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At least 667 records · Page 37

An Overview of the Design and Development of the GOES R-Series Space Segment

The first of the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellite R-series (GOES-R) satellites was launched in November 2016. GOES-R has been developed by NOAA in partnership with the National Aeronautics and Space Administration (NASA). The satellite represents a quantum leap in the state of the art for geostationary weather satellites by providing data from a suite of six new instruments. All instruments were developed expressly for this mission, and include two Earth-observing instruments (the Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM)), two solar-viewing instruments (Solar Ultraviolet Imager (SUVI) and Extreme ultraviolet and X-ray Irradiance Sensors (EXIS)) and two in situ instruments (Space Environment In-Situ Suite (SEISS) and a magnetometer pair). In addition to hosting the instruments, GOES-R also accommodates several communication packages designed to collect and relay data for weather forecasting and emergency management. Accommodating the six instruments and four communication payloads imposed challenging and competing constraints on the satellite, including requirements for extremely stable earth and solar pointing, high-speed and nearly error-free instrument data transmission, and a very quiet electromagnetic background. To meet mission needs, GOES-R employed several technological innovations, including low-thrust rocket engines that allow instrument observations to continue during maneuvers, and the first civilian use of Global Positioning System-based orbit determination in geostationary orbit. This paper will provide a brief overview of the GOES-R satellite and its instruments as well as the developmental challenges involved in accommodating the instruments and communications payloads.

GOES-16↗

Uncertain quantum computing futures and potential energy and physical resource impacts at scale

Considerable attention has recently focused on the vast energy and water demands of supercomputing, namely large-scale data centers that underpin artificial intelligence (AI), one of the great disruptors of contemporary society. Looking ahead some years from now, quantum computing is poised to disrupt established computing paradigms once again. Scientists and engineers are now working intensely to bring this century-old dream of physicists to fruition. Yet, as quantum computers begin to be integrated with classical supercomputing architectures, the implications for energy and physical resource use also need to be understood, especially how they compare to today’s AI data centers. These impacts have not yet been quantified by the research community – a notable gap in the literature, even if commercial-scale deployment of Quantum-Accelerated Computing Infrastructure (QuACI) is not expected for a few more years. This study is the first to conduct such an assessment. Using publicly available information from academic sources and private industry, we characterize multiple configurations of superconducting qubit-based, fault-tolerant quantum computers (FTQC) that could plausibly be deployed at scale in the 2030s and into the 2040s. By parameterizing these FTQC systems at a process level, we conduct a prospective scenario analysis to quantify their energy and physical resource needs. While these estimates are uncertain, given the current state of quantum technologies and their unknown future trajectories, important insights can already be drawn. One key finding is that while the electricity needs for a fleet of FTQCs are within the bounds of previous modeling studies that have explored high electricity demand futures, the needs for certain physical resources, namely water and helium-3, could pose bottlenecks to QuACI scale-up.

Computing↗

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗

Dynamic magnetic phase transition induced by parametric magnon pumping

Uncovering pathways to optically drive magnetic order-disorder transitions on ultrashort timescales can lead to the realization of novel out-of-equilibrium quantum phenomena. A long-sought pathway is to directly excite a highly nonthermal energy-momentum distribution of magnons, bypassing both charge and lattice degrees of freedom. However, this remains elusive owing to the weak coupling and large momentum mismatch between photons and magnons. Here we demonstrate strong parametric excitation of magnons across the entire Brillouin zone of the antiferromagnetic insulator Sr 2 ⁢Cu 3 ⁢O 4 ⁢Cl 2 by periodically modulating the superexchange interaction with the electric field of light. The excitation efficiency is greatly enhanced by tuning to the van Hove singularity in the magnon spectrum, sufficient to transiently collapse the antiferromagnetic state using a pulsed laser field of 10 9 V/m. The order parameter recovery timescale increases by over 1000 times as a function of excitation density, reflecting a crossover from high- to low-energy magnon dominated decay dynamics. This electric-field induced parametric magnon pumping mechanism is applicable to a broad range of magnetic insulators and opens up the possibility of dynamically engineering magnon distributions by design.

