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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Harmonized Database of Western U.S. Water Rights (HarDWR) v.1

Abstract In the arid and semi-arid Western U.S., access to water is regulated through a legal system of water rights. Individuals, companies, organizations, municipalities, and tribal entities have documents that declare their water rights. State water regulatory agencies collate and maintain these records, which can be used in legal disputes over access to water. While these records are publicly available data in all Western U.S. states, the data have not yet been readily available in digital form from all states. Furthermore, there are many differences in data format, terminology, and definitions between state water regulatory agencies. Here, we have collected water rights data from 11 Western U.S. state agencies, harmonized terminology and use definitions, formatted them for consistency, and tied them to a Western U.S.-wide shapefile of water administrative boundaries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Food resources affect territoriality of invasive wild pig sounders with implications for control

Abstract Interest in control methods for invasive wild pigs ( Sus scrofa ) has increased due to their range expansion, population growth, and an improved understanding of their destructive ecological and economic effects. Recent technological advances in traps for control of pig populations facilitate capture of entire social groups (sounders), but the efficacy of “whole-sounder” trapping strategies is heavily dependent on the degree of territoriality among sounders, a topic little research has explored. We assessed territoriality in wild pig sounders on the Savannah River Site, South Carolina, USA, and examined whether availability of food resources provided by a municipal-waste landfill affected among-sounder territoriality. We estimated utilization distribution overlap and dynamic interactions among 18 neighboring sounders around a landfill. We found that although neighboring sounders overlapped in space, intensity of use in shared areas was uniformly low, indicating territorial behavior. Neighbors tended to share slightly more space when closer to the landfill waste cells, indicating availability of a super-abundant resource somewhat weakens the degree of territoriality among sounders. Nevertheless, we conclude that sounders behaved in a generally territorial manner, and we discuss implications for whole-sounder trapping programs, particularly near concentrated resources such as landfills and crop fields.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

An AI-driven framework for evaluating local and state authorities’ permitting processes

The demand for new energy infrastructure is increasing across the United States, but heterogenous permitting processes and embedded requirements across different local jurisdictions can cause project delays, increase “soft costs,” and hinder developer expansion. This study analyzes the variability in local permitting requirements across the U.S. and develops a quantitative approach to describe their clarity and effectiveness in enabling infrastructure project development. By using an Energy Language Model (ELM), a large language model (LLM) for energy technologies, we systematically gathered permitting information from nearly 300 state-, county-, and city-level documents, creating a structured dataset of requirements and procedures on an unprecedented scale and speed. Our analysis revealed that local (city and county) permitting requirement documents are underrepresented compared to state-level guidance documents, which can impede timely and cost-effective installation of new electric infrastructure. Our validation process showed that the final database has an accuracy of approximately 95%. We, further, created a new quantitative method to score permitting requirements for clarity and efficiency, with electric vehicle supply equipment as an initial use case. The average local permitting document scored a 1.8 out of 5, which we interpret as meaning that half of the requirements developers face when installing electric infrastructure are ambiguous, increasing both cost and time. We also created a “Generalized Permit Process”, highlighting common procedural steps and identifying specific opportunities for municipalities to improve their documentation. This research establishes a systematic and scalable framework for evaluating the complexities of local infrastructure permitting processes by combining LLM-powered data collection and quantitative scoring. The framework enables policymakers and developers to identify and mitigate procedural bottlenecks, with the expectation that these improvements can accelerate application review and approval, reduce project costs, and expedite connection to utility distribution grids. As a foundational approach for streamlining local project development processes, this study’s methods are intended to be extended to a wide range of energy applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Current inequality and future potential of US urban tree cover for reducing heat-related health impacts

