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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Efficient exascale discretizations: High-order finite element methods

Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating point operations to energy intensive data movement. One of the few viable approaches to achieve high efficiency in the area of PDE discretizations on unstructured grids is to use matrix-free/partially assembled high-order finite element methods, since these methods can increase the accuracy and/or lower the computational time due to reduced data motion. In this paper we provide an overview of the research and development activities in the Center for Efficient Exascale Discretizations (CEED), a co-design center in the Exascale Computing Project that is focused on the development of next-generation discretization software and algorithms to enable a wide range of finite element applications to run efficiently on future hardware. CEED is a research partnership involving more than 30 computational scientists from two US national labs and five universities, including members of the Nek5000, MFEM, MAGMA and PETSc projects. We discuss the CEED co-design activities based on targeted benchmarks, miniapps and discretization libraries and our work on performance optimizations for large-scale GPU architectures. We also provide a broad overview of research and development activities in areas such as unstructured adaptive mesh refinement algorithms, matrix-free linear solvers, high-order data visualization, and list examples of collaborations with several ECP and external applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Fully gauge-fixed SU(2) Hamiltonian for quantum simulations

Here, we demonstrate how to construct a fully gauge-fixed lattice Hamiltonian for a pure SU(2) gauge theory. Our work extends upon previous work, where a formulation of an SU(2) lattice gauge theory was developed that is efficient to simulate at all values of the gauge coupling. That formulation utilized maximal-tree gauge, where all local gauge symmetries are fixed and a residual global gauge symmetry remains. By using the geometric picture of an SU(2) lattice gauge theory as a system of rotating rods, we demonstrate how to fix the remaining global gauge symmetry. In particular, the quantum numbers associated with total charge can be isolated by rotating between the lab and body frames using the three Euler angles. The Hilbert space in this new “sequestered” basis partitions cleanly into sectors with differing total angular momentum, which makes gauge-fixing to a particular total charge sector trivial, particularly for the charge-zero sector. In addition to this sequestered basis inheriting the property of being efficient at all values of the coupling, we show that, despite the global nature of the final gauge-fixing procedure, this Hamiltonian can be simulated using quantum resources scaling only polynomially with the lattice volume.

Lattice gauge theory↗
DOE OSTI2014

Exercises in high-dimensional sampling: maximal poisson-disk sampling and k -d darts

In this paper, we review our recent progress on efficient algorithms for generating well-spaced samples of high dimensional data, and for exploring and characterizing these data, the underlying domain, and functions over the domain. To our knowledge, these techniques have not yet been applied to computational topology, but the possible connections are worth considering. In particular, computational topology problems often have difficulty in scaling efficiently, and these sampling techniques have the potential to drastically reduce the size of the data over which these computational topology algorithms must operate. Lastly, we summarize the definition of these sample distributions; algorithms for generating them in low, moderate, and high dimensions; and applications in mesh generation, rendering, motion planning and simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Reinforcement Learning for Distance Maximization in Energy-Constrained Robots

Our goal is to teach a robot to walk in an energy efficient way. Inspired by nature [1], we create a reinforcement learning method that balances distance traveled and energy consumption, which we call “utility.” Further, each step is symmetric to ensure equal strides while walking straight. We achieve our goal by rewarding decisions that lead to the best utility over several training iterations.

Pereira, Luiz Manella↗
DOE OSTI2025

EMPDF : inferring the Milky Way mass with data-driven distribution function in phase space

We introduce the emPDF (empirical distribution function), a novel dynamical modelling method that infers the gravitational potential from kinematic tracers with optimal statistical efficiency under the minimal assumption of steady state. emPDF determines the best-fitting potential by maximizing the similarity between instantaneous kinematics and the time-averaged phase-space distribution function (DF), which is empirically constructed from observation upon the theoretical foundation of oPDF (Han et al. 2016). This approach eliminates the need for presumed functional forms of DFs or orbit libraries required by conventional DF- or orbit-based methods. emPDF stands out for its flexibility, efficiency, and capability in handling observational effects, making it preferable to the popular Jeans equation or other minimal assumption methods, especially for the Milky Way (MW) outer halo where tracers often have limited sample size and poor data quality. We apply emPDF to infer the MW mass profile using Gaia DR3 data of satellite galaxies and globular clusters, obtaining enclosed masses of M (,r) = 26±8, 46±8, 90±13⁠, and 149±40 x 10 10 M ⊙ at r = 30, 50, 100⁠, and 200 kpc, respectively. These are consistent with the updated constraints from simulation-informed DF fitting (Li et al. 2020). While the simulation-informed DF offers superior precision owing to the additional information extracted from simulations, emPDF is independent of such supplementary knowledge and applicable to general tracer populations. emPDF is currently implemented for tracers with complete 6D kinematics within spherical potentials, but it can potentially be extended to address more general problems.

