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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Agent-based modeling and simulation for the circular economy: Lessons learned and path forward

Circular economy aims at decoupling human activities from resource use and creating wealth. However, many have questioned the link between increased circularity and sustainability, resulting in several methodological approaches being developed to answer that question. This article analyzes and discusses the insights gained from applying agent-based modeling and simulation to study the techno-economic and social conditions promoting circularity and sustainability. This article analyzes the benefits and limitations of this technology and discusses future methodology developments within the circular economy context. Moreover, six limits of the circular economy concept are used to interpret insights from the literature: thermodynamic limits, system boundary limits, limits posed by the physical scale of the economy, limits posed by path dependencies and lock-in, limits of governance and management, and limits of social and cultural definitions. Promising research avenues are to use this methodology with machine learning, industrial ecology methods, and detailed geographic information.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Combining Agent Based Modeling and System Dynamics to Investigate the Circularity of Plastics

The United States currently produces about 1 million metric ton of ocean plastic pollution annually. One proposed solution to combat plastic waste is a circular economy (CE), which aims to transition from today's take-make-waste linear pattern of production and consumption to a system where the value of resources is maximized over time. Two key methods in industrial ecology are useful in assessing the viability of CE: (1) System Dynamics (SD) and (2) Agent Based Modeling (ABM). In prior work, the plastic life cycle was modeled with SD and ABM. The two models calculate recycling rates and costs in different ways, making it difficult to pinpoint necessary next steps. We integrate the ABM and SD models - linking the emergent patterns from micro-level human decisions to system level processes - which allows a more comprehensive understanding of feedbacks, costs, and environmental impacts. The integrated model is more accurate, and can be used to visualize recycling rates and human health and environmental impacts over time. The difference between the integrated and original SD model prompts a Sobol sensitivity analysis, which is used to understand which behavioral factors most affect plastic recycling patterns. We find that the habitual component is typically the most influential in promoting positive recycling behavior. Additionally, we utilize the combined model to understand and visualize how various behavioral intervention scenarios, like improved access to recycling programs and cart tagging, influence recycling patterns; these results can guide future policy-making.

agent-based modeling↗
DOE OSTI2021

Tissue scale agent-based simulation of premalignant progressions in Barrett’s esophagus

Barrett’s esophagus (BE) is a benign condition of the distal esophagus that initiates a multistage pathway to esophageal adenocarcinoma (EAC). Short of frequent intrusive (and costly) surveillance, effective screening for neoplasia in BE populations is yet to be established since progressors are rare and virtually undetectable without routine biopsies, which often sample only a small portion of the BE tissue. As a result, reliable estimation of the true prevalence of dysplasia in a BE population and evidence-based optimization of screening for at-risk individuals is challenging. Data-driven microsimulations, i.e., model-generated instances of disease history in a predefined virtual population, have found utility in the EAC screening literature as low-overhead alternatives to real-world hypothesis testing of optimal interventions for dysplasia. Despite the successes, computational limitations, paucity of knowledge and data on Barrett’s dysplasia, and the complexities of disease progression as a multiscale multiphysics process have hindered the treatment of disease progression in BE as a spatial process. Agent-based modeling of nucleation and proliferation processes in dysplasia warrants exploration in this context as an approximation that operates at a trade-off between computational tractability and precise representation of the composition and physics of the substrate (tissue). In this study, we describe spatially resolved simulations of premalignant progression toward EAC in a coarse-grained model of Barrett’s tissue that resolves the metaplastic tissue at a length scale of 0.42 mm (~3300 crypts/mm 2 ). Finally, the model is calibrated to reproduce historical high-grade dysplasia prevalence when model-generated patients are screened using the Seattle protocol.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Enabling Real-Time Communication in Multi-Agent Systems: A Graph Neural Network Based Approach

Global connectivity enables effective coordination in Multi-Agent Systems (MAS). Solving these connection problems under hardware constraints is an NP-hard non-Euclidean Degree Constrained Minimum Spanning Tree (DCMST) problem. Prior MAS controllers coordinate team movement for task completion and collision avoidance; some considering Line-of-Sight (LOS) maintenance but prioritizing flexibility over guarantees. Evolutionary Algorithms (EA) have been shown to find good solutions for DCMST, but their performance degrades with larger populations required to support a large MAS. We present a method based on edge graph attention networks, trained offline to reduce online computation times. Empirical comparisons with greedy polynomial-time solvers and EA show that our method leverages latent graph information to consistently find constraint-satisfying solutions in less time.