Excessive heat is a major and growing risk for urban residents. Here, we estimate the inequality in summertime heat-related mortality, morbidity, and electricity consumption across 5723 US municipalities and other places, housing 180 million people during the 2020 census. On average, trees in majority non-Hispanic white neighborhoods cool the air by 0.19 ± 0.05 °C more than in POC neighborhoods, leading annually to trees in white neighborhoods helping prevent 190 ± 139 more deaths, 30,131 ± 10,406 more doctors’ visits, and 1.4 ± 0.5 terawatt-hours (TWhr) more electricity consumption than in POC neighborhoods. We estimate that an ambitious reforestation program would require 1.2 billion trees and reduce population-weighted average summer temperatures by an additional 0.38 ± 0.01 °C. This temperature reduction would reduce annual heat-related mortality by an additional 464 ± 89 people, annual heat-related morbidity by 80,785 ± 6110 cases, and annual electricity consumption by 4.3 ± 0.2 TWhr, while increasing annual carbon sequestration in trees by 23.7 ± 1.2 MtCO 2 e yr -1 and decreasing annual electricity-related GHG emissions by 2.1 ± 0.2 MtCO 2 e yr -1 . The total economic value of these benefits, including the value of carbon sequestration and avoided emissions, would be USD 9.6 ± 0.5 billion, although in many neighborhoods the cost of planting and maintaining trees to achieve this increased tree cover would exceed these benefits. The exception is areas that currently have less tree cover, often the majority POC, which tend to have a relatively high return on investment from tree planting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Photoelectron spectroscopy and computational investigations of the electronic structures and noncovalent interactions of cyclodextrin-closo-dodecaborate anion complexes x-CD·B12X122- (x = a, ß, y; X = H, F)

We report a joint negative ion photoelectron spectroscopy (NIPES) and computational study on the electronic structures and noncovalent interactions of a series of cyclodextrin-closo-dodecaborate dianion complexes, ?-CD·B12X122- (? = a, ß, ?; X = H, F). The measured vertical / adiabatic detachment energies (VDEs / ADEs) are 1.15/0.93, 3.55/3.20, 3.90/3.60, and 3.85/3.60 eV for B12H122- and its a-, ß-, ?-CD complexes, respectively; while the corresponding values are 1.90/1.70, 4.00/3.60, 4.33/3.95, and 4.30/3.85 eV for the X = F case. These results show that the inclusion of B12X122- into the CD cavities greatly increase the electronic stability of the dianions. The effect of electronic stabilization for ß-CD is roughly the same as for ?-CD, both being considerably stronger than that for a-CD. Density functional theory (DFT) based geometry optimization reveals that B12X122- are inserted into CDs increasingly deeper from a-CD to ?-CD. The calculated VDEs and ADEs agree with the experiments well, particularly, reproducing the electron binding energy (EBE) trends. The molecular orbital analyses indicate that the most loosely bound photodetached electrons origin from the guest B12X122- moieties. In addition to a shift of all signals to larger EBE, significant changes in the signal patterns are observed. At low EBE, this is due to the splitting of highly degenerate B12X122- orbitals, while at high EBE, photodetachment from CD oxygens contributes to the new bands. The guest B12X122- and host CD nocovalent, size-specific interaction based on the independent gradient model (IGM) and energy decomposition analysis (EDA), is dominated by electrostatic interactions. The analysis further unravels unambiguiously the existence of dihydrogen bonding and how it affects the total energy that stabilizes the host-guest complexes of CDs·B12H122- compared to the general hydrogen bonding interaction in CDs·B12F122-. This work clearly exhibits strong influences on the electronic structures of dodecaborates upon clustering with CDs, with both size (a-, ß-, ?-) and molecular (X = H or F) specificities, thus providing critical molecular-level information on the cyclodextrin-closo-dodecaborate interactions of interest to medical applications, e.g. Boron neutron capature therapy. The NIPES experiments done at PNNL were supported by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Bioscience (X.-B.W.) and was performed at the EMSL, a national scientific user facility sponsored by DOE’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory. H.S. and Z.S. acknowledge the funding support of National Natural Science Foundation of China (Nos.11727810, 61720106009 and 21603074), the Science and Technology Commission of Shanghai Municipality (Nos. 19JC1412200), and the Program of Introducing Talents of Discipline to Universities 111 project (B12024). Z. L. thanks the China Scholarship Council (CSC) for financial support. We acknowledge the ECNU Multifunctional Platform for Innovation (001) and HPC Research Computing Team for providing computational and storage resources. J.W. acknowledges support from the Alexander von Humboldt foundation (Feodor Lynen Fellowship and Rückkehrerstipendium), a Freigeist fellowship of the Volkswagenfoundation and Prof. Vladimir A. Azov for helpful discussions.

