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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Electrical and structural characterization of in situ MOCVD Al2O3/β-Ga2O3 and Al2O3/β-(AlxGa1−x)2O3 MOSCAPs

This study investigates the electrical and structural properties of metal–oxide–semiconductor capacitors (MOSCAPs) with in situ metal-organic chemical vapor deposition-grown Al2O3 dielectrics deposited at varying temperatures on (010) β-Ga2O3 and β-(AlxGa1−x)2O3 films with different Al compositions. The Al2O3/β-Ga2O3 MOSCAPs exhibited a strong dependence of electrical properties on Al2O3 deposition temperature. At 900 °C, reduced voltage hysteresis (∼0.3 V) with improved reverse breakdown voltage (74.5 V) was observed, corresponding to breakdown fields of 5.01 MV/cm in Al2O3 and 4.11 MV/cm in β-Ga2O3 under reverse bias. In contrast, 650 °C deposition temperature resulted in higher voltage hysteresis (∼3.44 V) and lower reverse breakdown voltage (38.8 V) with breakdown fields of 3.69 and 2.87 MV/cm in Al2O3 and β-Ga2O3, respectively, but exhibited impressive forward breakdown field, increasing from 5.62 MV/cm at 900 °C to 7.25 MV/cm at 650 °C. High-resolution scanning transmission electron microscopy (STEM) revealed improved crystallinity and sharper interfaces at 900 °C, contributing to enhanced reverse breakdown performance. For Al2O3/β-(AlxGa1−x)2O3 MOSCAPs, increasing Al composition (x) from 5.5% to 9.2% reduced net carrier concentration and improved reverse breakdown field contributions from 2.55 to 2.90 MV/cm in β-(AlxGa1−x)2O3 and 2.41 to 3.13 MV/cm in Al2O3. The electric field in Al2O3 dielectric under forward bias breakdown also improved from 5.0 to 5.4 MV/cm as Al composition increased from 5.5% to 9.2%. The STEM imaging confirmed the compositional homogeneity and excellent stoichiometry of both Al2O3 and β-(AlxGa1−x)2O3 layers. These findings demonstrate the robust electrical performance, high breakdown fields, and excellent structural quality of Al2O3/β-Ga2O3 and Al2O3/β-(AlxGa1−x)2O3 MOSCAPs, highlighting their potential for high-power electronic applications.

Bhuiyan, A. F. M. Anhar Uddin (ORCID:0000000334212↗
DOE OSTI2023

Reactor physics characterization of triply periodic minimal surface-based nuclear fuel lattices

Triply periodic minimal surface (TPMS) lattices are receiving substantial attention in numerous engineering fields due to their impressive topology-driven physical characteristics. TPMS lattices are periodic structures of two distinct intertwined volume domains separated by an area-minimizing surface or wall. TPMS lattices have been observed in nature, such as biological membranes, skeletons, block copolymers, sea urchins, butterfly wings, and equipotential surfaces in crystals. Intriguingly, the topology of TPMS lattices can be easily parametrized via level-set equations and thus are heavily numerically and experimentally studied. Here, a significant research effort is currently applying TPMS lattices for heat exchangers and sinks. This paper extends TPMS lattice applications to nuclear reactor fuel designs, with a focus on identifying relevant TPMS geometric parameters controlling neutronics characteristics, such as reactivity, neutron spectrum, and heat removal properties. We found that fuel surface-area-to-volume ratios for TPMS lattices can be two orders of magnitude larger than current cylindrical fuel rods. Further, the selected TPMS lattice and its implicit equation, the unit cell pitch, wall thickness, and structure porosity are design parameters enabling neutronics optimization for both thermal and fast spectrum configurations, paving the way for exceptionally compact and dense nuclear core concepts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Harnessing deep reinforcement learning to construct time-dependent optimal fields for quantum control dynamics

Here, we present an efficient deep reinforcement learning (DRL) approach to automatically construct time-dependent optimal control fields that enable desired transitions in dynamical chemical systems. Our DRL approach gives impressive performance in constructing optimal control fields, even for cases that are difficult to converge with existing gradient-based approaches. We provide a detailed description of the algorithms and hyperparameters as well as performance metrics for our DRL-based approach. Our results demonstrate that DRL can be employed as an effective artificial intelligence approach to efficiently and autonomously design control fields in quantum dynamical chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

High-dimensional multi-fidelity Bayesian optimization for quantum control

Abstract We present the first multi-fidelity Bayesian optimization (BO) approach for solving inverse problems in the quantum control of prototypical quantum systems. Our approach automatically constructs time-dependent control fields that enable transitions between initial and desired final quantum states. Most importantly, our BO approach gives impressive performance in constructing time-dependent control fields, even for cases that are difficult to converge with existing gradient-based approaches. We provide detailed descriptions of our machine learning methods as well as performance metrics for a variety of machine learning algorithms. Taken together, our results demonstrate that BO is a promising approach to efficiently and autonomously design control fields in general quantum dynamical systems.