connectivity maintenance↗
DOE OSTI2021

Application of Machine Learning Techniques to an Agent-Based Model of Pantoea

Agent-based modeling (ABM) is a powerful simulation technique which describes a complex dynamic system based on its interacting constituent entities. While the flexibility of ABM enables broad application, the complexity of real-world models demands intensive computing resources and computational time; however, a metamodel may be constructed to gain insight at less computational expense. Here, we developed a model in NetLogo to describe the growth of a microbial population consisting of Pantoea . We applied 13 parameters that defined the model and actively changed seven of the parameters to modulate the evolution of the population curve in response to these changes. We efficiently performed more than 3,000 simulations using a Python wrapper, NL4Py . Upon evaluation of the correlation between the active parameters and outputs by random forest regression, we found that the parameters which define the depth of medium and glucose concentration affect the population curves significantly. Subsequently, we constructed a metamodel, a dense neural network, to predict the simulation outputs from the active parameters and found that it achieves high prediction accuracy, reaching an R 2 coefficient of determination value up to 0.92. Our approach of using a combination of ABM with random forest regression and neural network reduces the number of required ABM simulations. The simplified and refined metamodels may provide insights into the complex dynamic system before their transition to more sophisticated models that run on high-performance computing systems. The ultimate goal is to build a bridge between simulation and experiment, allowing model validation by comparing the simulated data to experimental data in microbiology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

E. coli -expressed SECRET AGENT O -GlcNAc modifies threonine 829 of GIGANTEA

The Arabidopsis thaliana glycosyl transferases SPINDLY (SPY) and SECRET AGENT (SEC) modify nuclear and cytosolic proteins with O-linked fucose or O-linked N-acetylglucosamine (O-GlcNAc), respectively. O-fucose and O-GlcNAc modifications can occur at the same sites. SPY interacts physically and genetically with GIGANTEA (GI), suggesting that it could be modified by both enzymes. Previously, we found that, when co-expressed in Escherichia coli, SEC modifies GI; however, the modification site was not determined. By analyzing the overlapping sub-fragments of GI, we identified a region that was modified by SEC in E. coli. Modification was undetectable when threonine 829 (T829) was mutated to alanine, while the T834A and T837A mutations reduced the modification, suggesting that T829 was the primary or the only modification site. Mapping using mass spectrometry detected only the modification of T829. Previous studies have shown that the positions modified by SEC in E. coli are modified in planta, suggesting that T829 is O-GlcNAc modified in planta.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Use of Nucleating Agent NA11 in the Preparation of Polyvinylidene Fluoride Dual-Layer Hollow Fiber Membranes

Polyvinylidene fluoride (PVDF) dual-layer hollow fiber membranes were simultaneously fabricated by thermally induced phase separation (TIPS) and non-solvent induced phase separation (NIPS) methods using a triple orifice spinneret (TOS) for water treatment application. The support layer was prepared from a TIPS dope solution, which was composed of PVDF, gamma-butyrolactone (GBL), and N-methyl-2-pyrrolidone (NMP). The coating layer was prepared from a NIPS dope solution, which was composed of PVDF, N,N-dimethylacetamide (DMAc), and polyvinylpyrrolidone (PVP). In order to improve the mechanical strength of the dual-layer hollow fiber, a nucleating agent, sodium 2,2'-methylene bis-(4,6-di-tert-butylphenyl) phosphate (NA11), was added to the TIPS dope solution. The performance of the membrane was evaluated by surface and cross-sectional morphology, water flux, mechanical strength, and thermal property. Our results demonstrate that NA11 improved the mechanical strength of the PVDF dual-layer hollow fiber membranes by up to 42%. In addition, the thickness of the coating layer affected the porosity of the membrane and mechanical performance to have high durability in enduring harsh processing conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Approximating Nash Equilibrium in Day-ahead Electricity Market Bidding with Multi-agent Deep Reinforcement Learning

In this paper, a day-ahead electricity market bidding problem with multiple strategic generation company (GEN-CO) bidders is studied. The problem is formulated as a Markov game model, where GENCO bidders interact with each other todevelop their optimal day-ahead bidding strategies. Considering unobservable information in the problem, a model-free and data-driven approach, known as multi-agent deep deterministic policy gradient (MADDPG), is applied for approximating the Nash equilibrium (NE) in the above Markov game. The MADDPG algorithm has the advantage of generalization due to the automatic feature extraction ability of the deep neural networks. The algorithm is tested on an IEEE 30-bus system with three competitive GENCO bidders in both an uncongested caseand a congested case. Comparisons with a truthful bidding strategy and state-of-the-art deep reinforcement learning methods including deep Q network and deep deterministic policy gradient (DDPG) demonstrate that the applied MADDPG algorithm can find a superior bidding strategy for all the market participants with increased profit gains. In addition, the comparison with a conventional model-based method shows that the MADDPG algorithm has higher computational efficiency, which is feasible for real-world applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Exploring Social Dynamics of Hard-Disk Drives Circularity with an Agent-Based Approach: Preprint