Li, Zhipeng↗
DOE OSTI2020

Determinants for proton location and electron coupled proton transfer in hydrogen bonded pentafluorophenol-anion clusters

This work aims to reveal the determinant factors for proton locations and electron coupled proton transfer (ECPT) in biologically relevant hydrogen bonded systems. Pentafluorophenol-anion clusters [C6F5O-•H+•A-]- are chosen to model active sites of biological functions, with the anion A- being systematically varied to ensure the proton affinities (PAs) of the anions well cover the referenced PA of C6F5O- from being appreciably smaller, similar, and to significantly larger. Negative ion photoelectron spectroscopy of these clusters provides spectroscopic evidence showing that proton location in the anionic state is largely following the PA prediction, while ECPT is observed only for the clusters with the anion possessing the electron binding energy (EBE) significantly larger than that of the referenced C6F5O-. Theoretical calculations suggest these clusters are stabilized by forming single strong hydrogen bond between donor and acceptor, and the associated charge and MO analyses fully support the experimental observations. The current holistic cluster model study indicates that PA is the right determinant that can be used to predict the proton location and describe hydrogen bonding structures, while both PA and EBE of anionic groups play important roles in facilitating ECPT process. This work was supported by U.S. Department of Energy (DOE), Office of Basic Energy Sciences, Division of Chemical Science, Geosciences, and Biosciences (X.-B.W.), and performed using EMSL, a national scientific user facility sponsored by DOE’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory, which is operated by Battelle Memorial Institute for the DOE. Part of this work was supported by the National Natural Science Foundation of China (No-11604046 for JZ; No. 11727810 for ZRS), as well as “Chenguang Program” by Shanghai Education Development Foundation, Shanghai Municipal Education Commission (No. 16CG38) and Natural Science Foundation of Shanghai (No. 16ZR1448100) (JZ).

Zhang, Jian↗
DOE OSTI2020

Desalination for a circular water economy

Today's water systems are enabled by ample fresh water sources, low-cost centralized treatment, and facile wastewater disposal. Climatic change, aging infrastructure, and source water contamination have exposed the vulnerabilities of this linear water paradigm. While seawater desalination enables coastal communities to augment their supply, more broadly securing water systems for municipal, industrial, and agricultural water users will require distributed desalination and fit-for-purpose reuse of nontraditional water sources. Our linear water economy must evolve into a resilient circular water economy, where water is continuously reused and “contaminants” become the feedstocks for other economically valuable processes. Additionally, technology innovation is needed to deliver autonomous, precise, resilient, intensified, modular, and electrified desalination systems that reduce the cost, improve the performance, and enhance the resilience of nontraditional water reuse systems. Meanwhile, strong federal leadership and coordination is needed to accelerate desalination research, promote information gathering efforts to direct technology development, and create an expanded role for non-profit organizations in knowledge dissemination.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Advancing Asset Management in Water Infrastructure Systems

