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At least 1,315 records · Page 73

A Bayesian Approach to Predict Solubility Parameters

Abstract Solubility is a ubiquitous phenomenon in many aspects of material science. While solubility can be determined by considering the cohesive forces in a liquid via the Hansen solubility parameters (HSP), quantitative structure–property relationship models are often used for prediction, notably due to their low computational cost. Here, gpHSP, an interpretable and versatile probabilistic approach to determining HSP, is reported. Our model is based on Gaussian processes, a Bayesian machine learning approach that provides uncertainty bounds to prediction. gpHSP achieves its flexibility by leveraging a variety of input data, such as SMILES strings, COSMOtherm simulations, and quantum chemistry calculations. gpHSP is built on experimentally determined HSP, including a general solvents set aggregated from the literature, and a polymer set experimentally characterized by this group of authors. In all sets, a high degree of agreement is obtained, surpassing well‐established machine learning methods. The general applicability of gpHSP to miscibility of organic semiconductors, drug compounds, and in general solvents is demonstrated, which can be further extended to other domains. gpHSP is a fast and accurate toolbox, which could be applied to molecular design for solution processing technologies.

Sanchez‐Lengeling, Benjamin↗

Multi-scale investigation on mechanical behavior and microstructural alteration of C-S-H in carbonated Alite paste

Carbonation treatment is a promising option to enhance recycled concrete aggregate (RCA) quality and eventually improve concrete performance. This study investigated the multi-scale mechanical properties of calcium silicate hydrates (C-S-H) in a mature alite paste subjected to accelerated carbonation treatment by testing macro compressive strength, microhardness and nanoindentation. The results show that, carbonation treatment resulted in a heterogeneous distribution of carbonation products in the alite sample. Reinforcement of C-S-H by the randomly precipitated calcite and vaterite crystals prevailed over the nano-structural and compositional alteration of C-S-H induced by carbonation, leading to an increase of nano-indentation modulus at the edge of the sample. Also, the microhardness at the edge zone was markedly higher than that at the core of the carbonated sample. The carbonated peripheral zone with improved nano-scale modulus and microhardness was likely serving as a “hard shell”, contributing to the improved macro compressive strength. The new insights into the multi-scale mechanical properties of carbonated C-S-H contribute to further understanding of the enhanced properties of RCA after carbonation treatment.

36 MATERIALS SCIENCE↗

Chemomechanical Coupling in Hexameric Protein–Protein Interfaces Harnesses Energy within V-Type ATPases

ATP synthase is the most prominent bioenergetic macromolecular motor in all life forms, utilizing the proton gradient across the cell membrane to fuel the synthesis of ATP. Notwithstanding the wealth of available biochemical and structural information inferred from years of experiments, the precise molecular mechanism whereby vacuolar (V-type) ATP synthase fulfills its biological function remains largely fragmentary. Recently, crystallographers provided the first high-resolution view of ATP activity in Enterococcus hirae V1-ATPase. Employing a combination of transition-path sampling and high-performance free-energy methods, the sequence of conformational transitions involved in a functional cycle accompanying ATP hydrolysis has been investigated in unprecedented detail over an aggregate simulation time of 65 μs. Our simulated pathways reveal that the chemical energy produced by ATP hydrolysis is harnessed via the concerted motion of the protein–protein interfaces in the V1-ring, and is nearly entirely consumed in the rotation of the central stalk. Surprisingly, in an ATPase devoid of a central stalk, the interfaces of this ring are perfectly designed for inducing ATP hydrolysis. However, in a complete V1-ATPase, the mechanical property of the central stalk is a key determinant of the rate of ATP turnover. The simulations further unveil a sequence of events, whereby unbinding of the hydrolysis product (ADP + Pi) is followed by ATP uptake, which, in turn, leads to the torque generation step and rotation of the center stalk. Molecular trajectories also bring to light multiple intermediates, two of which have been isolated in independent crystallography experiments.

Chemistry↗

Lignin-polysaccharide interactions in plant secondary cell walls revealed by solid-state NMR

Lignin is a complex aromatic biopolymer that strengthens and waterproofs plant secondary cell walls, enabling mechanical stability in trees and long-distance water transport in xylem. Lignin removal is a key step in paper production and biomass conversion to biofuels, motivating efforts to re-engineer lignin biosynthesis. However, the physical nature of lignin’s interactions with wall polysaccharides is not well understood. Here we show that lignin self-aggregates to form highly hydrophobic and dynamically unique nanodomains, with extensive surface contacts to xylan. Solid-state NMR spectroscopy of intact maize stems, supported by dynamic nuclear polarization, reveals that lignin has abundant electrostatic interactions with the polar motifs of xylan. Lignin preferentially binds xylans with 3-fold or distorted 2-fold helical screw conformations, indicative of xylans not closely associated with cellulose. These findings advance our knowledge of the molecular-level organization of lignocellulosic biomass, providing the structural foundation for optimization of post-harvest processing for biofuels and biomaterials.

