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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Grid-Forming PV Inverter: Technology Development and Microgrid Applications

Presently, excluding residential backup power applications, grid-forming (GFM) inverters are commercially available for battery energy storage system (BESS) and some PV plus battery systems but not yet for stand-alone PV. This tech update investigates the control design for GFM PV inverter, especially the control required to provide active power reserve and to stabilize the dc link voltage. Subsequently, the use cases of GFM PV plants in utility-level microgrids are discussed considering fully inverter-based microgrids (i.e., with PV and BESS) as well as mixed-source microgrids (i.e., with PV and diesel generator). Scenarios where active power up-reserve from GFM PV plants is beneficial are illustrated. Moreover, requirements and specifications for GFM PV plant, especially for its active power reserve function are developed. In addition, stability of an example utility-level microgrid with two GFM PV plants and a diesel generator is analyzed to shed light on the potential unstable interaction between multiple GFM resources and the countermeasures. This research aims to advance GFM PV technology to offer more flexibility in microgrid design. With GFM PV available, depending on the level of reliability required, cost-benefit analysis, etc., the GFM BESS or diesel generator may be sized smaller while leveraging the full potential of PV generation inside the microgrid.

14 SOLAR ENERGY↗
DOE OSTI2024

Self‐Potential Tomography Preconditioned by Particle Swarm Optimization—Application to Monitoring Hyporheic Exchange in a Bedrock River

Abstract A self‐potential (SP) data‐inversion algorithm was developed and tested on an analytical model of electrical‐potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP‐monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock‐lined riverbed. The algorithm combined stochastic source‐localization by particle‐swarm‐optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least‐squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical‐model data to evaluate the algorithm performance. Results indicated that true parameters of single‐source models were inverted and approximated with small residual error, whereas inversion of analytical‐model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non‐uniqueness of the inverse‐model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point‐scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP‐monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Performance Evaluation of Three RTU Energy Efficiency Technologies

This project was part of an effort by CLEAResult and ComEd to evaluate the energy saving potential of emerging technologies in the Chicago area. This project focused on evaluating emerging technologies related to rooftop units (RTUs). An RTU with a single-stage compressor and a constant-speed fan with an induction motor was selected as the baseline for technology comparison. Three retrofit strategies were investigated. The first two involved replacing the single-stage compressor of an RTU by either a two-stage or variable-speed compressor and adding a variable frequency drive (VFD) to the constant speed fan. The use of a multi-/variable-stage compressor improves the part-load efficiency of the compressor which will ultimately result in annual energy savings as well as peak demand shaving in some cases where the design capacity of the RTU is larger than the maximum cooling load of the building space that it is serving. The third technology was the use of a high rotor pole switched reluctance motor (SRM) as a replacement for the constant-speed supply fan. The SRM was applied in single-speed, two-stage and variable-speed compressor RTUs. SRM motors run via reluctance torque. Their stator poles are driven by direct current (DC) power and require an inverter as well as active control when using alternating current (AC) power. This inherent property results in high efficiency over a range of operating conditions. It also exhibits higher efficiency compared to variable frequency drives (VFDs) since its switching frequency is much slower (SCE, 2018).The three technologies investigated are summarized below: 1) Replacing the single-speed compressor with a two-stage compressor and adding a VFD to the supply fan. 2)Replacing the single-speed compressor with a variable-speed compressor and adding a VFD to the supply fan. 3) Replacing the constant-speed induction motor of the supply fan with a high rotor pole SRM. DOE’s building simulation platform EnergyPlus and its graphical user interface OpenStudio were used to evaluate the energy-saving potential of upgrading RTUs, by leveraging experimental data from previous research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A review of active probing-based system identification techniques with applications in power systems