Aging water system infrastructure, including drinking water, wastewater, and stormwater, poses a growing challenge for utilities and municipalities. These water systems have well documented challenges with respect to their age, condition, and level of service. ASCE annual report cards consistently rate these infrastructure systems in the United States as underfunded, overcapacity, or past service life (ASCE 2025 Report Card). For example, Chini and Stillwell (2017) estimated that the mean water loss in drinking water systems, i.e., non-revenue water, is approximately 16% across the United States. These concerns are not just relegated to the United States, with Courtenay, British Columbia, identifying 17% of their water main pipes as in a ‘poor’ condition state, defined as a category condition 5 out of 5 (City of Courtenay, 2024). These cases illustrate the challenges utilities are facing to manage extensive networks of infrastructure to deliver a consistent and high level of service. For buried infrastructure such as water systems, studies suggest that preventative interventions can lead to lower maintenance costs and fewer service disruptions (Mazumder et al, 2018; Li et al, 2014). The demonstrated need and benefit of appropriately applied asset management is juxtaposed against the relatively sparse literature that evaluates water systems within an asset management construct. Since 2020, just 37 papers specifically reference asset management in the Journal of Water Resources Planning and Management. Of those, only a few specifically look to develop strategies for improved asset management. Therefore, we highlight four key research areas that represent opportunities for advancement of asset management research for water systems. First, advances in condition assessment and forecasting are needed to better estimate asset deterioration using diverse datasets. Second, machine learning (ML) and artificial intelligence (AI) hold promise for predictive maintenance and investment prioritization, though questions of generalizability and model transparency remain. Third, applying a value of information framework can guide utilities in making cost-effective sensor deployment and data collection decisions, to direct monitoring strategies towards data-informed asset management decisions. Finally, integrated infrastructure management is critical, requiring coordinated planning with other infrastructure systems and stakeholder engagement to reduce costs and enhance service delivery.

Chini, Christopher M.↗
DOE OSTI2020

Field experimental evidence shows that self-interest attracts more sunlight

This study examines how messaging approaches in a prosocial intervention can influence not only the effectiveness of the intervention but also, contagion afterward. Our investigation focuses on leveraging two motivations for solar adoption: self-interest and prosocial. Using data from a natural field experiment in 29 municipalities containing 684,000 people, we find that self-interest messaging is twice as effective in inducing solar adoption both during and after the intervention. Adoptions under self-interest messaging have 10% higher net present value, but prosocial messaging increases the likelihood that adopters recommend solar to their friends and neighbors. Income moderates the effectiveness of self-interest messaging, performing much better in high-income communities than low- and moderate-income communities. There was no significant difference across income groups for prosocial messaging. These results provide guidance to policy makers aiming to encourage prosocial behavior across all income groups.

14 SOLAR ENERGY↗
DOE OSTI2023

Ceci N’est Pas Une Bombe: Lessons from a Field Experiment Using Neutron and Gamma Measurements to Confirm the Absence of Nuclear Weapons

In March 2023, the UN Institute for Disarmament Research held a verification experiment that included a mockup onsite inspection at a former military facility in the municipality of Menzingen, Switzerland. The experiment included a visit to the site by an inspection team, accompanied by the host team. Among other activities, radiation measurements were used to confirm the non-nuclear nature of selected items stored onsite. In this paper, we discuss the neutron and gamma measurement systems used during the experiment and the inspection protocols followed to confirm the absence of nuclear weapons. Furthermore, results from the experiment and a laboratory reproduction are presented, before concluding with lessons learned for how absence-confirmation measurements can help support verification of future arms control agreements.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Cordon screen: A cordon-based congestion pricing policy evaluation method for U.S. cities

Global trends toward urbanization will exacerbate traffic congestion, delays in economic productivity, and air pollution issues for growing cities. Traffic congestion pricing is one method available to help ameliorate these concerns. New York City is on the verge of implementing a cordon-based traffic congestion pricing policy around its central business district. For budget-constrained municipalities, evaluating implementation of such policy could be costly. This article proposes a sketch-planning methodology, called Cordon Screen, for major U.S. cities to evaluate the net income, traffic mitigation, and avoided pollution emissions from cordon-based traffic congestion pricing. This method relies on national datasets and limited user-specific data inputs, along with a range of user-selectable assumptions informed by academic literature to deliver order-of-magnitude results. The numerous limitations of this method are acceptable for preliminary policy evaluation to determine if greater financial investment to obtain more accurate results is justified. The Denver metropolitan area is used to demonstrate Cordon Screen capabilities, with mid-range assumption results suggesting the policy is most effective at generating net income and increasing vehicle speeds on major interstates. For Denver, the policy is comparably less effective at reducing air pollution and increasing speeds on minor roadways. Validation against early implementation results from the London cordon are acceptable. Still, users should discount revenue generation projections. Choice of cordon area may be the most difficult obstacle when using the Cordon Screen. With refinement, Cordon Screen could serve as a low-cost, open-source planning evaluation tool for growing and congested U.S. cities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Simulation-based analysis of different curb space type allocations on curb performance