Computer Science↗
DOE OSTI2020

Enhancing Heavy-Oil-Recovery Efficiency by Combining Low-Salinity-Water and Polymer Flooding

Summary Combining low-salinity-water (LSW) and polymer flooding was proposed to unlock the tremendous heavy-oil resources on the Alaska North Slope (ANS). The synergy of LSW and polymer flooding was demonstrated through coreflooding experiments at various conditions. The results indicate that the high-salinity polymer (HSP) (salinity = 27,500 ppm) requires nearly two-thirds more polymer than the low-salinity polymer (LSP) (salinity = 2,500 ppm) to achieve the target viscosity at the condition of this study. Additional oil was recovered from LSW flooding after extensive high-salinity-water (HSW) flooding [3 to 9% of original oil in place (OOIP)]. LSW flooding performed in secondary mode achieved higher recovery than that in tertiary mode. Also, the occurrence of water breakthrough can be delayed in the LSW flooding compared with the HSW flooding. Strikingly, after extensive LSW flooding and HSP flooding, incremental oil recovery (approximately 8% of OOIP) was still achieved by LSP flooding with the same viscosity as the HSP. The pH increase of the effluent during LSW/LSP flooding was significantly greater than that during HSW/HSP flooding, indicating the presence of the low-salinity effect (LSE). The residual-oil-saturation (Sor) reduction induced by the LSE in the area unswept during the LSW flooding (mainly smaller pores) would contribute to the increased oil recovery. LSP flooding performed directly after waterflooding recovered more incremental oil (approximately 10% of OOIP) compared with HSP flooding performed in the same scheme. Apart from the improved sweep efficiency by polymer, the low-salinity-induced Sor reduction also would contribute to the increased oil recovery by the LSP. A nearly 2-year pilot test in the Milne Point Field on the ANS has shown impressive success of the proposed hybrid enhanced-oil-recovery (EOR) process: water-cut reduction (70 to less than 15%), increasing oil rate, and no polymer breakthrough so far. This work has demonstrated the remarkable economical and technical benefits of combining LSW and polymer flooding in enhancing heavy-oil recovery.

Engineering↗
DOE OSTI2025

Spin State Modulation via Magnetic Fields in Fe Single Atom Catalysts for High-Performance Aqueous Zinc–Sulfur Batteries

Aqueous zinc–sulfur battery has garnered significant attention as a high-energy, low-cost, and safe energy storage system. However, the multielectron transfer kinetics of sulfur cathodes are relatively slow, presenting challenges such as limited sulfur utilization and lower discharge voltage, which significantly hinder their practical applications. Here, in this study, we explored a comprehensive design approach for high-performance, long-cycle aqueous zinc–sulfur batteries. The simultaneous introduction of ZnI 2 and Fe single atoms (Fe-SAs) as catalytically active agents decouples the redox reactions, effectively facilitating ZnS oxidation and S reduction separately. The application of an external magnetic field regulates the spin state of Fe-SAs, further enhancing their catalytic activity and electron transfer capability. Electrochemical tests demonstrate that the S@Fe-NC HS/ZnI 2 cathode assembled under a magnetic field exhibits excellent rate performance, achieving an impressive specific capacity of 1399 mAh g –1 at a high current density of 5 A g –1 and good cycling stability over 300 cycles, representing the highest reported high-current discharge capacity to date. This study provides a comprehensive design framework for optimizing zinc–sulfur (Zn–S) battery performance and elucidates the influence of magnetic field-induced spin state modulation on catalytic behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accelerated impurity solver for DMFT and its diagrammatic extensions