By 2025, it is estimated that installed data storage in the US will be 2.2 Zettabytes, generating about 50 million units of end-of-life hard-disk drives (HDDs) per year. The circular economy tackles waste issues by maximizing value retention in the economy, for instance, through reuse and recycling. However, the reuse of hard disk drives is hindered by the lack of trust organizations have toward other means of data removal than physically destroying HDDs. Here, an agent-based approach explores how organizations’ decisions to adopt other data removal means affect HDDs circularity. The model applies the theory of planned behaviour to model the decisions of HDDs end-users. Results demonstrate that the attitude (which is affected by trust) of end-users toward data-wiping technologies acts as a barrier to reuse. Moreover, social pressure can play a significant role as organizations that adopt CE behaviours can set an example for others.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2024

Agent-Based Model of Combined Community- and Jail-Based Take-Home Naloxone Distribution

Importance Opioid-related overdose accounts for almost 80 000 deaths annually across the US. People who use drugs leaving jails are at particularly high risk for opioid-related overdose and may benefit from take-home naloxone (THN) distribution. Objective To estimate the population impact of THN distribution at jail release to reverse opioid-related overdose among people with opioid use disorders. Design, Setting, and Participants This study developed the agent-based Justice-Community Circulation Model (JCCM) to model a synthetic population of individuals with and without a history of opioid use. Epidemiological data from 2014 to 2020 for Cook County, Illinois, were used to identify parameters pertinent to the synthetic population. Twenty-seven experimental scenarios were examined to capture diverse strategies of THN distribution and use. Sensitivity analysis was performed to identify critical mediating and moderating variables associated with population impact and a proxy metric for cost-effectiveness (ie, the direct costs of THN kits distributed per death averted). Data were analyzed between February 2022 and March 2024. Intervention Modeled interventions included 3 THN distribution channels: community facilities and practitioners; jail, at release; and social network or peers of persons released from jail. Main Outcomes and Measures The primary outcome was the percentage of opioid-related overdose deaths averted with THN in the modeled population relative to a baseline scenario with no intervention. Results Take-home naloxone distribution at jail release had the highest median (IQR) percentage of averted deaths at 11.70% (6.57%-15.75%). The probability of bystander presence at an opioid overdose showed the greatest proportional contribution (27.15%) to the variance in deaths averted in persons released from jail. The estimated costs of distributed THN kits were less than $\$$15 000 per averted death in all 27 scenarios. Conclusions and Relevance This study found that THN distribution at jail release is an economical and feasible approach to substantially reducing opioid-related overdose mortality. Training and preparation of proficient and willing bystanders are central factors in reaching the full potential of this intervention.

Tatara, Eric [Argonne National Laboratory (ANL), A↗
DOE OSTI2024

Heterogeneous Nucleating Agent for High‐Boiling‐Point Nonhalogenated Solvent‐Processed Organic Solar Cells and Modules

Abstract High‐boiling‐point nonhalogenated solvents are superior solvents to produce large‐area organic solar cells (OSCs) in industry because of their wide processing window and low toxicity; while, these solvents with slow evaporation kinetics will lead excessive aggregation of state‐of‐the‐art small molecule acceptors (e.g. L8‐BO), delivering serious efficiency losses. Here, a heterogeneous nucleating agent strategy is developed by grafting oligo (ethylene glycol) side‐chains on L8‐BO (BTO‐BO). The formation energy of the obtained BTO‐BO; while, changing from liquid in a solvent to a crystalline phase, is lower than that of L8‐BO irrespective of the solvent type. When BTO‐BO is added as the third component into the active layer (e.g. PM6:L8‐BO), it easily assembles to form numerous seed crystals, which serve as nucleation sites to trigger heterogeneous nucleation and increase nucleation density of L8‐BO through strong hydrogen bonding interactions even in high‐boiling‐point nonhalogenated solvents. Therefore, it can effectively suppress excessive aggregation during growth, achieving ideal phase‐separation active layer with small domain sizes and high crystallinity. The resultant toluene‐processed OSCs exhibit a record power conversion efficiency (PCE) of 19.42% (certificated 19.12%) with excellent operational stability. The strategy also has superior advantages in large‐scale devices, showing a 15.03‐cm 2 module with a record PCE of 16.35% (certificated 15.97%).

