Search NASA⌕ Search

SEARCH · Search NASA

Results for “reliance”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Ambient-Pressure Chemical Recycling of Thermoset Carbon Fiber-Reinforced Polymers via Low-Temperature Solvolysis: Techno-Economic and Life-Cycle Assessment

Carbon fiber-reinforced polymer (CFRP) waste is rapidly accumulating, with global volumes projected to exceed 500,000 tons annually by 2050. Virgin carbon fiber production is extremely energy- and cost-intensive, and growing demand has intensified supply-chain vulnerabilities associated with precursor availability and reliance on critical materials. Scalable recycling technologies therefore offer not only environmental benefits but also opportunities to reduce material costs and strengthen domestic composite supply chains. This study introduces an efficient, mild chemical recycling method for epoxy-amine CFRPs, utilizing acetic acid (80 wt%) and zinc acetate (1 wt%) at atmospheric pressure and low temperature (~110 °C). The solvolysis process preserves residual resin (~40%) on recycled carbon fibers (rCF), enhancing interfacial bonding in remanufactured composite materials. Recycled fibers retain ~90% of their mechanical properties, and recovered oligomers show potential for reuse in epoxy formulations, supporting material circularity. Techno-economic analysis (TEA) and life-cycle assessment (LCA) confirm the scalability and sustainability of this process.

Recycling CFRP↗
DOE OSTI2023

Dynamic probabilistic risk assessment for electric grid cybersecurity

Electric grid cybersecurity risk has become a significant concern of industries and governments. This paper proposes a dynamic probabilistic risk assessment method for electric grid cybersecurity risk analysis. The proposed method helps reduce the reliance on expert judgment, capture a broad range of components and system dynamics, and model the interactions between various contributing entities (e.g., attacker, operator). In addition, the scenarios with multiple events, such as the occurrence of both cyberattacks and failures of physical components, the occurrence of both cyberattacks and operators’ (in)correct reactions, are considered and analyzed. Further, for each cyberattack scenario, Monte Carlo simulations are used to obtain possible sequences of the system's evolution under study and then derive risk estimates. As an application of the proposed method, the risk assessment method serves as the basis of risk-informed defense resource allocation to improve electric grid cybersecurity. The proposed method is verified using the IEEE 14-bus system by evaluating different security resource allocations for selected cyberattack scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Bayesian Optimized Deep Ensemble for Uncertainty Quantification of Deep Neural Networks: a System Safety Case Study on Sodium Fast Reactor Thermal Stratification Modeling

Deep neural networks (DNNs) are increasingly important to scientific computing and engineering system simulations. Accurate uncertainty quantification (UQ) for DNNs is critical in safety-sensitive engineering domains. Traditional Deep Ensemble (DE) methods, while easy to implement, frequently suffer from poorly calibrated uncertainty estimates and limited predictive accuracy due to reliance on fixed architectures with varied weight initializations. To address these issues, we introduce a workflow that combines Bayesian Optimization (BO) and DE. The workflow is modular, scalable, and integrates parallel BO initialized with Sobol sequences to individually optimize the hyperparameters of each ensemble member. This method enhances ensemble diversity, improves predictive accuracy, and provides reliable uncertainty estimates. We evaluate the proposed BODE approach in a sodium fast reactor thermal stratification modeling case study, where we used a densely connected convolutional neural network to predict turbulent viscosity during the reactor transient with consideration of data noise. We benchmark its performance against several optimization approaches, including baseline deep ensemble, evolutionary algorithm-optimized ensemble, ensemble formed via random search combined with greedy selection, and a BO ensemble using random initialization. Here, our results demonstrate superior performance of the developed BODE approach. In noise-free scenarios, BODE notably reduces incorrect aleatoric uncertainty and significantly enhances predictive accuracy. Under conditions of 5% and 10% Gaussian noise, BODE adaptively quantifies uncertainty proportional to data noise, achieving up to an 80% reduction in root mean square error compared to baseline methods and producing well-calibrated prediction intervals.