Here, we present ComCTQMC, a GPU accelerated quantum impurity solver. It uses the continuous-time quantum Monte Carlo (CTQMC) algorithm wherein the partition function is expanded in terms of the hybridisation function (CT-HYB). ComCTQMC supports both partition and worm-space measurements, and it uses improved estimators and the reduced density matrix to improve observable measurements whenever possible. ComCTQMC efficiently measures all one and two-particle Green's functions, all static observables which commute with the local Hamiltonian, and the occupation of each impurity orbital. ComCTQMC can solve complex-valued impurities with crystal fields that are hybridized to both fermionic and bosonic baths. Most importantly, ComCTQMC utilizes graphical processing units (GPUs), if available, to dramatically accelerate the CTQMC algorithm when the Hilbert space is sufficiently large. We demonstrate acceleration by a factor of over 600 (100) in a simulation of δ-Pu at 600 K with (without) crystal fields. In easier problems, the GPU offers less impressive acceleration or even decelerates the CTQMC. Here we describe the theory, algorithms, and structure used by ComCTQMC in order to achieve this set of features and level of acceleration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Performance of Low Salinity Polymer Flood in Enhancing Heavy Oil Recovery on the Alaska North Slope

Combining low-salinity water (LSW) and polymer flooding was proposed to unlock the tremendous heavy oil resources (20–25 billion barrels) on the Alaska North Slope (ANS). The synergy effect of LSW and polymer flooding was demonstrated through coreflooding experiments carried out on representative rock and fluid systems. The results indicate that the high-salinity polymer solution (HSP, 2,300 ppm, salinity=27,500 ppm) requires nearly two thirds more polymer than the low-salinity polymer (LSP, 1,400 ppm, salinity=2,500 ppm) to achieve the same target viscosity of 45 cp measured from viscometer. Additional oil (5–9%) can be recovered from LSW flooding after extensive high-salinity water (HSW) flooding. LSW flooding performed in secondary mode can achieve higher recovery than in tertiary mode. Strikingly, LSP flooding can further improve the oil recovery by ~8% even after extensive HSP flooding with the same viscosity. LSP flooding performed directly after waterflooding can achieve ~10% more incremental oil recovery. The pH increase of the effluent during LSW/LSP flooding was significantly greater than that during HSW/HSP flooding, indicating the occurrence of ion exchange which might contribute to the improved oil recovery. Also, the water breakthrough was delayed in a low-salinity flood compared with a high-salinity flood. The idea of combining LSW and polymer flooding has been put into practice on a pattern-scale field pilot test in the target Milne Point field. Nearly two-year observation has shown impressive success: water cut reduction (70% to below 15%), increasing oil rate, and no polymer breakthrough so far. This work has demonstrated remarkable economical and technical benefits of combination of LSW and polymer flooding in enhancing heavy oil recovery.

Zhao, Yang↗
DOE OSTI2021

Directional Recoil Detection

Searches for dark matter–induced recoils have made impressive advances in the last few years. Yet the field is confronted by several outstanding problems. First, the inevitable background of solar neutrinos will soon inhibit the conclusive identification of many dark matter models. Second, and more fundamentally, current experiments have no practical way of confirming a detected signal's Galactic origin. The concept of directional detection addresses both of these issues while offering opportunities to study novel dark matter– and neutrino-related physics. The concept remains experimentally challenging, but gas time projection chambers are an increasingly attractive option and, when properly configured, would allow directional measurements of both nuclear and electron recoils. In this review, we reassess the required detector performance and survey relevant technologies. Fortuitously, the highly segmented detectors required to achieve good directionality also enable several fundamental and applied physics measurements. As a result, we comment on near-term challenges and how the field could be advanced.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Mathematics: The Tao of Data Science

The two pieces, "Ten Research Challenge Areas in Data Science" by Jeannette M. Wing and “Challenges and Opportunities in Statistics and Data Science: Ten Research Areas” by Xuming He and Xihong Lin, provide an impressively complete list of data science challenges from luminaries in the field of data science. They have done an extraordinary job, so this response offers a complementary viewpoint from a mathematical perspective and evangelizes advanced mathematics as a key tool for meeting the challenges they have laid out. Notably, we pick up the themes of scientific understanding of machine learning and deep learning, computational considerations such as cloud computing and scalability, balancing computational and statistical considerations, and inference with limited data. We propose that mathematics is an important key to establishing rigor in the field of data science and as such has an essential role to play in its future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Force field for calcium sulfate minerals to predict structural, hydration, and interfacial properties