Astrophysics of Galaxies (astro-ph.GA)↗
DOE OSTI2024

OpenStudio Development, Maintenance, and Support

BEM is a key decision support tool for energy efficiency, demand flexibility, and electrification at the building and building stock levels. The OpenStudio SDK maximizes the value of BEM by enhancing the productivity, consistency, and transparency with which it is applied. OpenStudio enables BEM experts to encapsulate domain and process knowledge in such a way that makes it usable by a range of stakeholders.

BEM↗
DOE OSTI2017

Conceptual design of a hybrid neutron-gamma detector for study of β-delayed neutrons at the RIB facility of RIKEN

Here, the conceptual design of the BRIKEN neutron detector at the radioactive ion beam factory (RIBF) of the RIKEN Nishina Center is reported. The BRIKEN setup is a complex system aimed at detecting heavy-ion implants, β particles, γ rays and β-delayed neutrons. The whole setup includes the Advanced Implantation Detection Array (AIDA), two HPGe Clover detectors and up to 166 3 He-filled counters embedded in a high-density polyethylene moderator. The design is quite complex due to the large number and different types of 3 He-tubes involved and the additional constraints introduced by the ancillary detectors for charged particles and γ rays. This article reports on a novel methodology developed for the conceptual design and optimisation of the 3 He-counter array, aiming for the best possible performance in terms of neutron detection. The algorithm is based on a geometric representation of two selected detector parameters of merit, namely, the average neutron detection efficiency and the efficiency flatness as a function of a reduced number of geometric variables. The response of the neutron detector is obtained from a systematic Monte Carlo simulation implemented in GEANT4. The robustness of the algorithm allowed us to design a versatile detection system, which operated in hybrid mode includes the full neutron counter and two clover detectors for high-precision gamma spectroscopy. In addition, the system can be reconfigured into a compact mode by removing the clover detectors and re-arranging the 3 He tubes in order to maximize the neutron detection performance. Both operation modes shows a rather flat and high average efficiency. In summary, we have designed a system which shows an average efficiency for hybrid mode ( 3 He tubes + clovers) of 68.6% and 64% for neutron energies up to 1 and 5 MeV, respectively. For compact mode (only 3 He tubes), the average efficiency is 75.7% and 71% for neutron energies up to 1 and 5 MeV, respectively. The performance of the BRIKEN detection system has been also quantified by means of Monte Carlo simulations with different neutron energy distributions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

WO 3 /CuWO 4 Ratio Controls Open-Circuit Photovoltage and Photocurrent in Type II Heterojunction Solar Fuel Photoelectrodes

WO 3 /CuWO 4 photoelectrodes for the oxygen evolution reaction benefit from a type II heterojunction for charge separation. However, the impact of the WO 3 /CuWO 4 ratio on the photocurrent and the photovoltage is not clear. To probe the effect of composition, Cu x W 1-x O y thin films with variable W:Cu ratio were prepared on FTO by reactive magnetron co-sputtering of W and Cu, followed by air annealing at 500ºC. EDS, XRD, Rietveld refinement, and Raman spectroscopy confirm the presence of crystalline WO 3 and CuWO 4 in the W rich films and increasing amounts of amorphous copper oxides in the Cu rich films. Bandgaps were determined by optical absorption spectroscopy, surface photovoltage spectroscopy (SPS), and photoaction spectra and are found to decrease from 2.7 eV to 1.2 eV with increasing copper oxide content. SPS reveals n-type semiconductor photoanode behavior for WO 3 /CuWO 4 samples and p-type photocathode behavior for CuO x rich films. Photoelectrochemical experiments confirm stable water oxidation with Faraday efficiency near unity for all W rich films and photocurrents that are increasing with CuWO 4 content. Optimal performance is seen for WO 3 /CuWO 4 mixed phases containing 47-75 mass% CuWO 4 . These compositions maximize charge separation at the type II heterojunction interface between the two materials. Additionally, according to incident photon to current efficiency (IPCE) data, the WO 3 improves photon conversion below 350 nm, while CuWO 4 improves conversion at 450-525 nm. Overall, this work shows for the first time how the WO 3 /CuWO 4 ratio controls the photovoltage and the photocurrent in type II heterojunction solar fuel photoelectrodes, and how copper oxides in the copper rich films severely degrade the performance. Furthermore, these results are useful in the context of bulk-heterojunction electrodes for the conversion of solar energy into fuels.