Bayesian optimization↗
DOE OSTI2025

Velocity- and pressure-based metrics for estimating strike injuries during fish passage through hydro turbines

Hydropower is a crucial source of clean and reliable energy worldwide, and its importance will continue to grow. To enhance the environmental sustainability of hydropower development and operations, it is essential to predict the strike injury rates of fish passing through turbines accurately and cost-effectively. However, conventional experiments involving a large number of live fish are still commonly conducted in practice, and previous attempts mainly focused on the dose-response relationships at an individual level or relative comparisons of biological characterization between different conditions. Thus, this study proposes two novel strike metrics based on velocity and pressure (M V and M P ) measured by the cutting-edge Sensor Fish (SF) technology, designed to quantify the biological effects of strikes and collisions between fish and rigid hydraulic structures. SF measurements and 48-hour survival rates of live fish from a study conducted at the Ice Harbor Dam on the Snake River were used to establish thresholds for the two proposed metrics. These metrics and thresholds were then applied to three additional SF studies conducted at hydropower facilities featuring Kaplan turbines within the Columbia River basin. Results from the application of the strike metrics indicate that the estimated survival rates derived from both metrics agree well with previously reported live fish survival rates. Furthermore, the study identified specific passage regions with elevated risks of fish mortality due to strikes and collisions. Overall, the proposed strike metrics present a reliable and cost-effective approach to reducing reliance on live fish and lowering costs in fish passage studies.

Biological characterization↗
DOE OSTI2022

Ecosystem service benefits to water users from perennial biomass production

We report although many agree that a transition to renewable energy sources is needed to avoid the climate consequences of continued reliance on fossil sources, price is a barrier. For renewable energy sources, including bioenergy, penetrating energy markets depends on lowering prices to compete with the price of fossil sources, but the tools used in decision making, such as supply curves, exclude non-market benefits from ecosystem services. Here, we extend the economic concept of an economic supply curve to account for ecosystem services co-produced with perennial biomass. We developed three new types of supply curves to visualize the increased supply of biomass (‘sustainable supply’) with sufficient water-quality benefits to offset biomass production costs. Using these tools, we show that the value of water-quality improvements could significantly reduce the break-even price of perennial feedstocks if it were available to farmers. In the most optimistic case, nearly half of potential biomass supply in a large tributary of the Mississippi river basin carried water purification value exceeding the cost of biomass production. Furthermore, adding the value to swimmers and waders offset production cost for over 90% of potential supply. Simulated benefits were context specific. For example, total value for water drinkers peaked at an intermediate level of fertilizer application. Geographically, benefits were highest in the eastern portion of the river basin. This research shows where the sustainable supply is needed and can generate value; the next step is to match this supply with credit buyers. Efforts to internalize the values of ecosystem services into biomass prices could help to meet Biden administration targets to meet 100% of sustainable aviation fuels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Uncovering the dominant role of root metabolism in shaping rhizosphere metabolome under drought in tropical rainforest plants

Plant-soil-microbe interactions are crucial for driving rhizosphere processes that contribute to metabolite turnover and nutrient cycling. With the increasing frequency and severity of water scarcity due to climate warming, understanding how plant-mediated processes, such as root exudation, influence soil organic matter turnover in the rhizosphere is essential. In this study, we used 16S rRNA gene amplicon sequencing, rhizosphere metabolomics, and position-specific 13 C-pyruvate labeling to examine the effects of three different plant species (Piper auritum, Hibiscus rosa sinensis, and Clitoria fairchildiana) and their associated microbial communities on soil organic carbon turnover in the rhizosphere. Here, our findings indicate that in these tropical plants, the rhizosphere metabolome is primarily shaped by the response of roots to drought rather than direct shifts in the rhizosphere bacterial community composition. Specifically, the reduced exudation of plant roots had a notable effect on the metabolome of the rhizosphere of P. auritum, with less reliance on neighboring microbes. Contrary to P. auritum, H. rosa sinensis and C. fairchildiana experienced changes in their exudate composition during drought, causing alterations to the bacterial communities in the rhizosphere. This, in turn, had a collective impact on the rhizosphere's metabolome. Furthermore, the exclusion of phylogenetically distant microbes from the rhizosphere led to shifts in its metabolome. Additionally, C. fairchildiana appeared to be associated with only a subset of symbiotic bacteria under drought conditions. These results indicate that plant species-specific microbial interactions systematically change with the root metabolome. As roots respond to drought, their associated microbial communities adapt, potentially reinforcing the drought tolerance strategies of plant roots. These findings have significant implications for maintaining plant health and preference during drought stress and improving plant performance under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Active populations and growth of soil microorganisms are framed by mean annual precipitation in three California annual grasslands