59 BASIC BIOLOGICAL SCIENCES↗

Capillary evaporation of the ionic liquid [EMIM][BF 4 ] in nanoscale solvophobic confinement

We report that solvent density fluctuations play a crucial role in liquid-vapor transitions in solvophobic confinement and can also be important for understanding solvation of polar and apolar solutes. In the case of ionic liquids (ILs), density fluctuations can be used to understand important processes in the context of nanoscale aggregation and colloidal self-assemblies. In this article, we explore the nature of density fluctuations associated with capillary evaporation of the IL 1-ethyl-3-methylimidazolium tetrafluoroborate ([EMIM][BF4]) in the confined region of model solvophobic nanoscale sheets by using molecular dynamics simulations combined with non-Boltzmann sampling techniques. We demonstrate that density fluctuations of the confined IL play an important role in capillary evaporation, suggesting analogies to dewetting transitions involving water. Lastly, significant changes in the interfacial structure of the IL are also detailed and suggested to underlie a non-classical (non-parabolic) dependence of the free energy barrier to evaporation on the degree of confinement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The ability of lens alpha crystallin to protect against heat-induced aggregation is age-dependent

Alpha crystallin was prepared from newborn and aged bovine lenses. SDS-PAGE and tryptic peptide mapping demonstrated that both preparations contained only the alpha-A and alpha-B chains, with no significant contamination of other crystallins. Compared with alpha crystallin from the aged lens, alpha crystallin from the newborn lens was much more effective in the inhibition of beta L crystallin denaturation and precipitation induced in vitro by heat. Together, these results demonstrate that during the aging process, the alpha crystallins lose their ability to protect against protein denaturation, consistent with the hypothesis that the alpha crystallins play an important role in the maintenance of protein native structure in the intact lens.

NASA Discipline Cell Biology↗

Incorporation of Membrane Proteins Into Bicontinuous Microemulsions Through Winsor‐III System‐Based Extraction

Abstract The membrane proteins (MP) α‐synuclein (ASYN) and bacteriorhodopsin (BR) were readily incorporated into bicontinuous microemulsions (BμEs) formed by two microemulsion systems: water/heptane/Aerosol‐OT (AOT)/CK‐2,13 and water/dodecane/sodium dodecyl sulfate (SDS)/1‐pentanol. (CK‐2,13 is an alkyl ethoxylate possessing two alkyl tail groups of carbon chain length 2 and 13 and an average degree of ethoxylation of 5.6.) MP were encapsulated in BμEs through preparation of Winsor‐III systems at optimal salinity, with the anionic surfactants AOT and SDS providing the driving force for extraction. Dissolution of ASYN in BμEs greatly increased the former's α‐helicity, similar to ASYN's behavior in the presence of biomembranes, while BμE‐ and vesicle‐encapsulated BR possessed similar secondary structure. Small‐angle neutron scattering (SANS) results clearly demonstrated the direct interaction of MP with the surfactants, resulting in a decrease of surface area per volume for surfactant monolayers due to decreased surfactant efficiency. The SANS signal for ASYN was isolated through the use of neutron contrast matching for the surfactants through partial deuteration of water and oil, one of the first reports of contrast matching for BμEs in the literature. The SANS results of the contrast‐matched sample reflected similar aggregation for ASYN in BμEs as was reported previously for vesicles and SDS solution. This study demonstrates the potential use of BμEs as MP host systems for conducting biochemical reactions such as the conversion of sunlight into adenosine triphosphate by BR and studying the fundamental behavior of MP, such as the role of ASYN dysfunction in Parkinson's disease, as well as for isolation and purification of MP via Winsor‐III‐based extraction.

