinding is higher, which is essential for the risk-based analyses.

deformation flow↗
DOE OSTI2023

Subsurface Characterization for Evaluating Geothermal Resource Potential from Existing Oil and Gas Wells in Tuttle, Oklahoma: Preprint

Oil and gas (O&G) wells often encounter co-produced hot water, possibly suitable for geothermal direct-use applications. The City of Tuttle is located on the eastern part of the Anadarko sedimentary basin in Oklahoma with high heat-in-place potential and recovery capability at depth. This study aims at demonstrating the potential of geothermal energy production for direct-use applications in two public schools and 250 nearby houses in Tuttle via repurposing existing O&G wells. In this scope, geochemistry, geology, and borehole log data were collected and incorporated into a 3D conceptual subsurface model. A digital elevation model (DEM) was used to represent the study area topography with four O&G wells. In addition, hydrogeochemical characteristics of the geothermal fluid and scaling potential were analyzed using ternary diagrams and chemical ratios to develop mixing models. The subsurface geology model indicated that the study area primarily consists of Permian to Mississippian Sandstone and Limestone formations, implying a porosity ranging between 12% and 22%, and a permeability up to 3.90E-14 m2 in certain reservoir levels. The reservoir temperature is expected to be ranging between 80 degrees C to 95 degrees C around 3 km depth with an average temperature gradient of 22.8 degrees C/km. Chemical geothermometers also estimated the reservoir temperature as 90 degrees C. Findings of the chemical model demonstrated that the geothermal fluid is Sodium-Potassium-Chloride-Sulfate type and possibly mixed with shallow groundwater resulting in higher Ca and Mg concentrations and lower Na/K ratio implying lower calcite scaling. These results comprehensively characterize the potential of geothermal resources in the study area and imply that geothermal energy production by repurposing existing O&G wells is suitable for low-temperature direct-use applications.

GEOTHERMAL ENERGY↗
DOE OSTI2023

Subsurface Characterization for Evaluating Geothermal Resource Potential from Existing Oil and Gas Wells in Tuttle, Oklahoma

Oil and gas (O&G) wells often encounter co-produced hot water, possibly suitable for geothermal direct-use applications. The City of Tuttle is located on the eastern part of the Anadarko sedimentary basin in Oklahoma with high heat-in-place potential and recovery capability at depth. This study aims at demonstrating the potential of geothermal energy production for direct-use applications in two public schools and 250 nearby houses in Tuttle via repurposing existing O&G wells. In this scope, geochemistry, geology, and borehole log data were collected and incorporated into a 3D conceptual subsurface model. A digital elevation model (DEM) was used to represent the study area topography with four O&G wells. In addition, hydrogeochemical characteristics of the geothermal fluid and scaling potential were analyzed using ternary diagrams and chemical ratios to develop mixing models. The subsurface geology model indicated that the study area primarily consists of Permian to Mississippian Sandstone and Limestone formations, implying a porosity ranging between 12% and 22%, and a permeability up to 3.90E-14 m2 in certain reservoir levels. The reservoir temperature is expected to be ranging between 80 degrees C to 95 degrees C around 3 km depth with an average temperature gradient of 22.8 degrees C/km. Chemical geothermometers also estimated the reservoir temperature as 90 degrees C. Findings of the chemical model demonstrated that the geothermal fluid is Sodium-Potassium-Chloride-Sulfate type and possibly mixed with shallow groundwater resulting in higher Ca and Mg concentrations and lower Na/K ratio implying lower calcite scaling. These results comprehensively characterize the potential of geothermal resources in the study area and imply that geothermal energy production by repurposing existing O&G wells is suitable for low-temperature direct-use applications.

gas wells↗
DOE OSTI2025

Machine Learning for Well Log Analysis in Uranium Mining

This project explores the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to automate well log analysis for uranium mining. Geophysical log data—spontaneous potential, resistivity, and gamma ray—were used to classify lithology, correlate well logs and identify roll front zonation patterns, which are critical for locating uranium ore bodies. Supervised ML algorithms such as eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Random Forest were trained to classify lithology with high accuracy. Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks were also used for role front zone identification. Moreover, a Fast Dynamic Time Warping (FastDTW) algorithm was employed for well log correlation. Additionally, sample lag was addressed using dynamic programming. Results demonstrate the potential of AI and ML to streamline well log analysis and enhance uranium exploration workflows.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Utah FORGE: Reports on Northwestern Nevada Well Doublet Drilling and Testing by Fervo Energy