Climate influences soil microbial composition and function, but the relative importance of a site's historic climate versus its more immediate environmental conditions is unclear. Using quantitative stable isotope probing (qSIP), we characterized actively growing soil microbial communities and soil properties in three California annual grasslands that span a rainfall gradient and have developed on similar parent material. The soils were assayed in the wet winter season, when environmental conditions are most similar across sites. Since growing populations might be expected to be most responsive to contemporary environmental conditions, we hypothesized that the structure of growing microbial communities would be more similar across the gradient than that of total communities (i.e., including non-growing populations). In addition, we hypothesized that population growth rates would be slowest in the driest site, reflecting a legacy effect of low soil moisture on microbial growth. Soils along the rainfall gradient differed in pH, texture, and cation exchange capacity, but not in total C, C:N or dominant minerals. The radiocarbon (14C) age of soil C (reflecting turnover time) increased with mean annual precipitation but soil respiration was uniformly modern, reflecting microbial reliance on recent C inputs across the sites. The structure of both total and growing microbial communities differed across sites. Across major microbial phyla, including the Actinobacteria, Acidobacteria, Bacteroidetes, Gemmatimonadetes and Proteobacteria, bacterial growth rates were consistently lower in the site with the lowest mean annual precipitation. Taxa that were growing at the dry site alone grew more slowly than taxa that grew at multiple sites. These results reflect the influence of climate history and point to the role of environmental filtering at the driest site in shaping its slower growing microbial community, possibly reflecting adaptation to repeated exposure to water stress. Lastly, across taxa, the growth rate of a taxon at one site was correlated with its growth rate in the other sites. Furthermore, this growth rate coherence is likely a consequence of genetically determined physiological traits and is consistent with the idea that evolutionary history constrains growth rate.

Environmental filtering↗
DOE OSTI2025

Environmental and socio-economic Pareto-front trade-off analysis of U.S. PET packaging material in a circular economy

Various recycling technologies are emerging to implement circular economy in plasticssupply chain systems. However, the environmental and socio-economic trade-offs of in circular economy are not well understood at a systems level. Particularly, quantifying these trade-offs as a function of end-of-life (EOL) management decisions, including transition of recycling technologies, systems level metrics such as circularity, recycled content, and the need for fossil-derived plastics are not well understood. Here, the present study addressed these research gaps by applying a systems analysis modeling approach that utilizes material flow analysis, life cycle assessment, socioeconomic data, and system optimization techniques for polyethylene terephthalate (PET) packaging supply chains in the United States. Pareto-front trade-offs between conflicting environmental and socio-economic impacts as well as those between socioeconomic impacts and circularity were explored using the epsilon constraint method. The Pareto-front trade-off analysis revealed the transition of EOL management strategies for PET packaging systems, including changes in selection of recycling technologies, to aid decision making process by quantifying studied system metrics. Transitioning from environmentally optimal to socio-economically optimal systems led to increased employment (by 17%), wages (by 26%), and revenues (by 6%) but also led to increased global warming potential (GWP; by 65%), energy consumption (by 59%), and reliance on fossil PET in the system (by 78%). Finally, the results show that there is not a unique set of recycling technologies to achieve a sustainable circular economy of PET packaging system, instead it depends on the decision maker’s objectives and targeted metrics of the system.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗
DOE OSTI2021