Calcium sulfates such as anhydrite, hemihydrate, and gypsum find widespread use in building materials, implants, and tissue healing. We introduce a simple and compatible atomistic force field for all calcium sulfate phases that reproduces a wide range of experimental data including lattice parameters, surface, hydration, mechanical, and thermal properties in 1% to 5% accuracy relative to experiments. The performance is several times better than prior force fields and DFT methods, which lead to errors in structures and energies up to 100%. We explain (hkl) cleavage energies, the dynamics of (hkl) water interfaces, and new insights into molecular origins of crystal-facet specific hydration and solubility. Impressive agreement of computed and experimentally measured hydration energies is shown. The models add to the Interface force field (IFF) and are compatible with multiple force fields (CHARMM, AMBER, GROMOS, CVFF, PCFF, OPLS-AA) for property predictions of sulfate-containing materials from atoms to the large nanometer scale.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of twist pitch on hysteretic losses and transport J c in overpressure processed high J c Bi-2212 round wires

Abstract Bi-2212 is the only high field, high-temperature superconductor (HTS) available in the macroscopically isotropic, multifilament high J c round wire (RW) form capable of generating high uniformity fields with minimum-screening current errors. However, the heat treatment that enables impressively high J c (4.2 K, 30 T) values that can attain ∼5000 A mm −2 also produces significant filament bonding (bridging). Filament bridging appears to significantly enhance hysteretic losses of the filaments themselves by coupling neighboring, nominally independent filaments, enabling shielding currents to flow across multiple filaments as though they were one filament of much larger diameter. Wire twisting can be employed to reduce filament-to-filament eddy current coupling losses due to induced currents flowing across the matrix, but twisting is less effective in reducing increased losses from bridging. Here, we compare the twist-pitch dependence of the losses of overpressure processed (OP) high J c Bi-2212 RWs with partially bridged filaments to those found in OP Bi-2212 RWs with discrete, not-bridged filaments. We show that filament sub-bundles in standard, partially-bridged wires that have some superconducting connections between filaments can exhibit significant coupling (much larger effective filament diameter), but twisting still reduces their hysteretic losses to values close to or below the ITER Nb 3 Sn wire loss specification, even though Bi-2212 wires have significantly larger J c values. Although it has been reported that twisting can reduce wire J c by damaging filaments, we found no reduction in transport J c , even for nominal twist pitches of 12 mm in 0.8 mm diameter wires. Evaluation of more-recent, higher J c Engi-Mat powder wires showed that their reduced filament bridging and improved longitudinal connectivity significantly improved transport J c and reduced the J c normalized losses, signaling that J c can be further improved without commensurate increase in losses. This important result strengthens the argument for production of high field, low loss HTS magnets made with Bi-2212 RWs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Nuclear data resources and initiatives for nuclear astrophysics

Research into the cosmic synthesis of the elements, the evolution and explosion of stars, the nature of the early Universe, and other important topics in nuclear astrophysics are at the forefront of nuclear science. These studies are motivating laboratory measurements and theoretical calculations that, after significant investments, are pushing the boundaries of what is possible. The latest nuclear results, however, must be specially prepared before they can be used to advance our knowledge of the cosmos. This processing requires a set of resources unique to nuclear astrophysics, and an impressive collection of nuclear reaction and nuclear structure datasets, processing codes, thermonuclear reaction rate libraries, and simulation codes and services have been developed for the field. There are, however, some serious challenges to these efforts that will only worsen in the future, making it important to develop strategies and act now to ensure a sustainable future for this work. After detailing the specific data types needed for nuclear astrophysics and the available data resources, the major challenges in this work and their implications are discussed. A set of initiatives are proposed to meet those challenges along with suggested implementations and possible ways that they may advance our understanding of the Universe and strengthen the field of nuclear astrophysics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Defect tolerance in halide perovskites: A first-principles perspective

In recent years, the impressive photovoltaic performance of halide perovskites has been commonly attributed to their defect tolerance. This attribution is seemingly intuitive and has been widely promoted in the field, though it has not been rigorously assessed. In this Perspective, we critically discuss the proposition of defect tolerance in halide perovskites based on first-principles calculations. We show that halide perovskites actually do suffer from defect-assisted nonradiative recombination, i.e., they are not defect tolerant. The nonradiative recombination rates in halide perovskites are comparable to or even greater than those in more conventional semiconductors. We note that to obtain accurate defect properties in halide perovskites, the level of theory and computational details are highly important, which was previously not sufficiently recognized. A distinctive feature of halide perovskites is that they can be grown with moderate defect densities using low-cost deposition techniques. But, similar to the case of conventional semiconductors, defect engineering is still key to improving the efficiency of perovskite solar cells.