antiferromagnetism↗

Experimental and theoretical insights into the effects of pH on catalysis of bond-cleavage by the lignin peroxidase isozyme H8 from Phanerochaete chrysosporium

Abstract Background Lignin peroxidases catalyze a variety of reactions, resulting in cleavage of both β-O-4′ ether bonds and C–C bonds in lignin, both of which are essential for depolymerizing lignin into fragments amendable to biological or chemical upgrading to valuable products. Studies of the specificity of lignin peroxidases to catalyze these various reactions and the role reaction conditions such as pH play have been limited by the lack of assays that allow quantification of specific bond-breaking events. The subsequent theoretical understanding of the underlying mechanisms by which pH modulates the activity of lignin peroxidases remains nascent. Here, we report on combined experimental and theoretical studies of the effect of pH on the enzyme-catalyzed cleavage of β-O-4′ ether bonds and of C–C bonds by a lignin peroxidase isozyme H8 from Phanerochaete chrysosporium and an acid stabilized variant of the same enzyme. Results Using a nanostructure initiator mass spectrometry assay that provides quantification of bond breaking in a phenolic model lignin dimer we found that catalysis of degradation of the dimer to products by an acid-stabilized variant of lignin peroxidase isozyme H8 increased from 38.4% at pH 5 to 92.5% at pH 2.6. At pH 2.6, the observed product distribution resulted from 65.5% β-O-4′ ether bond cleavage, 27.0% C α -C 1 carbon bond cleavage, and 3.6% C α -oxidation as by-product. Using ab initio molecular dynamic simulations and climbing-image Nudge Elastic Band based transition state searches, we suggest the effect of lower pH is via protonation of aliphatic hydroxyl groups under which extremely acidic conditions resulted in lower energetic barriers for bond-cleavages, particularly β-O-4′ bonds. Conclusion These coupled experimental results and theoretical explanations suggest pH is a key driving force for selective and efficient lignin peroxidase isozyme H8 catalyzed depolymerization of the phenolic lignin dimer and further suggest that engineering of lignin peroxidase isozyme H8 and other enzymes involved in lignin depolymerization should include targeting stability at low pH.

09 BIOMASS FUELS↗

Achieving extreme light confinement in low-index dielectric resonators through quasi-bound states in the continuum

Obtaining large field enhancement in low-refractive-index dielectric materials is highly relevant to many photonic and quantum optics applications. However, confining light in these materials is challenging, owing to light leakage through coupling to continuum modes in the surrounding environment. Here, we investigate the possibility of achieving high quality factors in low-index dielectric resonators through the bound states in the continuum (BIC). Our simulations demonstrate that destructive interference between leaky modes can be achieved by tuning the geometrical parameters of the resonator arrays, leading to the emergence of quasi-BIC in resonators that have a small index contrast to the underlying substrates. The resultant large field enhancement gives rise to giant quality factors and Purcell effects. By introducing vertical mirror symmetry, the quasi-BIC can be tuned into an ideal BIC. In addition, the quasi-BIC can modify the emission patterns of the coupled emitters, rendering highly directional and focused far-field emission. These findings may provide a path for the practical implementation of photonic and quantum devices based on low-index dielectric materials.

