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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Organic Photovoltaic Efficiency Predictor: Data-Driven Models for Non-Fullerene Acceptor Organic Solar Cells

In the design of organic solar cells, there has been a need for materials with high power conversion efficiencies. Scharber’s model is commonly used to predict efficiency; however, it exhibits poor performance with new non-fullerene acceptor (NFA) devices, since it was designed for fullerene-based devices. In this work, an empirical model is proposed that can be a more accurate alternative for NFA organic solar cells. Additionally, many screening studies use computationally expensive methods. A model based on using semiempirical simplified time-dependent density functional theory (sTD-DFT) as an alternative method can accelerate the calculations and yield a similar accuracy. The models presented in this paper, termed organic photovoltaic efficiency predictor (OPEP) models, have shown significantly lower errors than previous models, with OPEP/B3LYP yielding errors of 1.53% and OPEP/sTD- DFT of 1.55%. As a result, the proposed computational models can be used for the fast and accurate screening of new high-efficiency NFAs/donor pairs.

14 SOLAR ENERGY↗
DOE OSTI2024

Data-driven modeling of dislocation mobility from atomistics using physics-informed machine learning

Dislocation mobility, which dictates the response of dislocations to an applied stress, is a fundamental property of crystalline materials that governs the evolution of plastic deformation. Traditional approaches for deriving mobility laws rely on phenomenological models of the underlying physics, whose free parameters are in turn fitted to a small number of intuition-driven atomic scale simulations under varying conditions of temperature and stress. This tedious and time-consuming approach becomes particularly cumbersome for materials with complex dependencies on stress, temperature, and local environment, such as body-centered cubic crystals (BCC) metals and alloys. In this paper, we present a novel, uncertainty quantification-driven active learning paradigm for learning dislocation mobility laws from automated high-throughput large-scale molecular dynamics simulations, using Graph Neural Networks (GNN) with a physics-informed architecture. We demonstrate that this Physics-informed Graph Neural Network (PI-GNN) framework captures the underlying physics more accurately compared to existing phenomenological mobility laws in BCC metals.

36 MATERIALS SCIENCE↗
DOE OSTI2020

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 13: Functional Specification Report(Deliverable D9))

This report provides functional specification for the AGGREGATE project and associated modules/ tools being developed for outage management and restoration with the Distributed Energy Resources (DERs). This report also provide initial validation of the developed modules and performance metrics. The AGGREGATE team at this stage has been collaborating with General Electric (GE) and Seattle City Light (SCL) to move forward from offline validation to online validation using commercial advanced distribution management system (ADMS). Hence, the functional specifications documents, which outline the requirement of various modules, is provided to address the integration of the modules, including 1) real-time model update and aggregation tools module, 2) observability and controllability metric module, 3) fault location solution service restoration module, 4) transmission-distribution co-simulation module, and 5) advanced distribution management system module. integration of different AGGREGATE modules and functional specification provides the foundation for online multi-scenario testing using SCL system model.

42 ENGINEERING↗
DOE OSTI2020

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 14: Model Verification/Validation Test Plan (Deliverable D10))

This report summarizes the technical progress and validation plan for each of AGGREGATE project modules, and integrated modules. The overall validation plan can be divided into two major parts. Firstly, it provides offline validation results of each module using the IEEE-123 node distribution system with certain modifications to support individual module results verification. The offline validation plan tentatively validated the usability and practicability of developed AGGREGATE tools. Secondly, the realworld test system - Seattle City Light (SCL) test feeder for verifying each module and the integrated modules using GE advanced distribution management system (ADMS) software.

42 ENGINEERING↗
DOE OSTI2021

Report for Task 15: Developed Tool Verification/Validation Report (Deliverable D11): AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency

This report summarizes the verification report for the developed modules. The team conducted verification in two phases. In phase 1, the modules were validated using offline validation methods and in phase 2 the modules were subjected to real-time validation. This report outlines the approach and the results for the modules under offline and real-time settings. The rest of the report details the functional workflow of AGGREGATE modules, we then transition to offline validation followed by real-time validation of modules. We conclude the report by discussing some of the key points of this report.

14 SOLAR ENERGY↗