These reports review Fervo Energy's construction of a commercial enhanced geothermal system (EGS). Fervo has qualified full functionality of the system through production testing at commercially relevant operating conditions. The project site is located in a nearfield setting adjacent to an operating geothermal power station in north-central Nevada and is designed to deliver an uplift in high-temperature geothermal flow rates to increase the power capacity at the facility. The project involved drilling a first-of-a-kind EGS horizontal doublet well system consisting of an injection and production well pair within a high-temperature hard-rock geothermal formation. The lithology of the target reservoir is characterized as a mixed metasedimentary and igneous formation, comprised of phyllite, quartzite, diorite, and granodiorite, representative of the geology across the most prospective geothermal areas throughout the western US. This work included a 16-stage plug-and-perforate stimulation treatment which was the first of its kind in a high-temperature mixed metasedimentary and granitic formation in a fully horizontal doublet geothermal well.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Evaluation of the economic implications of varied pressure drawdown strategies generated using a real-time, rapid predictive, multi-fidelity model for unconventional oil and gas wells

Experience has suggested that pressure maintenance in hydraulically fractured reservoirs via lower, more sustained production drawdowns may offer improved cumulative recovery and overall resource extraction efficiency compared to more rapid drawdown approaches aimed at generating high initial production. However, given the inherent variability of oil and natural gas markets, operators pursue production strategies that maximize profitability over resource extraction efficiency. This study focuses on evaluating the implications of contrasting pressure drawdown strategies on the long-term production and resulting economics for a real, producing unconventional gas well in the Marcellus Shale of the Appalachian Basin using a techno-economic analysis approach. Our research combines elements of well-specific horizontal well design, production forecasting, equipment sizing and capital cost estimation, operating cost estimation, and revenue and tax calculations. Gas production forecast outlook scenarios were generated under varying pressure drawdowns using two approaches: 1) a novel physics-informed machine learning workflow and 2) traditional reservoir simulation. A discounted cash flow model was used to evaluate the resulting economic implications for each drawdown scenario—generating output for exploring the coupled effect of factors like the timing and volume of gas production, prevailing economic and market conditions for natural gas, and overall estimated ultimate recovery on profitability metrics such as internal rate of return and net present value. Results show that there is potential to maximize the cumulative gas produced in the specific case study well by employing a lower pressure drawdown. Conversely, the greatest profitability is achieved using rapid drawdown as signified by a small, specific subset of our outlook scenarios. On an averaging basis, we find that the combinations of highest cumulative producing and most profitable scenarios occur under lower drawdowns with long (>40 years) producing timeframes, but require higher relative gas price and lower discounting considerations. Further, the machine learning predictive outlooking capability proved effective for enabling rapid generation of a multitude of scenario forecasts. As a result, a variety of prominent example cases could be generated to strike the balance of greater productivity and economic return given their associated producing features and economic conditions when compared to similar producing scenarios—critical insight that offers improved decision support for unconventional oil and gas operations.

42 ENGINEERING↗
DOE OSTI2023

Rigorous Oxidation State Assignments for Supported Ga-Containing Catalysts Using Theory-Informed X-ray Absorption Spectroscopy Signatures from Well-Defined Ga(I) and Ga(III) Compounds

Gallium-based heterogeneous catalysts originally developed for commercial use in propane dehydroaromatization have been explored extensively as potential replacements for Pt- and Cr-based catalysts used in propane dehydrogenation for on-demand propylene production. In a large number of experimental and theoretical studies, active sites with a variety of Ga nuclearities, coordination environments, and oxidation states have been proposed. Isolated Ga(I) ions are often invoked, despite the scarcity of well-defined molecular species and their well-documented instability. In this study, we investigate the appearance of a high-intensity, low-energy white line at the Ga K-edge upon reduction of Ga/HZSM-5 by H 2 at a temperature of ca. 500 °C, accompanied by a dramatic reduction in the extended X-ray absorption fine structure (EXAFS) intensity. In contrast, Ga/γ-Al 2 O 3 does not show such behavior. In order to lay a rigorous foundation for characterizing these types of systems and to establish experimental signatures for the elusive Ga(I) oxidation state, we recorded Ga K-edge X-ray absorption spectra [including high-energy-resolution fluorescence detection-X-ray absorption near-edge spectroscopy (HERFD-XANES)] for several well-defined molecular and crystalline Ga(I) compounds. XANES is essential to establishing the presence of Ga(I), despite the overlap in edge energies with organoGa(III) compounds, because Ga(I)-containing oxide materials show very weak EXAFS scattering. Compared to the XANES of trigonal Ga(III)-containing materials, Ga(I) spectra display a significantly more intense white line feature. Theoretical simulations agree well with this experimental observation and reveal that the strong XANES intensity originates from the superposition of transitions to several empty, nearly degenerate p-like states. Finally, these signatures provide compelling evidence for assigning the intense white line and dramatic loss of EXAFS intensity in Ga/HZSM-5 to the near-quantitative reduction of Ga(III) to Ga(I), while the weaker white line and conventional EXAFS signal of Ga/γ-Al 2 O 3 point to, at most, a minor fraction of Ga(I) sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Sub-single exciton optical gain threshold in colloidal semiconductor quantum wells with gradient alloy shelling