Process Intensification for the Biological Production of the Fuel Precursor Butyric Acid from Biomass

The production of fuels from lignocellulosic biomass is key to reduce our reliance on petroleum and to promote a sustainable bioeconomy. Butyric acid (BA) is a promising chemical precursor for the production of renewable diesel and jet fuels. BA can be biologically produced from lignocellulosic sugars. However, challenges associated with product selectivity and recovery must be overcome to achieve industrially relevant metrics. Here, we evaluate various fermentation configurations and demonstrate near-homo-butyrate production by using the biocatalyst Clostridium tyrobutyricum. We also develop an advanced in situ product recovery process based on hybrid extraction-distillation (HED-ISPR) and conduct techno-economic analyses and life cycle assessments. We demonstrate that the HED-ISPR process lowers the overall capital and operating expenses and environmental impact compared to other traditional fermentation processes. Overall, BA minimum product selling price from biomass is 55% of the current BA selling price from petroleum, a significant decrease toward viable renewable fuel production.

09 BIOMASS FUELS↗
DOE OSTI2020

Titanium Niobium Oxide: From Discovery to Application in Fast-Charging Lithium-Ion Batteries

Lithium-ion batteries are essential for portable technology and are now poised to disrupt a century of combustion-based transportation. The electrification revolution could eliminate our reliance on fossil fuels and enable a clean energy future; advanced batteries would facilitate this transition. However, owing to the demanding performance, cost, and safety requirements, it is challenging to translate new materials from laboratory prototypes to industrial-scale products. This Perspective describes that journey for a new lithium-ion battery anode material, TiNb 2 O 7 (TNO). TNO is intended as an alternative to graphite or Li 4 Ti 5 O 12 with better rate and safety characteristics than the former and higher energy density than the latter. The high capacity of TNO stems from the multielectron redox of Nb 5+ to Nb 3+ , its operating voltage window well above the Li + /Li reduction potential prevents lithium dendrite formation, and its open crystal structure leads to high-power performance. Nevertheless, the creation of a practical TNO anode was nonlinear and nontrivial. Its history is built on 30 years of fundamental science that preceded its application as a battery anode, and its battery development included a nearly 30-year gap. The insights and lessons contained in this Perspective, many of them acquired firsthand, serve two purposes: (i) to unite the disparate studies of TiNb 2 O 7 into a coherent modern understanding relevant to its application as a battery material and (ii) to highlight briefly some of the challenges faced when scaling up a new material that affect TiNb 2 O 7 as well as new electrode candidates more generally.

25 ENERGY STORAGE↗
DOE OSTI2020

Translating a Material Discovery into a Commercial Product in the Modern Lithium-ion Battery Market

Lithium-ion batteries are essential for portable technology and are now poised to disrupt a century of combustion-based transportation. The electrification revolution could eliminate our reliance on fossil fuels and enable a clean energy future; advanced batteries would facilitate this transition. However, owing to the demanding performance, cost, and safety requirements, it is challenging to translate new materials from laboratory prototypes to commercial products. This Perspective describes that journey toward commercialization for a new lithium-ion battery anode material, TiNb2O7 (TNO). TNO is intended as an alternative to graphite or Li4Ti5O12 with better rate and safety characteristics than the former, and higher energy density than the latter. The high capacity of TNO stems from multielectron redox of Nb5+ to Nb3+, its operating voltage window well above Li+/Li reduction potential prevents lithium dendrite formation, and its open crystal structure leads to high-power performance. Nevertheless, the creation of a practical TNO anode was non-linear and non-trivial. Its history is built on 30 years on fundamental science that preceded its application as a battery, and its battery development included a nearly 30-year gap. The insights and lessons 2 contained in this Perspective, many of them acquired firsthand, serve two purposes: (i) to unite the disparate studies of TiNb2O7 into a coherent modern understanding relevant to its application as a battery material and (ii) to highlight some of the considerations of commercializing a new material that affect TiNb2O7 as well as new electrode candidates more generally.

