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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 73 records · Page 4

Adsorption Properties of Au−Ni Surface Alloys with a Nonstoichiometric Moiré Structure: A Density Functional Theory Study

Due to the large lattice mismatch between gold and nickel, gold–nickel surface alloys can form unique nonstoichiometric overlayer structures characterized by a moiré pattern and subsurface defects. For this work, we performed density functional theory (DFT) calculations to study the adsorption of molecular oxygen, atomic hydrogen, and atomic carbon on a gold–nickel(111) surface alloy with 0.46 monolayer gold randomly distributed in the surface layer. We observed six distinct adsorption structures for molecular oxygen characterized by intramolecular stretching frequencies of <700, 729, 795, 857, 929, and 1004 cm –1 , which describe well the experimentally observed high-resolution electron energy-loss spectra. Surface atomic hydrogen adsorption is associated with adsorbate–surface modes in the ∼1000 cm –1 range, while subsurface hydrogen can have features as low as ∼400 cm –1 . We observed a unique adsorption structure for atomic carbon inside the surface dislocation loop defect, which explains the experimentally observed low carbon-surface mode at ∼340 cm –1 . Our study sheds light on the unique adsorption properties of the gold–nickel surface alloys and helps with rationalizing vibrational frequency experimental studies for this system.

adsorption↗

First-Principles Study on the Role of Cu and Cl-Based Dopants in NiO

Utilization of wide band gap oxide-based materials in thin-film solar energy technologies has increased in recent years. Among the numerous candidate oxide materials, NiO has shown many desirable optoelectronic properties that are applicable to thin-film PV technologies such as cadmium telluride PV. However, one critical factor requiring further investigation is the p-type doping behavior of NiO, specifically when the cadmium telluride solar cell undergoes conventional processes such as copper doping and chlorine-based activation treatment. The previous literature has shown a large degree of variability in hole concentrations in NiO when copper is used as the primary dopant. This study uses first-principles computational modeling based on density functional theory coupled with defect equilibria calculations to quantitatively explore the role of copper and chlorine-based extrinsic dopants in the p-type doping activity of NiO. The study reveals the importance of extrinsic dopants and their binding interactions with nickel vacancies to effectively p-dope NiO. It is suggested that both the formation of V Ni + Cu Ni and V Ni + Cl O defect pairs under a supersaturated state of NiO are potential mechanisms for increasing hole densities. On the other hand, the production of 2Cu Ni severely limits the effectiveness of p-doping in NiO, even in the presence of the aforementioned defect pairs. Furthermore, the study provides a guideline for experimentalists interested in using copper or chlorine species to understand how to controllably p-dope NiO during thin-film synthesis.

chlorine↗

Report of the 2021 U.S. Community Study on the Future of Particle Physics (Snowmass 2021)

In 2019, with the construction of the projects supported by the 2014 P5 process well underway or in an advanced stage of planning, the Division of Particle and Fields (DPF) of the American Physical Society (APS) began to prepare a new community study of U.S. high energy physics (HEP) for the decade of 2025 – 2035, and beyond. This “Snowmass 2021” HEP Community Planning Exercise began formally with a kick-off meeting at the 2020 APS April Meeting and a Community-wide Planning Meeting in October of 2020. The exercise was to conclude in July of 2021 with a workshop in Seattle hosted by the University of Washington. The COVID-19 pandemic severely disrupted these plans. Work was paused from January to September of 2021 to lighten the burden on our younger scientists. We resumed work by September of 2021 and, despite the continuing challenges of COVID-19, our community was well prepared for the Seattle meeting, which had been rescheduled for July 17–26, 2022.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DSO+T: Expanded Study Results DSO+T Study: Volume 5

The Distribution System Operator with Transactive (DSO+T) study investigates the engineering and economic performance of a transactive energy retail market coordinating a high penetration of customer-side flexible energy assets. The study seeks to answer whether such an implementation is cost effective for customers, recovers sufficient revenue for DSOs, and is equally applicable and beneficial to a range of flexible asset types, renewable generation scenarios, and market assumptions. This report volume provides a detailed set of results for the DSO+T study extending results presented in Volumes 1, 2, and 4. The engineering and economic performance of the transactive energy scheme is presented for two separate flexible asset deployments: flexible loads (HVAC units and residential water heaters) and behind-the-meter batteries. The results of each transactive case are compared to a business-as-usual case. These cases are subject to two different renewable generation scenarios, a moderate renewable generation scenario, representative of current levels of renewable generation deployment, and a future high renewables scenario, including the increased deployment of rooftop solar photovoltaic and electric vehicles. The transactive coordination scheme is shown to produce effective and stable control and decrease peak loads 9–15%. The resulting annual demand flexibility provides net economic savings of $3.3–5.0B per year for a region the size of Texas. Detailed analysis shows that net benefits were seen for a range of distribution system operator, customer, and flexible asset types. Both participating customer (with transactive flexible assets) and nonparticipating customers (with nonflexible assets) see reductions in annual utility bills and net annual energy expenses in the range of 10–16%.