Chemistry↗
DOE OSTI2020

Surface Modification of a MXene by an Aminosilane Coupling Agent

MXenes, two–dimensional (2D) transition metal carbides and/or nitrides, possess surface termination groups such as hydroxyl, oxygen, and fluorine, which are available for surface functionalization. Their surface chemistry is critical in many applications. This article reports amine functionalization of Ti 3 C 2 T x MXene surface with [3–(2–aminoethylamino)–propyl]trimethoxysilane (AEAPTMS). Characterization techniques such as X–ray photoelectron spectroscopy verify the success of the surface functionalization and confirm that the silane coupling agent bonds to Ti 3 C 2 T x surface both physically and chemically. The functionalization changes the MXene surface charge from –35 to +25 mV at neutral pH, which allows for in situ preparation of self–assembled films. Further, surface charge measurements of the functionalized MXene at different pH values show that the functionalized MXene has an isoelectric point at a pH around 10.7, and the highest reported positive surface charge of +62 mV at a pH of 2.58. Furthermore, the existence of a mixture of different orientations of AEAPTMS and the simultaneous presence of protonated and free amine groups on the surface of Ti 3 C 2 T x are demonstrated. As a result, the availability of free amine groups on the surface potentially permits the fabrication of crosslinked electrically conductive MXene/epoxy composites, dye adsorbents, high–performance membranes, and drug carriers. Surface modifications of this type are applicable to many other MXenes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Few‐Unit‐Cell MFI Zeolite Synthesized using a Simple Di‐quaternary Ammonium Structure‐Directing Agent

Abstract Synthesis of a pentasil‐type zeolite with ultra‐small few‐unit‐cell crystalline domains, which we call FDP (few‐unit‐cell crystalline domain pentasil), is reported. FDP is made using bis‐1,5(tributyl ammonium) pentamethylene cations as structure directing agent (SDA). This di‐quaternary ammonium SDA combines butyl ammonium, in place of the one commonly used for MFI synthesis, propyl ammonium, and a five‐carbon nitrogen‐connecting chain, in place of the six‐carbon connecting chain SDAs that are known to fit well within the MFI pores. X‐ray diffraction analysis and electron microscopy imaging of FDP indicate ca. 10 nm crystalline domains organized in hierarchical micro‐/meso‐porous aggregates exhibiting mesoscopic order with an aggregate particle size up to ca. 5 μm. Al and Sn can be incorporated into the FDP zeolite framework to produce active and selective methanol‐to‐hydrocarbon and glucose isomerization catalysts, respectively.

Lu, Peng↗
DOE OSTI2022

Tunable CHA/AEI Zeolite Intergrowths with A Priori Biselective Organic Structure‐Directing Agents: Controlling Enrichment and Implications for Selective Catalytic Reduction of NOx

Abstract A novel ab initio methodology based on high‐throughput simulations has permitted designing unique biselective organic structure‐directing agents (OSDAs) that allow the efficient synthesis of CHA/AEI zeolite intergrowth materials with controlled phase compositions. Distinctive local crystallographic ordering of the CHA/AEI intergrowths was revealed at the nanoscale level using integrated differential phase contrast scanning transmission electron microscopy (iDPC STEM). These novel CHA/AEI materials have been tested for the selective catalytic reduction (SCR) of NOx, presenting an outstanding catalytic performance and hydrothermal stability, even surpassing the performance of the well‐established commercial CHA‐type catalyst. This methodology opens the possibility for synthetizing new zeolite intergrowths with more complex structures and unique catalytic properties.