System identification is becoming a relevant research area for numerous applications in power grids due to the increasing complexity of the system. A paradigm shift in power system infrastructure driven by renewable energy resources, controllable loads, and new power electronics technologies have given rise to new challenges in power systems operation and control. This increased complexity of power systems and unavailability of physics-based models of most inverter-based resources requires that traditional modeling of power systems approaches be complemented by system identification-based black or grey box modeling techniques. In light of the importance of system identification and little attention paid to the applications of these techniques in transforming power systems, this paper provides a comprehensive review of active probing-based system identification methods in the context of power system applications. It reviews applications of both linear and nonlinear system identification with discussion on their potential and key takeaways. To motivate a further practical use in power systems, the paper provides an example of system identification, to develop a state space model of an unknown plant with step-by-step details. The paper highlights the advantages of using modern power electronics-based sources in the identification process and discusses the emerging research directions for future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Sensitivity Analysis and Control of Induction Cooktop for Non-Ferromagnetic Cookware

All metal induction cooktop has the potential to enable heating of both ferromagnetic and non-ferromagnetic cookware. Compared to ferromagnetic cookware, the performance of an induction cooktop with non-ferromagnetic cookware is impacted significantly by the cookware misalignment. A detailed sensitivity analysis to the cookware misalignment for non-ferromagnetic cookware is studied in this paper. Based on the analysis, a control architecture is presented which ensures desired power transfer to the non-ferromagnetic cookware and zero voltage turn on of the high frequency inverter irrespective of cookware misalignment. Results are presented to verify the analysis and proposed control strategy.

Mukherjee, Subho [ORNL] (ORCID:0009000672297925)↗
DOE OSTI2024

2022 Component Innovation Awardee: Windurance

Combining battery energy storage with distributed wind energy systems can increase production, ability to meet local electricity demands, interconnection capacity, and potential sales of surplus energy back to the grid, while reducing demand charges and the overall levelized cost of energy (LCOE). Energy storage options for distributed wind energy systems can vary widely in terms of power level and energy storage capacity, and their potential benefits depend on factors including wind resource, turbine design, connection requirements, use patterns, utility rates, and regulations. Windurance received a 2022 Competitiveness Improvement Project (CIP) funding award to add battery energy storage capabilities to the company's bidirectional DC converter. The energy storage component will complete a comprehensive portfolio of power conversion and control electronics that can be seamlessly integrated with distributed wind systems. The company received earlier CIP awards to fund prototype design and construction of wind turbine pitch actuators, inverters, and controllers.

CIP↗
DOE OSTI2026

Asynchronous Grid Connections Providing Fast-Frequency Response: System Integration Study

This paper presents an integration study for the recent power electronic-based fast-frequency response technology, "asynchronous grid connection" which operates as an aggregator for behind-the-meter resources and distributed generators. Both technical feasibility and techno-economic viability studies are presented. The fast-frequency response characteristics, validated against Power Hardware-in-the-Loop experiments, are integrated into an IEEE 9- bus system in DigSilent PowerFactory for system-level dynamic analysis. It demonstrates that droop-based control enhancements to local distributed generators allow their aggregation to provide grid-supporting functionalities and participate in the ancillary service markets. To this end, a long-term simulation embedding the system within the ancillary service market framework of PJM has been performed. The fast-frequency response regulation is subsequently used to calculate the potential revenue and project the results on a 15-year investment horizon. Finally, the techno-economic analysis provides recommendations for enhancements to access the full potential of distributed generators on a technical and regulatory level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Robust Restoration From Cyber-Physical Attacks in Active Distribution Grids With Grid-Edge IBRs

