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At least 343 records · Page 19

Dual-sided charge-coupled devices

Existing charge-coupled devices (CCDs) operate by detecting either the electrons or holes created in an ionization event. Here, we propose an imager, the dual-sided CCD, which collects and measures both charge carriers on opposite sides of the device via a dual-buried channel architecture. We show that this dual detection strategy provides exceptional dark-count rejection and enhanced timing capabilities. These advancements have wide-ranging implications for dark-matter searches, near-infrared/optical spectroscopy, and time-domain x-ray astrophysics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fabrication of a Point-Like Transmission Target for Reducing Computed Tomography Imaging Artifacts

In this study, we address the challenge of enhancing image quality and spatial resolution in computed tomography (CT) imaging by introducing simulation and fabrication of high aspect ratio, point-like transmission targets. Utilizing advanced electroplating techniques, traditionally employed in the fabrication of Through Substrate Via (TSV) interconnects for CMOS circuitry, we successfully embed copper targets within silicon substrates. This method allows us to create high-aspect-ratio features specifically designed for X-ray transmission targets, resulting in micro targets that exhibit a volume increase compared to conventional evaporated surface targets. Furthermore, we present simulation results of the X-ray spectrum generated by these targets, demonstrating their potential to significantly improve both image quality and spatial resolution in CT applications. Our findings suggest that leveraging advanced fabrication techniques can open new avenues for the development of enhanced imaging technologies in medical diagnostics and beyond.

47 OTHER INSTRUMENTATION↗

Measuring 3D Profilometry of SAVY-4000 Nuclear Material Storage Containers: Novacam TubeInspect Capabilities Report

The SAVY-4000 container series is a general-purpose interim storage container for nuclear materials, developed and maintained by Los Alamos National Laboratory (LANL). It is the first vented, general-use nuclear material container to be demonstrated as meeting the requirements outlined in DOE M 441.1-1, the Nuclear Material Packaging Manual. Due to the challenging radiation, thermal, and corrosive storage conditions that the SAVY containers must endure, continuous surveillance techniques are employed to ensure the containers meet all safety standards and specifications. These inspections are typically performed by human operators, who check for issues such as corrosion, O-ring deterioration, corrosion, filter integrity, and potential manufacturing defects. However, human inspections alone are not sufficient, and automated inspection technologies, such as the ATIS system, as well as other automated systems are also utilized. The MicroCam TubeInspect, developed by Novacam Technologies Inc., is designed to address the challenges of understanding how manufacturing variations in the SAVY-4000 container series may affect performance. It is a 3D profilometry measurement system that enables detailed analysis of surface features, including defects, surface roughness, and manufacturing variations. This advanced tool significantly enhances rapid surveillance techniques for both pristine and used containers. In this study, container properties such as surface roughness, thickness, and geometric attributes like circularity are measured for SAVY-4000 containers. Artificially corroded or dented containers are examined to demonstrate the MicroCam's ability to quantify defects. A sensitivity analysis is also conducted, comparing the MicroCam results to those obtained using more precise instruments such as confocal microscopy. This comparison aims to provide valuable insights into container quality, durability, and potential improvements in manufacturing processes.

42 ENGINEERING↗

Comparison of theory with the experimental characterization of the spatial frequency response of interferometers using a binary pseudo-random array sample

Experimental evaluations of the surface height response of an interference microscope using a binary pseudo-random array test sample are compared with a theory based on a Fourier optics model. Measurements of key instrument characteristics, including the illumination, imaging, and obscuring apertures of three different Mirau objectives, support the theoretical calculations. Agreement between experimental and theoretical modeling confirms the predictability of the spatial frequency response for the purpose of specification and optimization of instrument configuration for specific metrology tasks. The results also provide confidence in methods of compensating for the decrease in instrument response with spatial frequency.