Griffith, Kent J.↗
DOE OSTI2020

Small-angle Neutron Scattering (SANS) Characterization of Clay- and Carbonate-rich Shale at Elevated Pressures

Unconventional oil and gas from shale formations have emerged as some of the fastest growing energy resources in the United States, providing both cleaner energy to consumers and reducing the nation’s reliance on energy imports. To properly harness these important natural resources, the nanopore structure of associated shales must be fully understood, particularly under hydraulic fracturing conditions, where they are exposed to both overburden compressive and hydrostatic fluid pressures. The current study uses small-angle neutron scattering (SANS) to characterize pore structure, including porosity, pore accessibility, and pore size distribution, in the 1–100 nm regime at elevated pressures for mineralogically distinct clay- and carbonate-rich shales from the Permian Basin. Unlike typical porosity measurement techniques, SANS is uniquely capable of characterizing both open and closed porosity, allowing measurement of how pore accessibility changes with pressure and determination of the size range of accessible versus inaccessible pores. The porosity of the clay-rich shale was 7.7%, compared to 0.51% for the carbonate-rich shale. However, only 2.6% of the nanopores in the carbonate-rich shale were inaccessible to water at 8 kPSI (55.1 MPa) compared to 7.8% for the clay-rich shale. Furthermore, our analyses indicated that the closed pores fall within distinct size ranges, likely corresponding with the chemical nature of the pore host material. These results provide valuable insight into the effects of shale petrophysical properties on hydrocarbon extraction from unconventional reservoirs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Platinum and Gold Supported on Transition Metal Nitrides for Hydrogen Evolution in an Alkaline Electrolyte

Here, as the urgency to reduce reliance on fossil fuels increases due to carbon dioxide emissions, hydrogen produced by renewably powered water electrolysis has emerged as a promising technology. Alkaline electrolyzers typically exhibit lower current densities than acidic electrolyzers due to the slow kinetics of the hydrogen evolution reaction (HER) under alkaline conditions. This work developed Pt- and Au-modified transition metal nitride (TMN) thin films for improving alkaline HER kinetics. One monolayer Pt–VN, Pt–Mo 2 N, and Pt–TiN were the most promising thin-film catalysts, with alkaline HER activity approaching that of a bulk Pt foil. Additionally, the Gibbs free energy of adsorbed hydrogen was identified as a useful descriptor for alkaline HER activity on TMN and TMN-supported catalysts and has the potential to guide future studies on TMN-based catalysts for enhancing alkaline HER. For practical applications, the thin-film catalysts were then extended to Pt- and Au-modified TMN powders for alkaline HER. Both 5 wt % Pt/TiN and 2 wt % Pt/TiN powders exhibited lower overpotentials at 5 mA/cm 2 when normalized by the Pt electrochemical surface area than the commercial 5 wt % Pt/C benchmark, suggesting a Pt–TiN synergy that creates opportunities for more cost-effective alkaline HER cathodes. Moreover, 20 wt % Au/Mo 2 N also displayed an enhancement in HER activity when compared to the commercial 20 wt % Au/C benchmark.

58 GEOSCIENCES↗
DOE OSTI2022

Regionalized Life-Cycle Water Impacts of Microalgal-Based Biofuels in the United States