The inverter-based resources (IBRs) have enabled the integration of renewable energy at the grid edge with enhanced control capabilities to support the reliable operation of power grids. Different control frameworks, such as hierarchical or distributed architecture, have been proposed with the expansion of cyber networks for real-time monitoring and control. This evolution of critical infrastructure into cyber-physical systems also brings more vulnerabilities for the broadened attack surfaces, and significantly increases the possibility of physical system failures or outages caused by cyberattacks. Among tremendous efforts in the defense-in-depth approach, it remains challenging to provide prompt detection and accurate location of attack entry points or paths. Therefore, the prevailing restoration framework may struggle to fully consider the cyber-physical interdependence, successfully isolate the compromised cyber and physical components, and safely recover the systems without the potential risks leading to secondary outages. This paper is motivated to develop a cyber-physical restoration framework for distribution grids to recover from cyber attacks by harnessing grid-edge IBRs. The framework is first built on the operational guidelines of IBRs considering the compromised cyber layer. Then, an ambiguity set is established to represent the uncertainty of attack scenarios and their possibility levels. Next, a distributionally robust optimization model is developed to provide the optimal load restoration strategy across all scenarios. The effectiveness of the proposed model is demonstrated through various use cases on the modified IEEE 13-node and 123-node test systems. Finally, simulation results demonstrate the effectiveness and advancement of developed post-attack restoration strategies.

Cybersecurity↗
DOE OSTI2023

Using the Gerchberg-Saxton algorithm to reconstruct nonmodulated pyramid wavefront sensor measurements

Adaptive optics (AO) is a technique to improve the resolution of ground-based telescopes by correcting, in real-time, optical aberrations due to atmospheric turbulence and the telescope itself. With the rise of Giant Segmented Mirror Telescopes (GSMT), AO is needed more than ever to reach the full potential of these future observatories. One of the main performance drivers of an AO system is the wavefront sensing operation, consisting of measuring the shape of the above mentioned optical aberrations. Aims. The non-modulated pyramid wavefront sensor (nPWFS) is a wavefront sensor with high sensitivity, allowing the limits of AO systems to be pushed. The high sensitivity comes at the expense of its dynamic range, which makes it a highly non-linear sensor. We propose here a novel way to invert nPWFS signals by using the principle of reciprocity of light propagation and the Gerchberg-Saxton (GS) algorithm. We test the performance of this reconstructor in two steps: the technique is first implemented in simulations, where some of its basic properties are studied. Then, the GS reconstructor is tested on the Santa Cruz Extreme Adaptive optics Laboratory (SEAL) testbed located at the University of California Santa Cruz. This new way to invert the nPWFS measurements allows us to drastically increase the dynamic range of the reconstruction for the nPWFS, pushing the dynamics close to a modulated PWFS. The reconstructor is an iterative algorithm requiring heavy computational burden, which could be an issue for real-time purposes in its current implementation. However, this new reconstructor could still be helpful in the case of many wavefront control operations. In conclusion, this reconstruction technique has also been successfully tested on the Santa Cruz Extreme AO Laboratory (SEAL) bench where it is now used as the standard way to invert nPWFS signal.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Three-dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep-learning techniques

Using multiple geophysical methods has become a prevailing approach in numerous geophysical applications to investigate subsurface structures and parameters. These multimethod-based exploration strategies have the potential to greatly diminish uncertainties and ambiguities encountered during geophysical data analysis and interpretation. One of the applications is the cooperative inversion of airborne magnetic and gravity gradient data for the interpretation of data obtained in mineral, oil and gas, and geothermal explorations. In this paper, a unified cooperative inversion framework is designed by combining the standard separate inversions with a deep neural network (DNN), which serves as the link between different types of data. A well-trained DNN takes the separately inverted susceptibility and density models as the inputs and provides improved models that will be used as the initial models of deterministic inversions. A two-round iteration strategy is adopted to guarantee the reasonability of the recovered models and overall efficiency of the inversion. In addition, this deep-learning (DL)-based framework demonstrates excellent generalization abilities when tested on models that are entirely distinct from the training data sets. The framework can easily incorporate multiphysics without necessitating any structural changes to the network. Synthetic experiments validate that our DL-based method outperforms conventional separate inversions and cross-gradient-based joint inversion in view of the accuracy of the recovered models and inversion efficiency. Successful application to field data further verifies the effectiveness of our DL-based method.