Hayes, Douglas G.↗

Effects of carbon concentration on the local atomic structure of amorphous GST

Ge-Sb-Te (GST) alloys are leading phase-change materials for data storage due to the fast phase transition between amorphous and crystalline states. Ongoing research aims at improving the stability of the amorphous phase to improve retention. This can be accomplished by the introduction of carbon as a dopant to Ge 2 Sb 2 Te 5 , which is known to alter the short- and mid-range structure of the amorphous phase and form covalently bonded C clusters, both of which hinder crystallization. The relative importance of these processes as a function of C concentration is not known. Here we used molecular dynamics simulation based on density functional theory to study how carbon doping affects the atomic structure of GST-C. Carbon doping results in an increase in tetrahedral coordination, especially of Ge atoms, and this is known to stabilize the amorphous phase. We observe an unexpected, non-monotonous trend in the number of tetrahedral bonded Ge with the amount of carbon doping. Our simulations show an increase in the number of tetrahedral bonded Ge up to 5 at.% C, after which the number saturates and begins to decrease above 14 at.% C. The carbon atoms aggregate into clusters, mostly in the form of chains and graphene flakes, leaving less carbon to disrupt the GST matrix at higher carbon concentrations. Different degrees of carbon clustering can explain divergent experimental results for recrystallization temperature for carbon doped GST.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗

Preparation and Characterization of Magnetite–Chitosan Nanoparticles and Evaluation of Their Cytotoxicity Effects on MCF7 and Fibroblast Cells

Nowadays, magnetic nanoparticles play a key role in drug treatment. However, if they are uncoated, they might aggregate and cause embolism in drug delivery. To avoid this, they are generally coated with polymers. In this investigation, magnetic nanoparticles (MNPs) were coated with chitosan through in situ co-precipitation process and their properties in addition to their cytotoxicity in MCF7 and fibroblast cells were analyzed. The results showed MNPs–chitosan nanoparticles would contain an average mean diameter of 32 nm and a saturation magnetization (M{sub S}) value of 38.87 emu/g. To characterize the synthesized nanoparticles in terms of structural, morphological and magnetic properties, Fourier transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), thermal gravimetric analysis (TGA) and vibrating sample magnetometry (VSM) studies were used. Toxicity test was also done to investigate whether their presence would cause any toxicity in the body; in addition, antibacterial assay was done to analyze if nanoparticles could be used as an antimicrobial agent.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Effect of Corona Block Length on the Structure and Chain Exchange Kinetics of Block Copolymer Micelles

The effect of corona block length on micelle structure and molecular chain exchange kinetics has been investigated for a series of dilute poly(styrene)-b-poly(ethylene-alt-propylene) (SEP) diblock copolymer micelles with constant PS core block length ($\langle$N core $\rangle$ ≈ 255) but different PEP corona block lengths (($\langle$N corona $\rangle$ = 256–2080), using a combination of dynamic light scattering (DLS), small-angle X-ray scattering (SAXS), and time-resolved small-angle neutron scattering (TR-SANS). Smaller core radii and aggregation numbers, but significantly thicker corona layers (proportional to N corona 0.7 ), were observed with increasing corona block length. Furthermore, 2 orders of magnitude more rapid chain exchange was observed in SEP micelles with the longest corona block compared to the shortest. This effect is attributed to the entropic gain arising from the relief of corona chain stretching upon chain expulsion. We further extend a previous theoretical model by explicitly including a corona term associated with the entropy change in the chain exchange process, which successfully explains the influence of the corona blocks on chain exchange. Our results are in excellent agreement with simulation results of Li and Dormidontova but are apparently contradictory with Halperin and Alexander’s theory for hairy micelles and with experimental observations in two other systems that the exchange kinetics slow down with increasing corona block length. These discrepancies reveal unanticipated complexity regarding the role of the corona block in chain exchange.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Composite Structures with Emissive Quantum Dots for Light Enhancement

Since their inception, quantum dots have proven to be advantageous for light management applications due to their high brightness and well-controlled absorption, scattering, and emission properties. As quantum dots become commercially available at large scale, the need for robust, stable, and flexible optical components continues to drive the development of robust and flexible quantum dot composite materials. In this review, after a thorough introduction to quantum dots, discussion delves into methods for fabricating quantum dot loaded composite optical elements such as thin films, microfabricated patterns, and microstructures. The importance of surface chemistry and ligand engineering, host matrixes, wet processing, and unique patterning methodologies is presented by considering photostability, aggregation, and phase separation of quantum dots in corresponding composites. With regard to prospective optical applications of quantum dot materials, emphasis is placed on light emitting and guiding composite materials for lasing applications, specifically whispering gallery mode-based photonic microsystems. These developments will enable novel flexible, portable, and miniaturized optoelectronic devices such as light-emitting diodes, flexible pixelated displays, solar cells, large-area microwaveguides, omnidirectional micromirrors, optical metasurfaces, and directional microlasers.