Bello‐Jurado, Estefanía↗
DOE OSTI2021

Few‐Unit‐Cell MFI Zeolite Synthesized using a Simple Di‐quaternary Ammonium Structure‐Directing Agent

Abstract Synthesis of a pentasil‐type zeolite with ultra‐small few‐unit‐cell crystalline domains, which we call FDP (few‐unit‐cell crystalline domain pentasil), is reported. FDP is made using bis‐1,5(tributyl ammonium) pentamethylene cations as structure directing agent (SDA). This di‐quaternary ammonium SDA combines butyl ammonium, in place of the one commonly used for MFI synthesis, propyl ammonium, and a five‐carbon nitrogen‐connecting chain, in place of the six‐carbon connecting chain SDAs that are known to fit well within the MFI pores. X‐ray diffraction analysis and electron microscopy imaging of FDP indicate ca. 10 nm crystalline domains organized in hierarchical micro‐/meso‐porous aggregates exhibiting mesoscopic order with an aggregate particle size up to ca. 5 μm. Al and Sn can be incorporated into the FDP zeolite framework to produce active and selective methanol‐to‐hydrocarbon and glucose isomerization catalysts, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tunable CHA/AEI Zeolite Intergrowths with A Priori Biselective Organic Structure‐Directing Agents: Controlling Enrichment and Implications for Selective Catalytic Reduction of NOx

Abstract A novel ab initio methodology based on high‐throughput simulations has permitted designing unique biselective organic structure‐directing agents (OSDAs) that allow the efficient synthesis of CHA/AEI zeolite intergrowth materials with controlled phase compositions. Distinctive local crystallographic ordering of the CHA/AEI intergrowths was revealed at the nanoscale level using integrated differential phase contrast scanning transmission electron microscopy (iDPC STEM). These novel CHA/AEI materials have been tested for the selective catalytic reduction (SCR) of NOx, presenting an outstanding catalytic performance and hydrothermal stability, even surpassing the performance of the well‐established commercial CHA‐type catalyst. This methodology opens the possibility for synthetizing new zeolite intergrowths with more complex structures and unique catalytic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Immobilization of transgenic plant cells towards bioprinting for production of a recombinant biodefense agent

Abstract Transgenic rice cells ( Oryza sativa ) producing recombinant butyrylcholinesterase (BChE) as a prophylactic/therapeutic against organophosphate nerve agent poisoning, cocaine toxicity, and neurodegenerative diseases like Alzheimer's were immobilized in a polyethylene glycol‐based hydrogel. The cells were sustained for 14 days in the semi‐solid matrix, undergoing a growth phase from days 0–6, a BChE production phase in sugar‐free medium from days 6–12, and a growth/recovery phase from days 12–14. Throughout this period, the cells maintained similar viability to those in suspension cultures and displayed analogous sugar consumption trends. The rice cells in the hydrogel also produced a significant amount of active BChE, comparable to the levels produced in liquid cultures. A considerable fraction of this BChE was secreted into the media, allowing for easier product separation. To the best of our knowledge, this proof‐of‐concept is the first report of immobilization of recombinant plant cells for continuous production of high‐value heterologous proteins. This work serves as a foundation for further investigation towards plant cell bioprinting and the development of a simple, efficient, robust, modular, and potentially field‐deployable bioreactor system for the manufacture of biologics.

Varma, Anika↗
DOE OSTI2021

Trocylation of 3-quinuclidinol, a key marker for the chemical warfare agent 3-quinuclidinyl benzilate, for its enhanced detection at low levels in complex soil matrices by electron ionization gas chromatography–mass spectrometry

Detection of 3-quinuclidinol (3Q), a marker for the chemical warfare agent 3-quinuclidinyl benzilate, is very difficult by gas chromatography–mass spectrometry (GC/MS), providing low, broad signals even when analyzed in isolated form. Therefore, a method that can convert 3Q into a substrate with enhanced detectability by GC/MS would be an important tool for its analysis. 2,2,2-Trichloroethoxycarbonyl chloride (TrocCl) was used in the derivatization of 3Q in three different soils of varying composition and total organic content (Virginia type A soil, Nebraska EPA standard soil and Ottawa sand) when present at a 10 μg g -1 concentration in each. A direct derivatization protocol and one involving the pre-extraction of the analyte were evaluated for their individual efficiencies and subsequent analysis using electron ionization GC/MS. The practical derivatization of 3Q, when present at low levels (10 μg g -1 ) in three different soil matrices, was found to be rapid (1 h) and to take place smoothly at ambient temperature (and as low as 4°C). The method detection limit was determined to be 30 ng mL -1 for the Virginia type A soil, 49 ng mL -1 for the Nebraska EPA standard soil and 72 ng mL -1 for the Ottawa sand sample. An expedient and practical derivatization method for 3Q, a chemical warfare degradation product difficult to detect by GC/MS, has been realized using trichloroethyl chloroformate. The reaction provides 3Q-Troc, a derivative with better detectability than 3Q by electron ionization GC/MS such as peak sharpness and a unique mass spectrum for its unambiguous identification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