42 ENGINEERING↗

APS Science 2020 (Vol. 2)

The U.S. Department of Energy's Advanced Photn Source (APS) is one of the world’s most productive x-ray light source facilities. Each year, the APS provides high-brightness x-ray beams to a diverse community of more than 5,000 researchers in materials science, chemistry, condensed matter physics, the life and environmental sciences, and applied research. Researchers using the APS produce over 2,000 publications each year detailing impactful discoveries, and solve more vital biological protein structures than users of any other x-ray light source research facility. APS x-rays are ideally suited for explorations of materials and biological structures; elemental distribution; chemical, magnetic, electronic states; and a wide range of technologically important engineering systems from batteries to fuel injector sprays, all of which are the foundations of our nation’s economic, technological, and physical well-being. The APS occupies an 80-acre site on the Argonne campus, about 25 miles from downtown Chicago, Illinois. It shares a site with the Center for Nanoscale Materials and the Advanced Protein Characterization Facility.

01 COAL, LIGNITE, AND PEAT↗

High Altitude Electromagnetic Pulse Testing of Photovoltaic Modules

This report details the test setup, process, and results for radiated susceptibility testing of multicrystalline silicon photovoltaic (PV) modules as part of the EMP-Resilient Electric Grid Grand Challenge Laboratory Directed Research and Development (LDRD) project at Sandia National Laboratories. Testing was conducted over October 10-17, 2019, where 8 photovoltaic modules were exposed to E1 transient pulses with peak field levels up to 100 kV/m. Modules were terminated in a resistive load representing connected components. State of health testing conducted via I-V curve tracing of the photovoltaic modules showed no observable loss of device function due to large electric field transients. Differential mode currents were measured on the order of 10's of amps for up to a microsecond following the radiated field pulse. Common mode currents took the form of a damped sinusoid with a maximum peak of 10's to 100's of amps with a resonance near 60 MHz.

14 SOLAR ENERGY↗

Solution-phase sample-averaged single-particle spectroscopy of quantum emitters with femtosecond resolution

Here, the development of many optical quantum technologies depends on the availability of solid-state single quantum emitters with near-perfect optical coherence. However, a standing issue that limits systematic improvement is the significant sample heterogeneity and lack of mechanistic understanding of microscopic energy flow at the single emitter level and ultrafast timescales. Here we develop solution-phase single-particle pump-probe spectroscopy with photon correlation detection that captures sample-averaged dynamics in single molecules and/or defect states with unprecedented clarity at femtosecond resolution. We apply this technique to single quantum emitters in two-dimensional hexagonal boron nitride, which suffers from significant heterogeneity and low quantum efficiency. From millisecond to nanosecond timescales, the translation diffusion, metastable-state-related bunching shoulders, rotational dynamics, and antibunching features are disentangled by their distinct photon-correlation timescales, which collectively quantify the normalized two-photon emission quantum yield. Leveraging its femtosecond resolution, spectral selectivity and ultralow noise (two orders of magnitude improvement over solid-state methods), we visualize electron-phonon coupling in the time domain at the single defect level, and discover the acceleration of polaronic formation driven by multi-electron excitation. Corroborated with results from a theoretical polaron model, we show how this translates to sample-averaged photon fidelity characterization of cascaded emission efficiency and optical decoherence time. Our work provides a framework for ultrafast spectroscopy in single emitters, molecules, or defects prone to photoluminescence intermittency and heterogeneity, opening new avenues of extreme-scale characterization and synthetic improvements for quantum information applications.

36 MATERIALS SCIENCE↗

Emergent ferromagnetism and insulator-metal transition in δ-doped ultrathin ruthenates

Abstract Heterostructures of complex transition metal oxides are known to induce extraordinary emergent quantum states that arise from broken symmetry and other discontinuities at interfaces. Here we report the emergence of unusual, thickness-dependent properties in ultrathin CaRuO 3 films by insertion of a single isovalent SrO layer (referred to as δ-doping). While bulk CaRuO 3 is metallic and nonmagnetic, films thinner than or equal to ~15-unit cells (u.c.) are insulating though still nonmagnetic. However, δ-doping to middle of such CaRuO 3 films induces an insulator-to-metal transition and unusual ferromagnetism with strong magnetoresistive behavior. Atomically resolved imaging and density-functional-theory calculations reveal that the whole δ-doped film preserves the bulk-CaRuO 3 orthorhombic structure, while appreciable structural and electronic changes are highly localized near the SrO layer. The results highlight delicate nature of magnetic instability in CaRuO 3 and subtle effects that can alter it, especially the role of A-site cation in electronic and magnetic structure additional to lattice distortion in ruthenates. It also provides a practical approach to engineer material systems via highly localized modifications in their structure and composition that may offer new routes to the design of oxide electronics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Extreme Nanoconfinement Dramatically Enhances Small Molecule Solubility in Nonpolar Polymers