CuWO4↗
NASA NTRS2000

Interference Lattice-based Loop Nest Tilings for Stencil Computations

A common method for improving performance of stencil operations on structured multi-dimensional discretization grids is loop tiling. Tile shapes and sizes are usually determined heuristically, based on the size of the primary data cache. We provide a lower bound on the numbers of cache misses that must be incurred by any tiling, and a close achievable bound using a particular tiling based on the grid interference lattice. The latter tiling is used to derive highly efficient loop orderings. The total number of cache misses of a code is the sum of (necessary) cold misses and misses caused by elements being dropped from the cache between successive loads (replacement misses). Maximizing temporal locality is equivalent to minimizing replacement misses. Temporal locality of loop nests implementing stencil operations is optimized by tilings that avoid data conflicts. We divide the loop nest iteration space into conflict-free tiles, derived from the cache miss equation. The tiling involves the definition of the grid interference lattice an equivalence class of grid points whose images in main memory map to the same location in the cache-and the construction of a special basis for the lattice. Conflicts only occur on the boundaries of the tiles, unless the tiles are too thin. We show that the surface area of the tiles is bounded for grids of any dimensionality, and for caches of any associativity, provided the eccentricity of the fundamental parallelepiped (the tile spanned by the basis) of the lattice is bounded. Eccentricity is determined by two factors, aspect ratio and skewness. The aspect ratio of the parallelepiped can be bounded by appropriate array padding. The skewness can be bounded by the choice of a proper basis. Combining these two strategies ensures that pathologically thin tiles are avoided. They do not, however, minimize replacement misses per se. The reason is that tile visitation order influences the number of data conflicts on the tile boundaries. If two adjacent tiles are visited successively, there will be no replacement misses on the shared boundary. The iteration space may be covered with pencils larger than the size of the cache while avoiding data conflicts if the pencils are traversed by a scanning-face method. Replacement misses are incurred only on the boundaries of the pencils, and the number of misses is minimized by maximizing the volume of the scanning face, not the volume of the tile. We present an algorithm for constructing the most efficient scanning face for a given grid and stencil operator. In two dimensions it is based on a continued fraction algorithm. In three dimensions it follows Voronoi's successive minima algorithm. We show experimental results of using the scanning face, and compare with canonical loop orderings.

VanderWijngaart, Rob F.↗
DOE OSTI2017

Facilitating CCS Business Planning by Extending the Functionality of the SimCCS Integrated System Model

The application of integrated system models for evaluating carbon capture and storage technology has expanded steadily over the past few years. To date, such models have focused largely on hypothetical scenarios of complex source-sink matching involving numerous large-scale CO 2 emitters, and high-volume, continuous reservoirs such as deep saline formations to function as geologic sinks for carbon storage. Though these models have provided unique insight on the potential costs and feasibility of deploying complex networks of integrated infrastructure, there remains a pressing need to translate such insight to the business community if this technology is to ever achieve a truly meaningful impact in greenhouse gas mitigation. Here, we present a new integrated system modelling tool termed SimCCUS aimed at providing crucial decision support for businesses by extending the functionality of a previously developed model called SimCCS. The primary innovation of the SimCCUS tool development is the incorporation of stacked geological reservoir systems with explicit consideration of processes and costs associated with the operation of multiple CO 2 utilization and storage targets from a single geographic location. In such locations provide significant efficiencies through economies of scale, effectively minimizing CO 2 storage costs while simultaneously maximizing revenue streams via the utilization of CO 2 as a commodity for enhanced hydrocarbon recovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Above-ground Antineutrino Detection for Nuclear Reactor Monitoring

Antineutrino monitoring of nuclear reactors has been demonstrated many times, however the technique has not as of yet been developed into a useful capability for treaty verification purposes. The most notable drawback is the current requirement that detectors be deployed underground, with at least several meters-water-equivalent of shielding from cosmic radiation. In addition, the deployment of liquid-based detector media presents a challenge in reactor facilities. We are currently developing a detector system that has the potential to operate above ground and circumvent deployment problems associated with a liquid detection media: the system is composed of segments of plastic scintillator surrounded by 6 LiF/ZnS:Ag. ZnS:Ag is a radio-luminescent phosphor used to detect the neutron capture products of lithium-6. Because of its long decay time compared to standard plastic scintillators, pulse-shape discrimination can be used to distinguish positron and neutron interactions resulting from the inverse beta decay (IBD) of antineutrinos within the detector volume, reducing both accidental and correlated backgrounds. Segmentation further reduces backgrounds by identifying the positron’s annihilation gammas, which are absent for most correlated and uncorrelated backgrounds. This work explores different configurations in order to maximize the size of the detector segments without reducing the intrinsic neutron detection efficiency. We believe this technology will ultimately be applicable to potential safeguards scenarios such as those recently described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