14 SOLAR ENERGY↗
DOE OSTI2024

300_underground robot (final research report)

Recent advancements in mobile robotics have displayed impressive capabilities in traversing and accessing areas that are inaccessible to humans either due to the characteristics of the environment or potential hazards. Furthermore, these advancements within the field of mobile robotics, more specifically uncrewed ground vehicles (UGVs), give the ability to potentially survey, observe, and map these inaccessible areas for humans. However, one of the most challenging areas to implement this technology is underground environments. The main challenge with implementing this technology in underground environments is the dependence on either GPS or RF communication for UGVs to navigate properly. Therefore, in order to properly demonstrate the mapping capabilities of the UGV this challenge must be resolved. The overall goal of this study is to demonstrate the mapping capabilities of a UGV while addressing this challenge and documenting the implementation and testing phase of the robot. The proposed solution to this challenge is to implement a SLAM algorithm onto the main computational device of the UGV utilizing the Robot Operating System (ROS). The algorithm is the open-source software package Slam Toolbox developed by Steve Macenski. Furthermore, the sllidar_ros2 package from Slamtec will be used to gather the lidar data from an A3M1 2D lidar. A separate program will be created to gather odometry information for our UGV robot. All of these software packages will run together in a Docker environment. Through working on this project I have developed a better understanding of the world of robotics/autonomous systems, especially with applications such as navigation and mapping. Furthermore, through this project, I have been given exposure to how research is conducted within a DOE lab setting. As robotics/autonomous systems become more advanced it's important to pursue more avenues of research such as this project as it will ensure the development of our capabilities.

42 ENGINEERING↗
DOE OSTI2022

High performance FPGA embedded system for machine learning based tracking and trigger in sPhenix and EIC

We present a comprehensive end-to-end pipeline to classify triggers versus background events in this paper. This pipeline makes online decisions to select signal data and enables the intelligent trigger system for efficient data collection in the Data Acquisition System (DAQ) of the upcoming sPHENIX and future EIC (Electron-Ion Collider) experiments. Starting from the coordinates of pixel hits that are lightened by passing particles in the detector, the pipeline applies three-stage of event processing (hits clustering, track reconstruction, and trigger detection) and labels all processed events with the binary tag of trigger versus background events. The pipeline consists of deterministic algorithms such as clustering pixels to reduce event size, tracking reconstruction to predict candidate edges, and advanced graph neural network-based models for recognizing the entire jet pattern. In particular, we apply the message-passing graph neural network to predict links between hits and reconstruct tracks and a hierarchical pooling algorithm (DiffPool) to make the graph-level trigger detection. We obtain an impressive performance (≥70% accuracy) for trigger detection with only 3200 neuron weights in the end-to-end pipeline. We deploy the end-to-end pipeline into a field-programmable gate array (FPGA) and accelerate the three stages with speedup factors of 1152, 280, and 21, respectively.