Elucidating gas solubility in confined polymer systems addresses a fundamental gap in polymer physics and has important implications for gas barrier and separation technologies and polymer upcycling reactions. In this study, we examine the solubility of methanol and n-hexane in polystyrene and low-density polyethylene confined within the interstitial pores of disordered silica nanoparticle packings. Using capillary rise infiltration, these polymers are infiltrated into the nanoparticle packings. Gas solubility in these confined polymers is measured using a quartz crystal microbalance. Remarkably, confinement leads to a 10- to ∼100-fold increase in gas solubility. Systematic experiments reveal that pore size plays a dominant role in increasing solubility. In contrast, the molecular weight of the polymer and the surface wetting characteristics of the nanoparticles, achieved by hydrophobically modifying the nanoparticles, have minimal effects. By systematically varying penetrant polarity, polymer crystallinity, pore size, and nanopore surface chemistry, this study isolates geometric nanoconfinement as the dominant factor governing solubility enhancement in confined polymers. Atomistic simulations revealed that confinement and surface−polymer interactions both contribute to enhanced solubility, with polymer packing playing a significant role in modulating gas uptake. Here, these results suggest that the changes in the molecular arrangements of polymer segments underlie the observed trends. This study highlights the potential of confined polymers in engineering the separation performance of membranes and heterogeneously catalyzed polymer upcycling reactions.

alcohols↗

Optimizing the quality factor of InP nanobeam cavities using atomic layer deposition

Photonic crystal nanobeam cavities are valued for their small mode volume, CMOS compatibility, and high coupling efficiency-crucial features for various low-power photonic applications and quantum information processing. However, despite their potential, nanobeam cavities often suffer from low quality factors due to fabrication imperfections that create surface states and optical absorption. In this work, we demonstrate InP nanobeam cavities with up to 140% higher quality factors by applying a coating of Al 2 O 3 via atomic layer deposition to terminate dangling bonds and reduce surface absorption. Additionally, changing the deposition thickness allows precise tuning of the cavity mode wavelength without compromising the quality factor. This Al 2 O 3 atomic layer deposition approach holds great promise for optimizing nanobeam cavities that are well-suited for integration with a wide range of photonic applications.

42 ENGINEERING↗

Moiré engineering in van der Waals heterostructures

Isolated atomic planes can be assembled into a multilayer van der Waals (vdW) heterostructure in a precisely chosen sequence. These heterostructures feature moiré patterns if the constituent 2D material layers are stacked in an incommensurable way, due to a lattice mismatch or twist. This design-by-stacking has opened up the promising area of moiré engineering, a term that can be understood in two different perspectives, namely, (i) structural—engineering a moiré pattern by introducing twist, relative strain, or defects that affect the commensurability of the layers and (ii) functional—exploiting a moiré pattern to find and tune resulting physical properties of a vdW heterostructure. The latter meaning, referring to the application of a moiré pattern, is seen in the literature in the specific context of the observation of correlated electronic states and unconventional superconductivity in twisted bilayer graphene. The former meaning, referring to the design of the moiré pattern itself, is present in the literature but less commonly discussed or less understood. The underlying link between these two perspectives lies in the deformation field of the moiré superlattice. In this Perspective, we describe a path from designing a moiré pattern to employing the moiré pattern to tune physical properties of a vdW heterostructure. We also discuss the concept of moiré engineering in the context of twistronics, strain engineering, and defect engineering in vdW heterostructures. Although twistronics is always associated with moiré superlattices, strain and defect engineering are often not. Here, in this work, we demonstrate how strain and defect engineering can be understood within the context of moiré engineering. Adopting this perspective, we note that moiré engineering creates a compelling opportunity to design and develop multiscale electronic devices.