Curbspace is a limited resource in urban areas. Delivery, ridehailing and passenger vehicles must compete for spaces at the curb. Cities are increasingly adjusting curb rules and allocating curb spaces for uses other than short-term paid parking, yet they lack the tools or data needed to make informed decisions. In this research, we analyze and quantify the impacts of different curb use allocations on curb performance through simulation, covering various mixes of curbspace uses (bus stops, paid parking, passenger pick-up/drop-off zones, and commercial vehicle loading zones), parking rules, and driver rule compliance. Three metrics (including two new ones) are developed to evaluate the performance of the curb, covering productivity and accessibility of passengers and goods, and CO 2 emissions. The metrics are calculated for each scenario across a wide range of input parameters (traffic volume, parking demand rate, vehicle dwell time, and street design speed) and compared to each other and to a baseline scenario. This work can inform policy decisions by providing municipalities a tool to analyze various curb management strategies and choose the ones that produce results more in line with their policy goals.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

The future evolution of energy-water-agriculture interconnectivity across the US

Abstract Energy, water, and agricultural resources across the globe are highly interconnected. This interconnectivity poses science challenges, such as understanding and modeling interconnections, as well as practical challenges, such as efficiently managing interdependent resource systems. Using the US as an example, this study seeks to define and explore how interconnectivity evolves over space and time under a range of influences. Concepts from graph theory and input–output analysis are used to visualize and quantify key intersectoral linkages using two new indices: the ‘Interconnectivity Magnitude Index’ and the ‘Interconnectivity Spread Index’. Using the Global Change Analysis Model (GCAM-USA), we explore the future evolution of these indices under four scenarios that explore a range of forces, including socioeconomic and technological change. Analysis is conducted at both national and state level spatial scales from 2015 to 2100. Results from a Reference scenario show that resource interconnectivity in the US is primarily driven by water use amongst different sectors, while changes in interconnectivity are driven by a decoupling of the water and electricity systems, as power plants become more water-efficient over time. High population and GDP growth results in relatively more decoupling of sectors, as a larger share of water and energy is used outside of interconnected sector feedback loops. Lower socioeconomic growth results in the opposite trend. Transitioning to a low-carbon economy increases interconnectivity because of the expansion of purpose-grown biomass, which strengthens the connections between water and energy. The results highlight that while some regions may experience similar sectoral stress projections, the composition of the intersectoral connectivity leading to that sectoral stress may call for distinctly different multi-sector co-management strategies. The methodology we introduce here can be applied in diverse geographical and sectoral contexts to enable better understanding of where, when, and how coupling or decoupling between sectors could evolve and be better managed.

Khan, Zarrar (ORCID:0000000281478553)↗
DOE OSTI2023

Multi-scale planning model for robust urban drought response

Increasingly severe droughts are straining municipal water resources and jeopardizing urban water security, but uncertainty in their duration, frequency, and intensity challenges drought planning and response. We develop the Drought Resilient Interscale Portfolio Planning model (DRIPP) to generate optimal planning responses to urban drought. DRIPP is a generalizable multi-scale framework for optimizing dynamic planning strategies of long-term infrastructure deployment and short-term drought response. It integrates climate and hydrological variability with high-fidelity representations of urban water distribution, available technology options, and demand reduction measures to yield robust and cost-effective water supply portfolios that are location-specific. We apply DRIPP in Santa Barbara, California to assess how least cost water supply portfolios vary under different drought scenarios and identify portfolios that are robust across drought scenarios. In Santa Barbara, we find that drought intensity, not duration or frequency, drives cost increases, reliability risk, and regret of overbuilding infrastructure. Under uncertain drought conditions, a diversified technology portfolio that includes both rapidly deployable, decentralized technologies alongside larger centralized technologies minimizes water supply cost while maintaining high robustness to climate uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Air quality and public health co-benefits of 100% renewable electricity adoption and electrification pathways in Los Angeles