Instruments & Instrumentation↗
DOE OSTI2022

The 2022 magneto-optics roadmap

Abstract Magneto-optical (MO) effects, viz. magnetically induced changes in light intensity or polarization upon reflection from or transmission through a magnetic sample, were discovered over a century and a half ago. Initially they played a crucially relevant role in unveiling the fundamentals of electromagnetism and quantum mechanics. A more broad-based relevance and wide-spread use of MO methods, however, remained quite limited until the 1960s due to a lack of suitable, reliable and easy-to-operate light sources. The advent of Laser technology and the availability of other novel light sources led to an enormous expansion of MO measurement techniques and applications that continues to this day (see section 1). The here-assembled roadmap article is intended to provide a meaningful survey over many of the most relevant recent developments, advances, and emerging research directions in a rather condensed form, so that readers can easily access a significant overview about this very dynamic research field. While light source technology and other experimental developments were crucial in the establishment of today’s magneto-optics, progress also relies on an ever-increasing theoretical understanding of MO effects from a quantum mechanical perspective (see section 2), as well as using electromagnetic theory and modelling approaches (see section 3) to enable quantitatively reliable predictions for ever more complex materials, metamaterials, and device geometries. The latest advances in established MO methodologies and especially the utilization of the MO Kerr effect (MOKE) are presented in sections 4 (MOKE spectroscopy), 5 (higher order MOKE effects), 6 (MOKE microscopy), 8 (high sensitivity MOKE), 9 (generalized MO ellipsometry), and 20 (Cotton–Mouton effect in two-dimensional materials). In addition, MO effects are now being investigated and utilized in spectral ranges, to which they originally seemed completely foreign, as those of synchrotron radiation x-rays (see section 14 on three-dimensional magnetic characterization and section 16 on light beams carrying orbital angular momentum) and, very recently, the terahertz (THz) regime (see section 18 on THz MOKE and section 19 on THz ellipsometry for electron paramagnetic resonance detection). Magneto-optics also demonstrates its strength in a unique way when combined with femtosecond laser pulses (see section 10 on ultrafast MOKE and section 15 on magneto-optics using x-ray free electron lasers), facilitating the very active field of time-resolved MO spectroscopy that enables investigations of phenomena like spin relaxation of non-equilibrium photoexcited carriers, transient modifications of ferromagnetic order, and photo-induced dynamic phase transitions, to name a few. Recent progress in nanoscience and nanotechnology, which is intimately linked to the achieved impressive ability to reliably fabricate materials and functional structures at the nanoscale, now enables the exploitation of strongly enhanced MO effects induced by light–matter interaction at the nanoscale (see section 12 on magnetoplasmonics and section 13 on MO metasurfaces). MO effects are also at the very heart of powerful magnetic characterization techniques like Brillouin light scattering and time-resolved pump-probe measurements for the study of spin waves (see section 7), their interactions with acoustic waves (see section 11), and ultra-sensitive magnetic field sensing applications based on nitrogen-vacancy centres in diamond (see section 17). Despite our best attempt to represent the field of magneto-optics accurately and do justice to all its novel developments and its diversity, the research area is so extensive and active that there remains great latitude in deciding what to include in an article of this sort, which in turn means that some areas might not be adequately represented here. However, we feel that the 20 sections that form this 2022 magneto-optics roadmap article, each written by experts in the field and addressing a specific subject on only two pages, provide an accurate snapshot of where this research field stands today. Correspondingly, it should act as a valuable reference point and guideline for emerging research directions in modern magneto-optics, as well as illustrate the directions this research field might take in the foreseeable future.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Perovskite on Silicon Tandem Solar Cells

Since installing solar panels costs more than the panels themselves, it is critically important to improve the efficiency of the panels so that fewer panels need to be installed. More than 90% of all panels being manufactured are made with silicon solar cells. The most promising approach to reach 27% is to upgrade the panels by adding a second set of cells with a larger band gap that can harvest the higher energy photons in the visible spectrum and generate a higher voltage than silicon is capable of generating. Perovskite semiconductors are very promising for low-cost tandems because they have high band gaps, can be rapidly printed from solutions and have been used to make 25% efficient cells by themselves. If we show that it is possible to make stable tandems with 30% efficiency using materials that could be deposited at low cost and that the energy yield will not be compromised, then private companies would be able to raise the capital needed to manufacture this technology. The main metrics for this project are the power conversion efficiency of a lab-scale perovskite/silicon tandem and the ability to maintain a high power conversion efficiency in perovskite solar cells after accelerated operational stability testing under maximum power point at elevated temperature and 1 sun illumination. In short, this project demonstrates improvements to the perovskite absorber layer, contacts for the perovskite solar cell, and transparent oxide layers for window electrodes to achieve tandem efficiencies of 25% after one year and 27% after two years. By the end of the project, we identify strategies to further improve light management in the tandem devices and outline a pathway to reach 30%.In parallel, stability testing is conducted to evaluate said absorber and contact layers in the perovskite top cell, demonstrating 1000 hours of operation with less than 10% degradation at 1 sun. Our work on this project has made a leading impact on the development of perovskite/silicon tandems. The triple halide perovskite that we developed using iodide, bromide, and chloride and published in Science in March 2020 has received significant interest from other experts in the field at conferences. We took a silicon bottom cell with 21% efficiency, a technology that is responsible for a $30 billion market, and improved it by 30% relative. In addition, we have demonstrated impressive stability of our perovskite semitransparent top cells used in the tandems, showing for the first time packaged devices that pass a variety of IEC stability tests including damp heat, temperature cycling, and UV exposure tests.

14 SOLAR ENERGY↗