While algal biofuels have the potential to reduce the national reliance on fossil fuels, high water consumption associated with algal biomass cultivation represents a major concern potentially compromising the sustainable commercialization of this technology. This study focuses on quantifying the water footprint (WF) and water scarcity footprint (WSF) of renewable diesel derived from algal biomass and provides insights into where algal cultivation is less water-intensive than traditional ethanol and biodiesel feedstocks. Results are generated with an engineering process model developed to predict the life-cycle water consumption, considering green, blue, and gray water, of algae facilities across the United States at a high spatiotemporal resolution. The total WFs for Florida and Arizona are determined to be 13.1 and 17.6 m 3 GJ –1 , respectively. The blue WF in Arizona is shown to be 8.5 times larger than in Florida, while the green WF is 4.5 times smaller, but when combined into a total WF, there is just a 26% difference between the two locations. The analysis reveals that the total life-cycle WFs of algal renewable diesel are smaller than the optimal WFs of corn ethanol and soybean biodiesel. Algal systems benefit from higher growth rates and offer the opportunity to manage wastewater streams, therefore generating smaller green and gray WFs than those of conventional biofuels. Here, the WSF analysis identifies the Gulf Coast as the most suitable region for algal cultivation, with cultivation in the western US shown to exacerbate local water stress levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

carbon capture and storage↗
DOE OSTI2025

The Impact of Clean Grid Transition on Wastewater Sector Greenhouse Gas Emissions

This study examines the spatial and temporal impacts of the U.S. clean energy grid transition on related greenhouse gas (GHG) emissions from the wastewater treatment industry. By analyzing data from 17,156 water resource recovery facilities (WRRFs) and state-specific grid decarbonization scenarios, the results project a 60% reduction in Scope 2 emissions by 2050, driven by the national shift to renewable energy. However, regional disparities are prominent, with northeastern and western states achieving the most significant reductions, while the Ohio Valley and Rockies are likely to experience higher emissions due to the reliance on fossil fuels. This study offers the first assessment of clean grid impacts on the WRRFs and highlights the need for targeted, region-specific strategies across different emission scopes. This research provides insights for policymakers and stakeholders in the wastewater sector, emphasizing the critical role of grid decarbonization in achieving GHG reduction goals.

Li, Xiatong↗
DOE OSTI2021

Semi-Automated Creation of Density Functional Tight Binding Models through Leveraging Chebyshev Polynomial-Based Force Fields

Density functional tight binding (DFTB) is an attractive method for accelerated quantum simulations of condensed matter due to its enhanced computational efficiency over standard density functional theory (DFT) approaches. However, DFTB models can be challenging to determine for individual systems of interest, especially for metallic and interfacial systems where different bonding arrangements can lead to significant changes in electronic states. In this regard, we have created a rapid-screening approach for determining systematically improvable DFTB interaction potentials that can yield transferable models for a variety of conditions. Our method leverages a recent reactive molecular dynamics force field where many-body interactions are represented by linear combinations of Chebyshev polynomials. This allows for the efficient creation of multi-center representations with relative ease, requiring only a small investment in initial DFT calculations. Here, we have focused our workflow on TiH 2 as a model system and show that a relatively small training set based on unit-cell-sized calculations yields a model accurate for both bulk and surface properties. Our approach is easy to implement and can yield reliable DFTB models over a broad range of thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

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

Multipole Expansion of Atomic Electron Density Fluctuation Interactions in the Density-Functional Tight-Binding Method

The accuracy of the density-functional tight-binding (DFTB) method in describing noncovalent interactions is limited due to its reliance on monopole-based spherical charge densities. In this study, we present a multipole-extended second-order DFTB (mDFTB2) method that takes into account atomic dipole and quadrupole interactions. Furthermore, we combine the multipole expansion with the monopole-based third-order contribution, resulting in the mDFTB3 method. To assess the accuracy of mDFTB2 and mDFTB3, we evaluate their performance in describing noncovalent interactions, proton transfer barriers, and dipole moments. Here, our benchmark results show promising improvements even when using the existing electronic parameters optimized for the original DFTB3 model. Both mDFTB2 and mDFTB3 outperform their monopole-based counterparts, DFTB2 and DFTB3, in terms of accuracy. While mDFTB2 and mDFTB3 perform comparably for neutral and positively charged systems, mDFTB3 exhibits superior performance over mDFTB2 when dealing with negatively charged systems and proton transfers. Overall, the incorporation of the multipole expansion significantly enhances the accuracy of the DFTB method in describing noncovalent interactions and proton transfers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