GaAs Thermophotovoltaic Patterned Dielectric Back Contact Devices with Improved Sub-Bandgap Reflectance

We demonstrate GaAs thermophotovoltaic (TPV) devices with a patterned dielectric back contact (PDBC) architecture, featuring a dielectric spacer between the semiconductor and back metal contact over most of the back surface for high reflectance, and metal point contacts over a smaller area for electrical conduction. In the TPV application, high sub-bandgap reflectance is needed to reflect unused sub-bandgap photons to the thermal emitter to minimize energy losses in this portion of the thermal spectrum. We explore different PDBC fabrication processes with SU-8 and SiO2 dielectric spacer layers to maximize sub-bandgap reflectance while minimizing series resistance to increase TPV conversion efficiency. We successfully demonstrate GaAs SU-8 PDBC TPV devices with 2200 degrees C blackbody-weighted sub-bandgap reflectance of 94.9% and 96.5% with and without a front metal grid, respectively. This is 0.7% and 2.3% (absolute) higher than the mean sub-bandgap reflectance of 94.2% for GaAs baseline TPV devices with 100% Au back contact with front metal grid. Lower sub-bandgap reflectance in TPV devices with front grids indicates the front grid induces light scattering leading to additional parasitic absorption in the TPV device. We also show that for higher contact coverage fractions, the PDBC reflectance cannot in general be treated by a linear interpolation using simple 1D transfer matrix method modeling and should be treated instead as a diffraction grating by solving Maxwell's equations in 3D.

energy storage↗
DOE OSTI2023

Hybrid Integration of GaP Photonic Crystal Cavities with Silicon-Vacancy Centers in Diamond by Stamp-Transfer

Optically addressable solid-state defects are emerging as some of the most promising qubit platforms for quantum networks. Maximizing photon-defect interaction by nanophotonic cavity coupling is key to network efficiency. We demonstrate fabrication of gallium phosphide 1-D photonic crystal waveguide cavities on a silicon oxide carrier and subsequent integration with implanted silicon-vacancy (SiV) centers in diamond using a stamp-transfer technique. The stamping process avoids diamond etching and allows fine-tuning of the cavities prior to integration. After transfer to diamond, we measure cavity quality factors (Q) of up to 8900 and perform resonant excitation of single SiV centers coupled to these cavities. For a cavity with a Q of 4100, we observe a 3-fold lifetime reduction on-resonance, corresponding to a maximum potential cooperativity of C = 2. In conclusion, these results indicate promise for high photon-defect interaction in a platform which avoids fabrication of the quantum defect host crystal.

Purcell enhancement↗
DOE OSTI2019

Sub-20 nm Core–Shell–Shell Nanoparticles for Bright Upconversion and Enhanced Förster Resonant Energy Transfer

Upconverting nanoparticles provide valuable benefits as optical probes for bioimaging and Förster resonant energy transfer (FRET) due to their high signal-to-noise ratio, photostability, and biocompatibility; yet, making nanoparticles small yields a significant decay in brightness due to increased surface quenching. Approaches to improve the brightness of UCNPs exist but often require increased nanoparticle size. Here we present a unique core-shell-shell nanoparticle architecture for small (sub-20 nm), bright upconversion with several key features: (1) maximal sensitizer concentration in the core for high near-infrared absorption, (2) efficient energy transfer between core and interior shell for strong emission, and (3) emitter localization near the nanoparticle surface for efficient FRET. This architecture consists of β-NaYbF 4 (core) @NaY 0.8-x Er x Gd 0.2 F 4 (interior shell) @NaY 0.8 Gd 0.2 F 4 (exterior shell), where sensitizer and emitter ions are partitioned into core and interior shell, respectively. Emitter concentration is varied (x = 1, 2, 5, 10, 20, 50, and 80%) to investigate influence on single particle brightness, upconversion quantum yield, decay lifetimes, and FRET coupling. We compare these seven samples with the field-standard core-shell architecture of β-NaY 0.58 Gd 0.2 Yb 0.2 Er 0.02 F 4 (core) @NaY 0.8 Gd 0.2 F 4 (shell), with sensitizer and emitter ions codoped in the core. At a single particle level, the core-shell-shell design was up to 2-fold brighter than the standard core-shell design. Further, by coupling a fluorescent dye to the surface of the two different architectures, we demonstrated up to 8-fold improved emission enhancement with the core-shell-shell compared to the core-shell design. Finally, we show how, given proper consideration for emitter concentration, we can design a unique nanoparticle architecture to yield comparable or improved brightness and FRET coupling within a small volume.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Transparent conductor-Si pillars heterojunction photodetector