Calibration↗

Detection of the pairwise kinematic Sunyaev-Zel’dovich effect and pairwise velocity with DESI DR1 galaxies and ACT DR6 and Planck CMB data

We present a 9.3⁢𝜎 detection of the pairwise kinematic Sunyaev-Zel’dovich (kSZ) effect by combining a sample of 913,286 Luminous Red Galaxies (LRGs) from the Dark Energy Spectroscopic Instrument Data Release 1 (DESI DR1) catalog and coadded Atacama Cosmology Telescope (ACT DR6) and Planck cosmic microwave background (CMB) temperature maps. This represents the highest-significance pairwise kSZ measurement to date. The analysis uses three ACT CMB temperature maps: coadded 150 GHz, total frequency maps, and a component separated Internal Linear Combination (ILC) map, all of which cover 19,000 square degrees of the sky from Advanced ACTPol observations conducted between 2017 and 2022. Comparison of the results of these three maps serves as a consistency check for potential foreground contamination that may depend on the observation frequency. An estimate of the best-fit mass-averaged optical depth is obtained by comparing the pairwise kSZ curve with the linear theory prediction of the pairwise velocity under the best-fit Planck cosmology and is compared with predictions from simulations. This estimate serves as a reference point for future comparisons with thermal SZ–derived optical depth measurements for the same DESI cluster samples, which will be presented in a companion paper. Finally, we employ a machine learning approach, trained on simulations to estimate the optical depth for 456,803 DESI LRG-identified clusters within the simulated mass range ( ≳ 10 13 ⁢𝑀 ⊙ ). These are combined with the measured kSZ signal to infer the individual cluster peculiar velocities, providing the opportunity to constrain the behavior of gravity and the dark sector over a range of cosmic scales and epochs.

Gong, Yulin [Cornell University] (ORCID:0000000346↗

Measurement of Photons Emitted by High-Energy Charged Particles as Background in Single-Photon Resolving Image Sensors

This work introduces an advanced technique optimized for detecting photons generated by charged particles, leveraging Skipper charge coupled device (Skipper-CCD) image sensors. By analyzing background sources and detection efficiencies, the technique achieves strong agreement between experimental results and Cherenkov-based simulations. It also provides a robust framework for investigating secondary photon production in environments with high fluxes of ionizing particles, such as those anticipated in space-based astronomical instruments. These secondary photons present a critical challenge as background noise for next-generation single-photon resolving imagers used to study faint celestial objects. Furthermore, the method exhibits significant potential for broader applications, including exploring photon generation in various substrate materials and examining their transport through multiple interfaces.

Fernandez Moroni, Guillermo [Fermilab; Chicago U.,↗

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗

Field Validation of MVA Technology for Offshore CCS: Novel Ultra-High-Resolution 3D Marine Seismic Technology (P-Cable) (Final Report)

The objectives of the proposed study were to deploy and validate a specific monitoring technology, high-resolution 3D marine seismic (HR3D), appropriate for large-demonstration and commercial-scale offshore CCS sites. The project accomplished successful acquisition two HR3D seismic surveys. The first HR3D dataset was over the offshore injection site of the Tomakomai, Japan integrated pilot CCS project, which at the time of survey acquisition was actively injecting CO 2 . The first survey also represented a successful international collaboration between the DOE NETL program and Japan’s national CCS program and was the first successful acquisition and use of HR3D over an active CO 2 injection site (Meckel, Feng et al. 2019). The Tomakomai HR3D survey successfully tested a novel 4-streamer HR3D system array in which, for the first time, no cross-cable (aka “P-Cable”) was utilized and only four GeoEel streamers were used instead of the standard 12-streamer configuration. Consequently, this was not, strictly speaking, a deployment of the “P-Cable” system of (Planke and Berndt 2004) but rather a modified version, thereof, and it is the first known demonstration of the modified system configuration. One very positive outcome from the Japanese collaboration earlier in the project was the ability to learn from the Japanese how they used tail buoys with GPS to determine the position of the seismic source and receivers in time and space. Based on that experience, GCCC designed and built six GPS receivers that could be used to position the streamer receivers and the seismic source via tail buoys. A fundamental advance that was made on the original design, was the ability to directly power the tail buoy GPS units and transfer data through the streamers (i.e., vs. the batteries used at Tomakomai). The bulkiness of the GPS batteries caused drag and episodic surging of the buoys, which affected data quality by lifting up the tail end of the streamers so the receivers were not at the same depth. The units were tested onshore for accuracy and functionality, and the design was subsequently and successfully tested in marine acquisition mode during the SLP survey acquisition. The marine acquisition test and survey satisfied Subtasks 2.2.2, Novel Positioning Technology Selection and Subtask 2.2.3, Novel Positioning Technology Deployment. Results of the novel positioning technology selection (Subtask 2.2.2) were considered successful and will be incorporated in future HR3D seismic acquisition projects to reduce costs, improve deployment safety at sea, and integrate both seismic and data recording via a single data transfer through the streamers to the recording system. The project also established a permitting process through NETL NEPA compliance, which included an Environmental Assessment in a marine setting and is required for conducting these types of surveys using Federal funding. The permitting process charted a “boilerplate,” which can allow future surveys related to other funded projects to move forward more expeditiously. Future improvements that could be considered are more robust seals on the GPS module and stronger materials (especially joints) on tail buoy fabrication. These would increase fixed costs, but would be advisable and probably more economic long-term if multiple HR3D surveys are planned. Project Accomplishments include: • Pre-survey Sensitivity Study • Marine geochemistry methods and data analysis • Successful HR3D seismic dataset acquired @ Tomakomai active CO 2 injection marine site • Developed advanced seismic processing techniques • No NRMS anomalies detected in overburden; Demonstration of containment • Repeatability study • Second survey collected @ San Luis Pass, TX • 4D application using positioning techniques developed in the project for monitoring were successful