24 POWER TRANSMISSION AND DISTRIBUTION↗

In Situ ATR-FTIR Study of the Cathode–Electrolyte Interphase: Electrolyte Solution Structure, Transition Metal Redox, and Surface Layer Evolution

We present a study of the lithium nickel manganese cobalt oxide (LiNi 0.6 Mn 0.2 Co 0.2 O 2 , NMC622) cathode-electrolyte interphase (CEI) during galvanostatic charging and discharging using in situ attenuated total reflectance Fourier transform infrared (ATR-FTIR) methods to investigate the voltage dependent electrolyte solution structure changes at the interface, transition metal (TM) redox chemistry, and cathode/electrolyte interfacial layer evolution. Furthermore, our in situ cell design provides both reliable electrochemical device testing and strong FTIR vibrational absorption signals near the cathode surface. Specifically, advanced spectral analysis elucidates changes of near-surface Li+ ion (de)solvation by solvent molecules during galvanostatic cycling. Moreover, cathode metal-oxygen vibrational absorptions, sensitive to TM redox behaviors and subsequent local structural variations, were correlated to cathode de-lithiation (and lithiation) and electrolyte solution structure changes. In addition, we have detected the formation and evolution of a CEI surface layer on the NMC622 cathode that contributes to the cell's capacity fade.

25 ENERGY STORAGE↗

Biopolymer‐assisted Synthesis of P‐doped TiO 2 Nanoparticles for High‐performance Lithium‐ion Batteries: A Comprehensive Study

Abstract TiO 2 material has gained significant attention for large‐scale energy storage due to its abundant, low‐cost, and environmentally friendly properties, as well as the availability of various nanostructures. Phosphorus doping has been established as an effective technique for improving electronic conductivity and managing the slow ionic diffusion kinetics of TiO 2 . In this study, non‐doped and phosphorus doped TiO 2 materials were synthesized using sodium alginate biopolymer as chelating agent. The prepared materials were evaluated as anode materials for lithium‐ion batteries (LIBs). The electrodes exhibit remarkable electrochemical performance, including a high reversible capacity of 235 mAh g −1 at 0.1 C and excellent first coulombic efficiency of 99 %. An integrated approach, combining operando XRD and ex‐situ XAS, comprehensively investigates the relationship between phosphorus doping, material structure, and electrochemical performance, reinforced by analytical tools and first principles calculations. Furthermore, a full cell was designed using 2 %P‐doped TiO 2 anode and LiFePO 4 cathode. The output voltage was about 1.6 V with high initial specific capacity of 148 mAh g −1 , high rate‐capability of 120 mAh g −1 at 1 C, and high‐capacity retention of 96 % after 1000 cycles at 1 C.

El Halya, Nabil↗

Bioenergy Technologies in Long-Run Climate Change Mitigation: Results from the EMF-33 Study

Bioenergy is expected to play an important role in long-run climate change mitigation strategies as highlighted by many integrated assessment model (IAM) scenarios. These scenarios, however, also show a very wide range of results, with uncertainty about bioenergy conversion technology deployment and biomass feedstock supply. To date, the underlying differences in model assumptions and parameters for the range of results have not been conveyed. Here we explore the models and results of the 33rd study of the Stanford Energy Modeling Forum to elucidate and explore bioenergy technology specifications and constraints that underlie projected bioenergy outcomes. We first develop and report consistent bioenergy technology characterizations and modeling details. We evaluate the bioenergy technology specifications through a series of analyses—comparison with the literature, model intercomparison, and an assessment of bioenergy technology projected deployments. We find that bioenergy technology coverage and characterization varies substantially across models, spanning different conversion routes, carbon capture and storage opportunities, and technology deployment constraints. Still, the range of technology specification assumptions is largely in line with bottom-up engineering estimates. We then find that variation in bioenergy deployment across models cannot be understood from technology costs alone. Important additional determinants include biomass feedstock costs, the availability and costs of alternative mitigation options in and across end-uses, the availability of carbon dioxide removal possibilities, the speed with which large scale changes in the makeup of energy conversion facilities and integration can take place, and the relative demand for different energy services.

bioenergy↗

Study of Different Formulations for the Multiperiod Blending Problem Applied to Lithium Recovery from Produced Water

We present several formulations to solve the MPBP for the recovery of REE/CMs from produced water and propose a decomposition approach thatleverages strategies in general disjunctive programming to enhance its performance. We compare these proposed formulations/strategies via two illustrative case studies on recovering lithium from a network of produced water sources.