To demonstrate how a mega city can lead in decarbonizing beyond legal mandates, the city of Los Angeles (LA) developed science-based, feasible pathways towards utilizing 100% renewable energy for its municipally-owned electric utility. Aside from decarbonization, renewable energy adoption can lead to co-benefits such as improving urban air quality from reductions in combustion-related emissions of oxides of nitrogen (NO x ), primary fine particulate matter (PM 2.5 ) and others. Herein, we quantify changes to air pollutant concentrations and public health from scenarios of 100% renewable electricity adoption in LA in 2045, alongside aggressive electrification of end-use sectors. Our analysis suggests that while ensuring reliable electricity supply, reductions in emissions of air pollutants associated with the 100% renewable electricity scenarios can lead to 8% citywide reductions of PM 2.5 concentration while increasing ozone concentration by 5% relative to a 2012 baseline year, given identical meteorology conditions. The combination of these concentration changes could result in net monetized public health benefits (driven by avoided deaths) of up to $\$$1.4 billion in year 2045 in LA, results potentially replicable for other city-scale decarbonization scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Transcriptional control of Clostridium autoethanogenum using CRISPRi

Gas fermentation by Clostridium autoethanogenum is a commercial process for the sustainable biomanufacturing of fuels and valuable chemicals using abundant, low-cost C1 feedstocks (CO and CO 2 ) from sources such as inedible biomass, unsorted and nonrecyclable municipal solid waste, and industrial emissions. Efforts toward pathway engineering and elucidation of gene function in this microbe have been limited by a lack of genetic tools to control gene expression and arduous genome engineering methods. To increase the pace of progress, here we developed an inducible CRISPR interference (CRISPRi) system for C. autoethanogenum and applied that system toward transcriptional repression of genes with ostensibly crucial functions in metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Designing Future Energy Systems with Generative AI

Energy systems are experiencing various changes that impact the distribution, use, and reliability of energy. Local utilities and municipalities must respond and adapt to these changes, moving towards a future energy system with modernized infrastructure and other targeted investments and policy decisions. However, planning for and enacting these advancements requires significant effort from experts and engineers to develop strategies that ensure a reliable and secure energy future. This includes characterizing the current energy infrastructure, identifying areas for development, and engaging with local community members. Emerging generative artificial intelligence techniques can alleviate pain points and help support the development of the next generation of energy systems. Here, in this article, we highlight on-going generative AI work in the areas of atmospheric modeling, building energy management, and distribution network design, and we propose a vision for the role of generative AI that considers opportunities and identifies challenges inherent to this technology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Using Artificial Intelligence to Improve Reliability and Operational Efficiency of Small-Scale Hydroelectric Distributed Generation

Reliability and resilience are critical concerns for distributed generation (DG) at the rural electric level. The integration of renewable energy sources, such as small-scale hydroelectric distributed generators (hydro DGs), introduces operational challenges, particularly regarding aging infrastructure and grid stability. Artificial Intelligence (AI)-driven Machine Learning (ML) models and applications of Large Language Models (LLMs) offer promising solutions for optimizing DG operations and enhancing resilience. This paper explores AI-based models for improving efficiency, fault resolution, and outage mitigation in small-scale hydro DGs. Furthermore, it highlights the development of a centralized, AI-powered information portal for rural electric cooperatives and municipalities. The research evaluates hydro DG plant models and discusses the applicability of AI-powered question-answering tools for real-time operations, focusing on statistical data, load flow, voltage regulation, and generation power. The findings demonstrate AI’s potential to transform DG management to ensure greater stability and resilience in rural electric grids.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046↗