3D seismic GPS positioning↗

Findings on subtask 3.3 – applicability of automated brine chemistry determinations for treatment and recovery processes through facility automation/modularization: engineering design study

Under the Energy & Environmental Research Center’s (EERC’s) ~$\$$22 million Phase II Brine Extraction and Storage Test (BEST) Program, a multimillion-dollar brine treatment technology test bed facility was established in western North Dakota to provide a platform for evaluating developing technologies and approaches for brine treatment and volume reduction. The initial facility, and associated research effort, was funded by the U.S. Department of Energy (DOE), with in-kind contributions provided by several industry participants and the state of North Dakota. Since its opening, the Brine Technology Test Facility (BTTF) has supported performance evaluations of desalination technologies capable of treating high-salinity produced water (PW) and enabled data collection for multiple approaches of PW management and critical material recovery. As part of the decommissioning process for the original project, facility ownership and liability were transferred to Select Water, which is providing the EERC with a continuing site access option for state or federal research and/or commercial technology development. This report documents the findings from a design study conducted by the EERC and the engineering firm that was originally contracted to design and construct the facility (Advanced Engineering and Environmental Services, LLC [AE2S]) that evaluated the current status of BTTF and its systems and developed a retrofit design to increase the facility’s capabilities through automation and modularization of its PW treatment infrastructure. The proposed retrofit will provide DOE and industry with an expanded range of conditioned PW that can be produced at the facility for evaluating fit-for-purpose water treatment technologies, online instrumentation for brine chemistry determination, and systems that recover critical materials like lithium and magnesium. The current facility consists of an 9600-square-foot facility that includes a 40-foot by 65-foot Class 1, Division 2-rated demonstration area and associated control rooms and lab-ready space capable of sourcing oil and gas PW and wastewater from industrial sources or tailoring brine compositions up to 300,000 mg/L total dissolved solids (TDS) and supplying them at rates up to 25 gpm for extended-duration technology demonstrations. The colocation of the facility with Select Water’s water management facilities allows for access and unloading of more than 10,000 bbl/day of trucked water delivered to site and associated access to on-site Class I and Class II brine disposal wells and nearby hazardous waste landfills operated and/or contracted by Select Water to dispose of concentrate and/or effluents associated with the testing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Overview of preparation for the American WAKE ExperimeNt (AWAKEN)

The American WAKE ExperimeNt (AWAKEN) is a multi-institutional field campaign focused on gathering critical observations of wind farm–atmosphere interactions. These interactions are responsible for a large portion of the uncertainty in wind plant modeling tools that are used to represent wind plant performance both prior to construction and during operation and can negatively impact wind energy profitability. The AWAKEN field campaign will provide data for validation, ultimately improving modeling and lowering these uncertainties. The field campaign is designed to address seven testable hypotheses through the analysis of the observations collected by numerous instruments at 13 ground-based locations and on five wind turbines. The location of the field campaign in Northern Oklahoma was chosen to leverage existing observational facilities operated by the U.S. Department of Energy Atmospheric Radiation Measurement program in close proximity to five operating wind plants. The vast majority of the observations from the experiment are publicly available to researchers and industry members worldwide, which the authors hope will advance the state of the science for wind plants and lead to lower cost and increased reliability of wind energy systems.