2D materials↗

Photophysical Properties and Phase Behavior of Ultrawide Photovoltaic Bandgap Cesium–Lead-Based Triple Halide Perovskites

Metal halide perovskite films in the top cell of triple-junction tandems require bandgaps around 2.0 eV to achieve current matching, assuming that the middle absorbing layer is the commonly used FAPbI 3 composition and the bottom cell has a bandgap around 1.1 eV. Unfortunately, mixed organic/inorganic metal halide perovskites that have the necessary Br content to reach a bandgap of 2.0 eV segregate into iodine-rich and bromine-rich phases under illumination, limiting their obtainable voltage. Previous reports have shown improved photostability using either Cs-based inorganic compositions or Cl incorporation on the X-site. Here, we investigate the inorganic triple halide compositional space CsPb­(I 1–x–y Br y Cl x ) 3 where bandgaps near 2.0 eV are expected based on the knowledge that CsPbI2Br has a bandgap of 1.90 eV. Incorporation of Cl occurs readily for x ≤ 0.07–0.10 within perovskites with a Br content of 0.3 ≤ y ≤ 0.42. When x >0.1, X-ray diffraction and photoluminescence (PL) measurements indicate that multiple compositional phases form. We hypothesize that the variable sizes of the three halide ions are not supported within the rigid Cs lattice, resulting in the formation of multiple compositional phases. The photoluminescence quantum yield of the single-phase compositional space–CsPb­(I 1–x–y Br y Cl x ) 3 where x ≤ 0.07was typically 0.001–0.004%, most likely as a result of a high defect density, including mobile iodine species. PL light-soaking measurements of many perovskite compositions with bandgaps in the range of 1.89–2.05 eV demonstrate that phase segregation occurs when initial bandgaps are above 1.95 eV regardless of halide content: indicating further iodide oxidation and corresponding migration under illumination. The conclusion is that further compositional or additive engineering is necessary for the development of inorganic triple halide compositions that accomplish the elusive goal of fabricating high-quality and photostable 2.0 eV films for use in multijunction tandems.

Electrical conductivity↗

Time-Gated Raman Spectroscopy (Intern Final Report)

Time-gated Raman spectroscopy is a powerful tool for rapid non-destructive analysis of chemical compounds, particularly when combined with other investigative methods. Time-gating the signal obtained from a sample during Raman spectroscopy allows for the removal of background emission and black body radiation, improving clarity and accuracy of scans. The main objectives of this project were to prove the lab’s time-gated Raman spectroscopy system works as proof of concept and to make select improvements to the in-house LabVIEW software used to run the time-gated system. This time-gated system will be added to the CTK’s TAP reactors in the future, but this is out of the scope of this internship project. This research is important, as understanding the mechanisms behind catalysts leads to designing better systems/materials and the perfection of catalysts, and energy-efficient chemical manufacturing is key when designing a greener future. The research for this project was done with samples at both ambient conditions in sample holders and at operando conditions (i.e., high temperature, unsteady-state) inside a small-volume chemical reactor. Numerous spectro-kinetic scans of the catalysts were obtained, but the advanced dynamics of these systems are still being interpreted. There is data that demonstrates that the time-gated system is correctly rejecting emission from samples, and one can observe real-time changes in the signal from the sample, due to coking or changes induced by redox chemistry. Chemical manufacturers and the planet are the main beneficiaries of catalysis research, as better catalysts will reduce carbon emissions.