We report a high-performing heterojunction photodetector by enhanced surface effects. Periodically, patterned Si substrates were used to enlarge the photo-reactive regions and yield proportionally improved photo-responses. An optically transparent indium-tin-oxide (ITO) was deposited on a Si substrate and spontaneously formed an ITO/Si heterojunction. Due to an electrical conductive ITO film, ITO/Si heterojunction device can be operated at zero-bias, which effectively suppresses the dark current, resulting in better performances than those by a positive or a negative bias operation. This zero-bias operating heterojunction device exhibits a short response time (∼ 22.5 ms) due to the physical reaction to the incident light. We revealed that the location of the space charge region (SCR) is crucial for a specific photon-wavelength response. The SCR space has the highest collection efficiency of the photo-generated carriers. The photo-response can be maximized when we design the photodetector by superposing the SCR space over a corresponding photon-absorption length. The surface enhanced Si pillar devices significantly improved the photo-responses ratios from that of a planar Si device. According to this design scheme, a high photo-response ratio of 5560% was achieved at a wavelength of 600 nm. This surfaced-enhanced heterojunction design scheme would be a promising approach for various photoelectric applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

tomoCAM : fast model-based iterative reconstruction via GPU acceleration and non-uniform fast Fourier transforms

X-ray-based computed tomography is a well established technique for determining the three-dimensional structure of an object from its two-dimensional projections. In the past few decades, there have been significant advancements in the brightness and detector technology of tomography instruments at synchrotron sources. These advancements have led to the emergence of new observations and discoveries, with improved capabilities such as faster frame rates, larger fields of view, higher resolution and higher dimensionality. These advancements have enabled the material science community to expand the scope of tomographic measurements towards increasingly in situ and in operando measurements. In these new experiments, samples can be rapidly evolving, have complex geometries and restrictions on the field of view, limiting the number of projections that can be collected. In such cases, standard filtered back-projection often results in poor quality reconstructions. Iterative reconstruction algorithms, such as model-based iterative reconstructions (MBIR), have demonstrated considerable success in producing high-quality reconstructions under such restrictions, but typically require high-performance computing resources with hundreds of compute nodes to solve the problem in a reasonable time. Here, tomoCAM , is introduced, a new GPU-accelerated implementation of model-based iterative reconstruction that leverages non-uniform fast Fourier transforms to efficiently compute Radon and back-projection operators and asynchronous memory transfers to maximize the throughput to the GPU memory. The resulting code is significantly faster than traditional MBIR codes and delivers the reconstructive improvement offered by MBIR with affordable computing time and resources. tomoCAM has a Python front-end, allowing access from Jupyter -based frameworks, providing straightforward integration into existing workflows at synchrotron facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Shifting Between Compute and Memory Bounds: A Compression-Enabled Roofline Model

In the evolving landscape of high-performance computing, especially to fight the end of Moore’s Law and Dennard’s Scaling, the ability to shift between compute-bound and memory-bound states is critical for enhancing adaptability and flexibility to diverse system and domain-specific architectures. Such capability is vital for optimizing performance across distinguished hardware configurations, such as accelerators, memory hierarchies, and cache systems. Despite that ad hoc optimization techniques, such as compressed/approximate computation, have been enabled for compute-/data-intensive computing for improved performance in distinct hardware settings, there lacks an understanding of 1) the rational behind performance improvement; 2) capability of different optimizations; 3) what optimization to respond to specific computational and memory demands. This work proposes a compression-enabled roofline model to facilitate this adaptability with data compression techniques to balance and transform between computational and memory demands. This model enables applications to adjust in response to the specific strengths and limitations of the underlying hardware and system to optimize resource utilization. The effectiveness of this approach is demonstrated with matrix multiplication kernels on different input sizes, with turning on/off various compression techniques, including 1) low-precision floating point; 2) sparse matrix formulation; and 3) compressed arrays with ZFP. By reducing memory transfer volumes and cache misses and increasing data locality and computational intensity through compression, the specific roofline model can transform between compute and memory bounds to align more efficiently with system capabilities. This advancement not only improves overall performance but also maximizes adaptability in diverse computing environments.

Naraparaju, Ramasoumya [University of Washington]↗
DOE OSTI2025

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