17 WIND ENERGY↗

A Smart Vision-Aided RICH (Robotic Interface Control and Handling) System for VULCAN

High-flux neutron beams and high-efficiency detectors enable rapid neutron diffraction measurements at the Engineering Materials Diffractometer (VULCAN) at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory (ORNL). To optimize beam time utilization, efficient sample exchange, alignment, and automated measurements are essential. Recent advances in artificial intelligence (AI) have expanded the capabilities of robotic systems. Here, we report the development of a Robotic Interactive Control and Handling (RICH) system for sample handling at VULCAN, designed to support high-throughput experiments and reduce overhead time. The RICH system employs a six-axis desktop robot integrated with AI-based computer vision models capable of recognizing and localizing samples in real time from instrument and depth-resolving cameras. Vision algorithms combine these detections to align samples with designated measurement positions or place them within complex sample environments such as furnaces. This integration of machine learning-assisted vision with robotic handling demonstrates the feasibility of autonomous sample detection and preparation, offering a pathway toward fully unmanned neutron scattering experiments.

automation↗

The scientific case for concurrent neutron and X-ray scattering and spectroscopy

The interrogation of materials with X-rays or neutrons to determine structure, energetics, and dynamics is fundamental to advancing physical and chemical materials science and enabling innovative material technologies. A persistent challenge in materials development is that progress depends on understanding structure and dynamics across multiple length and time scales in increasingly complex, multicomponent systems featuring interfaces, heterogeneity, and hierarchical organization. Despite rapidly growing demands on materials characterization, current experimental approaches are almost exclusively based on isolated X-ray or neutron scattering and spectroscopy, reflecting a paradigm largely unchanged for decades. To assess the scientific need for a new experimental paradigm, a 3-day workshop sponsored by the U.S. National Science Foundation (NSF) was held at the SpringHill Suites, San Jose, California, from June 2 to 4, 2022. The workshop brought together 70 national and international experts who critically evaluated opportunities enabled by concurrent neutron and X-ray (NeX) scattering, spectroscopy, and imaging experiments. The participants reached a clear consensus that establishing NeX capabilities is crucial for advancing the science of complex materials in the United States. This report illustrates the scientific drivers for NeX experiments through representative examples spanning biomaterials, energy materials, soft matter, nanomaterials, quantum materials, geoscience, and applied materials research. The complementarity of neutrons and X-rays is essential for robust model development and refinement, particularly in multiphase and multicomponent systems. While joint refinement of data from separate experiments is valuable, concurrent measurements uniquely eliminate uncertainties arising from sample evolution, environmental drift, and irreproducibility associated with experiments performed at different locations and times. Realizing NeX capabilities will require the development of new instrumentation, data analysis frameworks, and robust sample environments compatible with both neutron and X-ray probes. Addressing these challenges will enable unambiguous interpretation of complex materials behavior and open new frontiers in materials research.

X-ray↗

Role of Nuclear Science User Facilities (NSUF) in Nuclear Energy Materials Research

The Nuclear Science User Facilities (NSUF) is one of a diverse number of U.S. Department of Energy (DOE) user facilities established to provide researchers with the most advanced tools of modern science. The NSUF is unique and represents a consortium of capabilities distributed across the U.S. at twenty-one institutions. The NSUF is centered at and managed from the Idaho National Laboratory (INL), where it was originally founded, but it coordinates activities at twenty “partner” institutions that include universities, the Center for Advanced Energy Studies (CAES), national laboratories, and a nuclear industry vendor. These institutions have capabilities that include neutron, ion, and gamma irradiation, hot cells, advanced materials characterization equipment, and high-performance computing resources. Many of these capabilities were beyond reach for most researchers before NSUF. The NSUF provides researchers to access these capabilities at no cost to nuclear energy researchers to produce the highest quality research results to increase understanding of advanced nuclear energy technologies important to DOE-NE and support national priorities by adapting to the needs of DOE-NE programs, industry, and new innovative concepts for sustainable nuclear future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantum-enhanced detection of viral cDNA via luminescence resonance energy transfer using upconversion and gold nanoparticles