Colloidal semiconductor quantum wells have emerged as a promising material platform for use in solution-processable lasers. However, applications relying on their optical gain suffer from nonradiative Auger decay due to multi-excitonic nature of light amplification in II-VI semiconductor nanocrystals. Here, we show sub-single exciton level of optical gain threshold in specially engineered CdSe/CdS@CdZnS core/crown@gradient-alloyed shell quantum wells. This sub-single exciton ensemble-averaged gain threshold of (Ng)≈ 0.84 (per particle) resulting from impeded Auger recombination, along with a large absorption cross-section of quantum wells, enables us to observe the amplified spontaneous emission starting at an ultralow pump fluence of ~ 800 nJ cm –2 , at least three-folds better than previously reported values among all colloidal nanocrystals. Finally, using these gradient shelled quantum wells, we demonstrate a vertical cavity surface-emitting laser operating at a low lasing threshold of 7.5 μJ cm –2 . These results represent a significant step towards the realization of solution-processable electrically-driven colloidal lasers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Driving ultrafast spin and energy modulation in quantum well states via photo-induced electric fields

Abstract The future of modern optoelectronics and spintronic devices relies on our ability to control the spin and charge degrees of freedom at ultrafast timescales. Rashba spin-split quantum well states, 2D states that develop at the surface of strong spin-orbit coupling materials, are ideal given the tunability of their energy and spin states. So far, however, most studies have only demonstrated such control in a static way. In this study, we demonstrate control of the spin and energy degrees of freedom of surface quantum well states on Bi 2 Se 3 at picosecond timescales. By means of a focused laser pulse, we modulate the band-bending, producing picosecond time-varying electric fields at the material’s surface, thereby reversibly modulating the quantum well spectrum and Rashba effect. Moreover, we uncover a dynamic quasi-Fermi level, dependent on the Lifshitz transition of the second quantum well band bottom. These results open a pathway for light-driven spintronic devices with ultrafast switching of electronic phases, and offer the interesting prospect to extend this ultrafast photo-gating technique to a broader host of 2D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electron mobility enhancement by electric field engineering of AlN/GaN/AlN quantum-well HEMTs on single-crystal AlN substrates

To enhance the electron mobility in quantum-well high-electron-mobility transistors (QW HEMTs), we investigate the transport properties in AlN/GaN/AlN heterostructures on Al-polar single-crystal AlN substrates. Theoretical modeling combined with experiment shows that interface roughness scattering due to high electric field in the quantum well limits mobility. Increasing the width of the quantum well to its relaxed form reduces the internal electric field and scattering, resulting in a binary QW HEMT with a high two-dimensional electron gas (2DEG) density of 3.68×1013 cm–2, a mobility of 823 cm2/Vs, and a record-low room temperature (RT) sheet resistance of 206 Ω/□. Further reduction of the quantum well electric field yields a 2DEG density of 2.53×1013 cm–2 and RT mobility > 1000 cm2/V s. These findings will enable future developments in high-voltage and high-power microwave applications on the ultrawide bandgap AlN substrate platform.