Ovalle, Daniel↗

Evolving Electricity Supply and Demand to Achieve Net-Zero Emissions: Insights from the EMF-37 Study

This paper explores the role of electricity in achieving economy-wide net-zero CO2 emissions by 2050 in the United States based on results from 17 models as part of the 37th Stanford Energy Modeling Forum (EMF-37). In the study's Net-Zero scenario, the models use diverse pathways to achieve net-zero emissions by 2050, with gross energy-related residual emissions ranging from 17.2 to 66.6 % of 2020 levels. Electricity consistently emerges as central to achieving net-zero, with models projecting rapid electrification of end-uses and rapidly declining CO2 intensity of electricity. However, the extent of electrification and the technology mix to decarbonize the power sector vary considerably across models. In the Net-Zero scenario, electricity is projected to evolve from ~20 % of final energy in 2020 to 17-63 % in 2050 across the models driven by electrification in all sectors-buildings, industry, and transportation-and, to a lesser extent by direct air capture. By 2050, total electricity consumption increases by 24-176 % (relative to 2020), accompanied by significant expansion in renewable electricity production. Together, solar and wind generation grows by 175-834 %, supplying 45-90 % of total electricity in 2050, with wind achieving slightly higher shares than solar. Electricity storage technologies are deployed at scale to support wind and solar generation. The electricity generation mix varies across models: some project almost complete reliance on renewables, while others see a substantial role for natural gas, often with carbon capture and storage. This paper synthesizes the rich diversity of modeling approaches and results, highlighting differing views on how key drivers of electricity demand and supply might evolve.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Flexible and Generic Functional Mock-up Unit Based Threat Injection Framework for Grid-interactive Efficient Buildings: A Case Study in Modelica

Grid-interactive efficient buildings (GEBs) have been considered as an important asset to support the power grid reliability by utilizing the demand flexibility offered by GEBs. GEBs are enabled by advances in sensors and controls, and the communication between building equipment, whole buildings, and the grid. The integration of different building technologies and network-based communication system makes GEBs vulnerable to passive threats such as equipment failure and active threats such as cyber-attacks. Modeling and simulation is an effective way to evaluate the impact of threats on the system performance. This paper proposes a generic and flexible threat injection framework for commonly-used building energy simulators such as EnergyPlus and Modelica to support threat modeling and evaluation. This framework leverages functional mock-up unit (FMU) to develop a general modeling interface for threat injection and simulation. A numerical case study using Modelica as a building energy simulator is conducted to demonstrate the capability of the framework for supporting single/multiple-order threat modeling and simulation of a GEB. Four threats and their combinations are injected on a Modelica-based threat-free building energy and control system, including operating supply fan at its full speed, remotely cycling the chiller on and off, blocking the chiller from receiving the chilled water supply temperature setpoints, and hijacking the global zone air temperature setpoint. Simulation results show that the cyber-attack that leads to short-term signal blocking has small effects on the system operation due to the "self-healing" feature of the heating, ventilation, and air-conditioning (HVAC) interactive control system. The threat that takes control of resetting the global zone air temperature setpoints has the most adverse impact on the system energy use, peak power demand, thermal comfort and the provision of demand flexibility. The combination of four threats have aggregative effects on the system but the effects are less than the additive effects of the individual threat.

Fu, Yanyang↗

How structural differences influence cross-model consistency: An electric sector case study

Multiple models are often employed to describe a range of possible outcomes for one or more scenarios, yielding insights into causal relationships and their uncertainties. Electric sector capacity expansion scenarios are a common topic of such efforts due to the economic influence of the electric sector, but model results typically span a broad solution space despite efforts to harmonize input assumptions, making decision implications difficult to discern. This study investigates the relationship between input harmonization and cross-model scenario consistency under disparate electric sector scenarios. We compare cross-model consistency between two state-of-the-art electric sector capacity expansion models (GCAM-USA and ReEDS) for six electric sector scenarios comprising alternate assumptions about fossil fuel resource availability, technology innovation, and long-term economy-wide transitions under four harmonization configurations varying model representations of electricity demand, fuel prices, renewable resources, and capacity retirements. These comparisons reveal that cross-model consistency can vary across scenarios under a given harmonization configuration, suggesting that harmonization efforts must often be scenario-specific if comparable cross-model consistency is desired. Model structural differences can hinder consistency, and the impact of these differences can depend on the scenario. Ultimately, thorough harmonization can reveal insights into cross-model consistency, which can be used to tighten uncertainty bounds and improve the decision-making implications of multi-model activities.

Cohen, Stuart↗