Geochemistry & Geophysics↗
DOE OSTI2020

Runaway electron beam dynamics at low plasma density in DIII-D: energy distribution, current profile, and internal instability

Parameters of the post-disruption runaway electron (RE) beam in the collisionless background plasma achieved after deuterium injection are investigated in DIII-D. The spatially resolved RE energy distribution function is measured for the first time during the RE plateau stage by inverting hard X-ray bremsstrahlung spectra. It has maximum energy up to 20 MeV and a non-monotonous feature at 5{6 MeV observed only in the core of the beam supporting the possibility of kinetic instabilities. The RE current profile is reconstructed for the first time using the spatially resolved RE energy distribution. It is found to be more peaked than the pre-disruption plasma current, with higher internal inductance, suggesting preferential formation of REs in the core plasma or potentially a radially inward motion of the REs. The accessed relatively low-current (180 kA) RE beam is found stable, likely due to its elevated q profile. From this base stable equilibrium, instability is accessed by ramping the solenoid current. Under a large applied accelerating loop voltage an internal kink mode is observed. The kink mode leads to sawtooth-like relaxation of the RE current profile, but drives no RE loss. Under conditions of a large decelerating voltage, chirping Alfvénic instabilities driven by REs during the RE plateau stage are observed for the first time. The low-frequency (0.1{7 MHz) Alfvénic instabilities, supposedly compressional Alfvén eigenmodes, are found to be correlated with a RE loss signal. Finally, this provides novel plasma conditions to study these instabilities and investigate opportunities to utilize them for RE control. Bifurcated electron cyclotron emission (ECE) spectrum is measured during the collisionless RE plateau, with a break point at ≈100 GHz suggesting resonant absorption of the ECE at low frequencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

OASIS: Offsetting Active Reconstruction Attacks in Federated Learning

Federated Learning (FL) has garnered significant attention for its potential to protect user privacy while enhancing model training efficiency. For that reason, FL has found its use in various domains, from health care to industrial engineering, especially where data cannot be easily exchanged due to sensitive information or privacy laws. However, recent research has demonstrated that FL protocols can be easily compromised by active reconstruction attacks executed by dishonest servers. These attacks involve the malicious modification of global model parameters, allowing the server to obtain a verbatim copy of users' private data by inverting their gradient updates. Tackling this class of attack remains a crucial challenge due to the strong threat model. In this paper, we propose a defense mechanism, namely OASIS, based on image augmentation that effectively counteracts active reconstruction attacks while preserving model performance. We first uncover the core principle of gradient inversion that enables these attacks and theoretically identify the main conditions by which the defense can be robust regardless of the attack strategies. We then construct our defense with image augmentation showing that it can undermine the attack principle. Comprehensive evaluations demonstrate the efficacy of the defense mechanism highlighting its feasibility as a solution.

deep neural networks↗
DOE OSTI2021

Adapting confocal Raman microscopy for in situ studies of redox transformations at electrode-electrolyte interfaces

Confocal Raman microscopy was applied to quantify redox species present within the diffusion layer adjacent to an electrode surface under potentiostatic control. A glass microscope coverslip with a thin indium tin oxide (ITO) coating served as both the working electrode and optical window for a microscope-stage mountable spectroelectrochemical cell. A high numerical aperture objective mounted in an inverted microscope frame just below the stage brought excitation radiation through the coverslip window and to a tight focus a few micrometers above the ITO film surface. Species diffusing into the confocal probe volume defined by the excitation beam focus and the collected light region were detected, identified and quantified based on their Raman scattering frequencies and intensities. Here, in measurements that interrogated the interconversion of ferrocyanide and ferricyanide ions as a function of applied voltage, least-squares regression analysis of spectral datasets predicted the formal potential and relative surface concentrations of the ions in good agreement with the expected Nernstian response. Preliminary studies of methyl viologen reduction at an ITO film/Nafion membrane interface were conducted and show the possibility for estimation of mass transport coefficients of redox species within ionic polymer materials.