36 MATERIALS SCIENCE↗

Emergent Above-Gap Photoluminescence in Molecularly Engineered Hybrid Bilayer Crystals

Bilayer crystals, built by stacking two-dimensional (2D) covalent monolayers, give rise to coupled excitonic states whose properties are constrained by fixed lattice symmetry and orientation. Replacing one covalent monolayer with a 2D molecular crystal––held together by non-covalent forces––overcomes this limitation, as molecular functional groups afford tunable in-plane lattice geometry, intermolecular spacing, and interlayer coupling, providing a powerful knob for exciton engineering. Here, in this study, we report four-atom-thick hybrid bilayer crystals (HBCs) synthesized by directly growing single-crystalline PDI molecular crystal atop WS 2 monolayers, which exhibit a robust photoluminescence (PL) peak 120 meV above the WS 2 optical band gap alongside a belowgap emission. Both peaks display strong polarization anisotropy—nearing unity for the above-gap emission—and maintain a perfectly linear power-law dependence up to an excitation density of ~10 7 mW/cm 2 , indicative of coexisting localized and delocalized excitonic states. Substituting PDI with a PTCDA monolayer on WS 2 fully quenches PL, demonstrating molecular control over excitonic emission. Lattice scale ab initio GW and GW-BSE calculations reveal a significantly hybridized bilayer band structure in PDI/WS 2 that supports interlayer excitonic species both above and below the WS 2 gap with strong polarization anisotropy, in excellent agreement with experiment. Our work introduces a molecule-based bilayer platform for the bottom-up design and control of excitonic phenomena in atomically thin optoelectronic and quantum materials.

2D materials↗

Chirality manipulation of ultrafast phase switches in a correlated CDW-Weyl semimetal

Light engineering of correlated states in topological materials provides a new avenue of achieving exotic topological phases inaccessible by conventional tuning methods. Here we demonstrate a light control of correlation gaps in a model charge-density-wave (CDW) and polaron insulator (TaSe 4 ) 2 I recently predicted to be an axion insulator. Our ultrafast terahertz photocurrent spectroscopy reveals a two-step, non-thermal melting of polarons and electronic CDW gap via the fluence dependence of a longitudinal circular photogalvanic current. This helicity-dependent photocurrent reveals continuous ultrafast phase switches from the polaronic state to the CDW (axion) phase, and finally to a hidden Weyl phase as the pump fluence increases. Additional distinctive attributes aligning with the light-induced switches include: the mode-selective coupling of coherent phonons to the polaron and CDW modulation, and the emergence of a non-thermal chiral photocurrent above the pump threshold of CDW-related phonons. The demonstrated ultrafast chirality control of correlated topological states here holds large potentials for realizing axion electrodynamics and advancing quantum-computing applications.

36 MATERIALS SCIENCE↗

Properties of Electronic Materials

This final technical report summarizes the research conducted under DOE Grant DE-SC0002623, "Properties of Electronic Materials," led by Principal Investigator Shengbai Zhang at Rensselaer Polytechnic Institute. Over the 16-year period, the project employed first-principles computational methods to investigate the structural, electronic, and dynamic properties of a wide range of electronic materials, with applications in energy technologies, optoelectronics, and data storage. Key areas included topological insulators, phase-change materials, graphene and two-dimensional systems, perovskites for photovoltaics, defect engineering in semiconductors, kagome lattices, and ultrafast carrier dynamics. The research resulted in 115 peer-reviewed publications, advancing fundamental understanding of material behaviors at the atomic scale and contributing to innovations in renewable energy, memory devices, and quantum materials. Findings have implications for improving energy efficiency, developing lead-free solar cells, and enabling high-speed data processing. The work has trained numerous graduate students and postdocs, fostering the next generation of computational materials scientists. The original goals were to develop theoretical models and computational tools to predict and optimize electronic properties of materials for energy applications. All objectives were accomplished, with no major departures from planned methodologies. Challenges in computational scaling were addressed through access to high-performance computing resources.

36 MATERIALS SCIENCE↗