Physics↗
DOE OSTI2020

Evaluation of temperature changes in a cell culture plate well with absorbing walls containing a 3D model of tumour spheroid under irradiation in the optical range

The temperature conditions for photodynamic therapy of the culture of tumour cells organised in 3D spheroids are studied. The spheroids are placed in the cell culture medium in the well of a special cell culture plate with absorbing walls. A mathematical model is presented that describes the temperature distribution in a well with a cell culture plate heated by optical radiation. It is shown that the temperature in the well volume is not uniformly distributed, and the temperature on the well surface can differ significantly from the temperature in its volume. (laser medicine)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Interplay of superconducting, metallic, and crystalline states of composite fermions at 𝜈 = $\frac{1}{6}$ in wide quantum wells

Evidence for developing fractional quantum Hall effect (FQHE) at filling fraction 𝜈 = 1/6 and 1/8 was recently reported in wide GaAs quantum wells [Wang et al., Phys. Rev. Lett. 134, 046502 (2025)]. In this article, we theoretically investigate the nature of the state at 𝜈 = 1/6 as a function of the quantum well width and the density by considering composite-fermion (CF) crystals, CF Fermi sea, and various kinds of paired CF states. The 𝑓-wave paired state has the lowest energy among the paired CF states. However, for parameters of interest, the energies of the CF crystal, the CF Fermi liquid, and the 𝑓-wave paired CF state are too close to distinguish. We, therefore, predict that 𝑖𝑓 the FQHE at 𝜈 = 1/6 is experimentally confirmed, this state would be an 𝑓-wave paired state of CFs, which can be verified by measurement of its thermal Hall conductance. Exact diagonalization studies on clean systems with up to eight electrons show that the ground states at 𝜈 = 𝑛/(6⁢𝑛 ± 1) are incompressible for all widths and densities we have considered, and are well described by the corresponding Laughlin and Jain states. We propose a phase diagram for large quantum well widths and densities in which at zero disorder, incompressible FQHE states are stabilized at 𝜈 = 𝑛/(6⁢𝑛 ± 1) and 𝜈 = 1/6, but in between these fillings the CF crystal is stabilized. We also present a qualitative discussion on the effects of disorder and propose a schematic phase diagram based on it. With disorder, which creates a spatial variation in the filling factor, two regimes are identified: (i) for small disorder, when the incompressible states percolate at the special fillings, FQHE with quantized Hall plateaus and vanishing longitudinal resistance should occur; and (ii) for larger disorder, when the CF crystal percolates, the longitudinal resistance rises with decreasing temperature but the domains of FQHE liquid produce minima at the special filling factors. Here, experiments are consistent with the latter scenario. We also mention a possible connection of the phase diagram presented here to a puzzling behavior observed for the fractional quantum anomalous Hall effect in pentalayer graphene.

Composite fermions↗
DOE OSTI2020

Quantum-well states in fractured crystals of the heavy-fermion material CeCoIn5

Quantum-well states appear in metallic thin films due to the confinement of the wave function by the film interfaces. Using angle-resolved photoemission spectroscopy, we unexpectedly observe quantum-well states in fractured single crystals of CeCoIn5. We confirm that confinement occurs by showing that these states’ binding energies are photon-energy independent and are well described with a phase accumulation model, commonly applied to quantum-well states in thin films. This indicates that atomically flat thin films can be formed by fracturing hard single crystals. For the two samples studied, our observations are explained by free-standing flakes with thicknesses of 206 and 101 Å. We extend our analysis to extract bulk properties of CeCoIn5. Specifically, we obtain the dispersion of a three-dimensional band near the zone center along in-plane and out-of-plane momenta. We establish part of its Fermi surface, which corresponds to a hole pocket centered at G. We also reveal a change of its dispersion with temperature, a signature that may be caused by the Kondo hybridization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Working principles of doping-well structures for high-mobility two-dimensional electron systems

Suppressing electron scattering is essential to achieve high-mobility two-dimensional electron systems (2DESs) that are clean enough to probe exotic interaction-driven phenomena. In heterostructures it is common practice to utilize modulation doping, where the ionized dopants are physically separated from the 2DES channel. The doping-well structure augments modulation doping by providing additional screening for all types of charged impurities in the vicinity of the 2DES, which is necessary to achieve record-breaking samples. Despite its prevalence in the design of ultrahigh-mobility 2DESs, the working principles of the doping-well structure have not been reported. As such, here we elaborate on the mechanics of electron transfer from doping wells to the 2DES, focusing on GaAs/AlGaAs samples grown by molecular beam epitaxy. Based on this understanding we demonstrate how structural parameters in the doping well can be varied to tune the properties of the 2DES.

36 MATERIALS SCIENCE↗