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

Ensuring thermodynamic consistency with invertible coarse-graining

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Effects of temperature inversion on densification in chemical vapor infiltration

In a classical chemical vapor infiltration (CVI) process, the competing effects of chemical kinetics and reagent gas transport lead to non–uniform depositions such that outer layers of a preform densify faster leaving the core highly porous. Currently, CVI must be performed at a sufficiently low temperature to achieve good densification quality which leads to high processing time and cost. Volumetric heating of the preform, especially through microwaves, can create temperature inversion such that the core is hotter than the outer surface and potentially, overcome the challenges associated with isothermal CVI. Direct numerical simulations (DNS) of densification under various such temperature distributions indicate that microwave heating in CVI processing can lead to better (uniform) densification of porous preforms. Here the role of key parameters describing the temperature distributions on the densification behavior is investigated. Strategic temporal control of the temperature distribution shows that processing times can be reduced by almost half while maintaining a good densification quality similar to that of low–temperature isothermal processing. Inside–out densification due to the inverted temperature profile is a key distinguishing characteristic of microwave assisted CVI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Topology-Aware Reinforcement Learning for Voltage Control: Centralized and Decentralized Strategies

Volt-VAR control (VVC) methods based on deep reinforcement learning (DRL) can effectively control distribution grid voltage and minimize power loss by implementing corrective and preventive control measures on the reactive power output of inverter-based distributed energy resources (DERs). However, model-free DRL-based VVC approaches usually cannot capture the important topological feature of the power system since they use a fully-connected network (FCN) to deliver the action. Therefore, this paper proposes a graph convolutional network (GCN)-based DRL approach that can employ the topological information of the network to take better control action for regulating the voltage. Our implementation allows for both centralized and decentralized configurations, utilizing a single agent and multiple agents respectively. Although the centralized GCN-based DRL approach has its advantages of minimizing voltage fluctuation and power loss, it is not suitable for large scale power systems due to its challenges in terms of scalability, computation speed and potential single points of failure. Therefore, these problems can be resolved using the decentralized GCN-based DRL approach. Moreover, to ensure the safe operation of the model, our proposed approach incorporates an exponential barrier function while formulating the reward function for each agent. To validate performance of the proposed approaches, the proposed model is tested on modified IEEE test systems and the performances are measured in terms on voltage fluctuation reduction, minimization of power loss and computational speed. Finally, the results show that the proposed topology-aware approach outperforms the FCN-based DRL approach in terms of reducing voltage fluctuation and minimizing power loss of the network. Moreover, it is shown that the decentralized GCN-based DRL has faster computational speed than other approaches.

42 ENGINEERING↗
DOE OSTI2020

Tin–Lead Alloying for Efficient and Stable All-Inorganic Perovskite Solar Cells

Cesium containing all-inorganic perovskites have received considerable interest in photovoltaics research because of their potential for improved stability compared to their organic-inorganic hybrid counterparts. However, the inorganic perovskites studied thus far still suffer from lower power conversion efficiency and long-term instability, due to an unfavorable bandgap and either phase instability or air-sensitivity. Herein, A strategy to mitigate these concerns is investigated by alloying tin and lead on the B site to form tin-lead alloyed low-bandgap (~1.34 eV) inorganic CsSn 0.3 Pb 0.7 I 3 perovskites. Solar cells made using this material in an inverted full-structured architecture with a PEDOT:PSS hole transport materials (HTM) attain power conversion efficiency (PCE) up to 9.41% (stabilized PCE 7.23%). Furthermore, a simple HTM-free device without PEDOT:PSS layer is demonstrated more stable than the full-structured device and exhibits a PCE of 7.60% (stabilized PCE 7.31%) – the highest efficiency to date for an inorganic perovskite with a bandgap below 1.40 eV. This simplified device structure shows good reproducibility and stability. Finally, this work provides a possible route for fabricating low-cost, high stability devices with competitive efficiencies.

14 SOLAR ENERGY↗