36 MATERIALS SCIENCE↗

Controlling Structural, Electronic, and Energy Flow Dynamics of Catalytic Processes through Tailored Nanostructures

MoS 2 (molybdenum disulfide) is a highly-versatile catalyst material for support of numerous reactions from hydrodesulfurization and denitrogenation to the focus of this renewal proposal: hydrogenation of CO/CO 2 towards (higher) alcohols. At the same time, MoS 2 is a non-toxic, environmentally-benign and rather inert material- which under ambient conditions for some time has served as a lubricant and, more recently, as next-generation electronic material. The apparent contrast between inertness and stability in ambient, and catalytic activity under reactive conditions is puzzling and calls for a synergistic theoretical and experimental investigation with the long-term objective of enabling the rational design of MoS 2 -based catalysts for alcohol-formation reactions by providing a microscopic understanding of the environmental factors that determines site activity and selectivity. Our research project seeks answers to the questions (a) what conformation does MoS 2 adopt under reaction conditions (as opposed to that under ultrahigh vacuum and low temperatures)?; (b) what reaction pathways exist on such a material?; (c) how can the local environment of the active sites be manipulated so as to make MoS 2 an efficient catalyst for production of higher alcohol from syngas? In particular, research strategies will explore how the basal plane composed of sulfur atoms can be activated so as to exhibit a reactivity of its own, by addressing three research targets and building on extensive preliminary and enabling work: (1) vacancies and vacancy aggregates on the basal plane; (2) non-local catalyst transformation through alkali doping, hydrogenation and phase transition; (3) fabrication of a metal-nanoparticle-activated MoS 2 system, in which particle anchoring, reactive sites and pathways as well as selectivity are controlled by design, as an example of predictive development of a catalyst material,. All strategies are directed to improve the efficacy of the key reactive sites and selectivity of chemical pathways by design, to replace the inefficient methodology of trial and error in catalyst development. This research project represents a synergistic combination of computational guidance, foundational surface-science-based experiments and validation under reactive conditions that aims at transformative new insights into the working of MoS 2 -based hydrogenation-catalysts, a topic squarely at the center of the interest of DOE BES. Guided and led by Talat Rahman, a computational physicist, this project will apply density functional theory to understand structure, reaction pathways and chemical potentials associated with MoS 2 -based CO/CO 2 hydrogenation, augmented by kinetic Monte Carlo methods for reaction rates and prefactors as well as ab-initio molecular dynamics for evaluation of thermal stability. Complementary experimental input and validation will originate from co-PI Ludwig Bartels, a physical chemist and materials scientist, whose group focuses on local imaging and preparation of MoS 2 materials, from co-PI Peter Dowben, an experimental physicist, whose group is expert in the spectroscopy of occupied and unoccupied electronic states, and from senior collaborator Michael White of Brookhaven National Laboratory, whose group generates high-resolution electronic and activity information on size-selected well-defined metal chalcogenide clusters. This collaborative effort will enable a comprehensive understanding of the correlation of structural integrity and catalytic activity of MoS 2 in forms ranging from extended films to individual particles with known geometries and binding sites. Alcohol formation from syngas is a rapidly emerging application that has great potential through facile, economic, and decentralized biomass gasification. CO 2 activation is one of the most pressing concerns of our time: increasing CO 2 levels in the atmosphere change the climate and expose the globe to environmental transformations with the potential for enormous economic and societal impact. We will investigate CO/CO 2 hydrogenation via an interdisciplinary research collaboration with established synergy – one that, in accordance with the mission of the DOE, involves accredited Hispanic-Serving Institutions and that, through student exchange with international collaborators and National Labs, will directly benefit a broad spectrum of communities and generate human resources in sciences essential to their future.

2D materials↗

Computational Modeling of Exciton-Bath Hamiltonians for Light Harvesting 2 and Light Harvesting 3 Complexes of Purple Photosynthetic Bacteria at Room Temperature

Light harvesting 2 (LH2) complex is the primary component of the photosynthetic unit of purple bacteria that is responsible for harvesting and relaying excitons. The electronic absorption line shape of LH2 contains two major bands at 800 and 850 nm wavelength regions. Under low light conditions, some species of purple bacteria replace LH2 with light harvesting 3 (LH3), a variant form with almost the same structure as the former but with distinctively different spectral features. The major difference between the absorption line shapes of LH2 and LH3 is the shift of the 850 nm band of the former to a new 820 nm region. The microscopic origin of this difference has been the subject of some theoretical/computational investigations. However, the genuine molecular level source of such a difference is not clearly understood yet. This work reports a comprehensive computational study of LH2 and LH3 complexes so as to clarify different molecular level features of LH2 and LH3 complexes and to construct simple exciton-bath models with a common form. All-atomistic molecular dynamics simulations of both LH2 and LH3 complexes provide detailed molecular level structural differences of bacteriochlorophylls (BChls) in the two complexes, in particular, in their patterns of hydrogen bonding (HB) and torsional angles of the acetyl group. Time-dependent density functional theory calculation of the excitation energies of BChls for structures sampled from the MD simulations suggests that the observed differences in the HB and torsional angles cannot fully account for the experimentally observed spectral shift of LH3. Potential sources that can explain the actual spectral shift of LH3 are discussed, and their magnitudes are assessed through fitting of experimental line shapes. Furthermore, these results demonstrate the feasibility of developing simple exciton-bath models for both LH2 and LH3, which can be employed for large-scale exciton quantum dynamics in their aggregates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emergent Nanostructure and Ion Transport in Polyzwitterion/Polyanion Blends