Abstract The COVID-19 pandemic has profoundly impacted global economies and healthcare systems, revealing critical vulnerabilities in both. In response, our study introduces a sensitive and highly specific detection method for cDNA, leveraging Luminescence Resonance Energy Transfer (LRET) between upconversion nanoparticles (UCNPs) and gold nanoparticles (AuNPs), and achieves a detection limit of 242 fM for SARS-CoV-2 cDNA. This innovative sensing platform utilizes UCNPs conjugated with one primer and AuNPs with another, targeting the 5′ and 3′ ends of the SARS-CoV-2 cDNA, respectively, enabling precise differentiation of mismatched cDNA sequences and significantly improving detection specificity. Through rigorous experimental analysis, we established a quenching efficiency range from 10.4 % to 73.6 %, with an optimal midpoint of 42 %, thereby demonstrating the superior sensitivity of our method. Our work uses SARS-CoV-2 cDNA as a model system to demonstrate the potential of our LRET-based detection method. This proof-of-concept study highlights the adaptability of our platform for future diagnostic applications. Instrumental validation confirms the synthesis and formation of AuNPs, addressing the need for experimental verification of the preparation of nanomaterial. Our comparative analysis with existing SARS-CoV-2 detection methods revealed that our approach provides a low detection limit and high specificity for target cDNA sequences, underscoring its potential for targeted COVID-19 diagnostics. This study demonstrates the superior sensitivity and adaptability of using UCNPs and AuNPs for cDNA detection, offering significant advances in rapid, accessible diagnostic technologies. Our method, characterized by its low detection limit and high precision, represents a critical step forward in developing next-generation biosensors for managing current and future viral outbreaks. By adjusting primer sequences, this platform can be tailored to detect other pathogens, contributing to the enhancement of global healthcare responsiveness and infectious disease control.

Esmaeili, Shahriar [Institute for Quantum Science ↗

Colorado State University Extension Industrial Assessment Center

Since its inception in 1984, the Colorado State University Industrial Assessment Center has performed industrial assessments at more than 720 manufacturing facilities in Colorado, Montana, Nebraska, Nevada, New Mexico, North Dakota, South Dakota, Utah, and Wyoming. From 2017 to 2019 there was a funding gap and the IAC shutdown. In 2020 through DOE extension funding the University relaunched the IAC as an extension center in order to provide assessments to underserved areas. Under this award, the CSU Industrial Assessment Center (IAC) was rebuilt with the help of student employees and the director. The CSU team experienced difficulty as the program was in the process of being restarted right as the 2020 pandemic hit. Nonetheless, the CSU IAC was instrumental in providing energy assessments to manufacturers in Colorado and Wyoming during the period of performance of 09/2019 – 12/2022. The Department of Energy's Industrial Assessment Centers (IACs) provide a valuable service to small and medium-sized manufacturers seeking to optimize their operations. These university-based centers offer no-cost, on-site assessments conducted by engineering faculty and students, analyzing energy consumption, production processes, and waste streams. They utilize advanced data acquisition systems to record operational data, and then use the data to create assessment recommendations. These recommendations form the foundation of the comprehensive energy report. The comprehensive report delivers actionable recommendations for enhancing energy efficiency, reducing waste, and reducing greenhouse gas emissions and improving productivity, often identifying significant cost savings. Furthermore, IACs facilitate access to implementation grants, enabling the businesses to readily adopt these improvements. This program not only strengthens individual businesses but also contributes to national goals of training the next generation of energy experts, as well as increasing industrial competitiveness and reduced environmental impact.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Radiative Cooling Paints: Application on Warehouses and Integration with Phase Change Materials

Despite extensive research on radiative cooling (RC), researchers are still working to understand its best implementation strategy and potential benefits. Understanding this could be an instrumental part of reducing building energy costs and combating climate change. In this work, we introduce two concepts to achieve this goal and broaden the application of RC paints. While building energy simulations for RC are common, most studies focus on single-layer paints in residential settings. Limited research exists on warehouses, and no literature has conducted multi-climate zone analyses or included RC technologies with >90% reflectance. As RC technology advances in efficiency, versatility, and affordability, large-scale simulations across diverse climates are crucial, particularly for warehouses as a passive indoor temperature control solution. Here, a TRNSYS-modeled single-story warehouse assesses the energy impact of BaSO4-based RC paints. Another under-explored RC application is its integration with phase change materials (PCMs), which provide thermal regulation via latent heat storage. Though RC and PCMs have been combined by placing PCMs atop, beneath, or within RC layers, studies focus on either experiments or modeling, with no validation between the two. Here, we develop a simple RC+PCM experimental and modeling setup, placing RC paint atop an aluminum cell filled with a Rubitherm PCM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