Solid polymer electrolytes (SPEs) hold great promise for the advancement of next-generation energy storage devices. However, the ion transport mechanism in SPEs remains poorly understood. In this study, we investigate blends of poly(1-(3-sulfonatopropyl)-2-vinylpyridinium) (P2VPPS) and poly(lithium (trifluoromethane)sulfonimide methacrylate) (P(MTFSI)Li) of varying molar ratios to develop a mechanistic understanding of ionic conductivity in a miscible polyzwitterion/polyanion system. Polyanions can act as single-ion conductors, but conductivity is often prohibitively low due to the decreased segmental mobility and ion aggregation. Here, it is hypothesized that the introduction of a polyzwitterion would competitively interact with the polyanion charge groups to realize improvements in the conductivity. Attractive interactions between the polyanions and polyzwitterions are confirmed by the blend’s increased glass transition temperature using the Gordon–Taylor equation. Notably, an ordered local nanostructure (∼24 Å) emerged in the P2VPPS/P(MTFSI)Li system at certain compositions, as characterized by small-angle X-ray and neutron scattering (SAXS/SANS). Concurrent with the emergence of this structure, broadband dielectric spectroscopy confirmed improvements in ionic conductivity. The highest conductivity is observed at a specific blend ratio P2VPPS:P(MTFSI)Li = 0.2:1 in the glassy state and 0.3:1 in the rubbery state, corresponding to the lowest effective activation energy (E*). Coarse-grained molecular dynamics simulations further emphasize the role of complexation between polyzwitterion and polyanion chains, correlating with the emergence of a new peak in SAXS and SANS for the blends. This work provides a fresh perspective on the role of local structural design in developing SPEs and offers insights into the morphological effects on ionic conductivity.

chemical structure↗

Enhanced Activity of Heterogeneous Pd(II) Catalysts on Acid-Functionalized Metal–Organic Frameworks

Single-site heterogeneous catalysts (SSHCs) play important roles in fundamental science and technology, owing to the molecular level control of structure–support interactions that is possible in these systems. Recently, SSHCs supported by acidic oxides have attracted particular interest because catalytically active metal centers can be formed at the surface sites. Here, we incorporated a palladium SSHC in phosphated and sulfated metal–organic frameworks (MOFs), hafnium-based MOF-808 (Hf-MOF-808-PO 4 and Hf-MOF-808-SO 4 ). The structural and electronic properties of the Pd(II) sites coordinated to the acidic sites in these MOFs were investigated through X-ray photoelectron spectroscopy, vibrational spectroscopy, X-ray crystallographic techniques, catalytic studies, and quantum mechanical electronic structure calculations employing density functional theory. We demonstrated that the presence of node-bound acidic functional groups stabilizes the Pd(II) site in these MOFs, resulting in enhanced catalytic activities (compared to in the nonacid functionalized Hf-MOF-808) in the oxidative Heck reaction where Pd(II) is the active species. The density functional calculations support the interpretation that the acid functionalization of the MOF node can stabilize the Pd(0) intermediate state during the catalytic reactions, thereby suppressing Pd(0) aggregation leading to catalyst deactivation. Furthermore, these findings offer insights and methodology for the catalytic investigation of SSHCs in MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

VOLTTRON/volttron-GS

PNNL grid related applications Object oriented design intended to facilitate reuse and extensibility of system features. The template enforces that needed structure and behaviors are available. Users may inherit and adapt these structures and behaviors to meet their specific requirements. Recognizes separation of the transactive system calculations into (1) scheduling of assets, (2) balancing of supply and demand, and (3) coordination among independent agents. This separation facilitates useful computation boundaries in which computations can be completed without requiring end-to-end communication for each update. The code provides fundamental market solutions for balancing. The code provides mechanisms for inter-agent coordination. Allows event-driven agent interactions; not limited to prescribed time intervals. Aggregates value and electricity at nodes and conveys opportunities up and down through the network.

Hammerstrom, Don↗