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DOE OSTI2024

Integrate Latimer Controls' Solution into RTAC (CRADA Final Report, CRD-23-24672)

Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.

14 SOLAR ENERGY↗

DOE OSTI2023

Leveraging peptide–cellulose interactions to tailor the hierarchy and mechanics of peptide–polymer hybrids

Inspired by spider silk's hierarchical diversity, we leveraged peptide motifs with the capability to tune structural arrangement for controlling the mechanical properties of a conventional polymer framework. The addition of nanofiller with hydrogen bonding sites was used as another pathway towards hierarchical tuning via matrix–filler interactions. Specifically, peptide–polyurea hybrids (PPUs) were combined with cellulose nanocrystals (CNCs) to develop mechanically-tunable nanocomposites via tailored matrix–filler interactions (or peptide–cellulose interactions). In this material platform, we explored the effect of these matrix–filler interactions on the secondary structure, hierarchical ordering, and mechanical properties of the peptide hybrid nanocomposites. Interactions between the peptide matrix and CNCs occur in all of the PPU/CNC nanocomposites, preventing α-helical ordering, but promoting inter-molecular hydrogen bonded β-sheet formation. Depending on peptide and CNC content, the Young's modulus varies from 10 to 150 MPa. Unlike conventional cellulose-reinforced polymer nanocomposites, the mechanical properties of these composite materials are dictated by a balance of CNC reinforcement, peptidic ordering, and microphase-separated morphology. This research highlights that leveraging peptide–cellulose interactions is a strategy to create materials with targeted mechanical properties for a specific application using a limited selection of building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Bioproduction, bioprotection, and biocontainment in multi-kingdom microbial systems with 3D spatial control

Engineered living materials (ELMs) are a class of hybrid materials that include engineered microbes encapsulated by a polymer matrix. The biotic and abiotic components define the ELMs design space and can be altered to improve performance and function. While current synthetic materials in the field display robust biocompatibility with both native and engineered living systems, we have a limited understanding of how to leverage three-dimensional (3D) form factors to spatially organize and control microbial dynamics within the material. Motivated by this knowledge gap, we employed extrusion-based 3D printing to fabricate multi-kingdom hydrogel constructs for the encapsulation of both single and multi-kingdom microbial systems. Core–shell cubic constructs enabled the spatial organization of a constitutive multi-kingdom system of levodopa (L-DOPA)-producing E. coli and betaxanthins (BXN)-producing S. cerevisiae. This spatial organization in 3D materials can introduce precise control over bioproduction, bioprotection, and biocontainment features that are critical to the efficacy of current ELMs. The relative spatial organization of the organisms, as well as the surface area-to-volume ratio were investigated to determine how these design elements impact microbial behavior (metabolite production, growth, expression, and cell distribution) over time. We demonstrated that F127-bis-urethane methacrylate (F127-BUM) core–shell geometries enable the hierarchical 3D printing of multi-kingdom constructs, offering customizable control over bioproduction, bioprotection, and biocontainment. With the optimization of these core–shell structures for continuous bioproduction, these ELMs could be deployed as compact and sustainable bioreactors in remote environments.

additive manufacturing↗

DOE OSTI2022

Multifunctional nanopore electrode array method for characterizing and manipulating single entities in attoliter-volume enclosures

Structurally regular nanopore arrays fabricated to contain independently controllable annular electrodes represent a new kind of architecture capable of electrochemically addressing small collections of matter—down to the single entity (molecule, particle, and biological cell) level. Furthermore, these nanopore electrode arrays (NEAs) can also be interrogated optically to achieve single entity spectroelectrochemistry. Larger entities such as nanoparticles and single bacterial cells are investigated by dark-field scattering and potential-controlled single-cell luminescence experiments, respectively, while NEA-confined molecules are probed by single molecule luminescence. By carrying out these experiments in arrays of identically constructed nanopores, massively parallel collections of single entities can be investigated simultaneously. The multilayer metal–insulator design of the NEAs enables highly efficient redox cycling experiments with large increases in analytical sensitivity for chemical sensing applications. NEAs may also be augmented with an additional orthogonally designed nanopore layer, such as a structured block copolymer, to achieve hierarchically organized multilayer structures with multiple stimulus-responsive transport control mechanisms. Finally, NEAs constructed with a transparent bottom layer permit optical access to the interior of the nanopore, which can result in the cutoff of far-field mode propagation, effectively trapping radiation in an ultrasmall volume inside the nanopore. Furthermore, the bottom metal layer may be used as both a working electrode and an optical cladding layer, thus, producing bifunctional electrochemical zero-mode waveguide architectures capable of carrying out spectroelectrochemical investigations down to the single molecule level.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Band gap predictions of double perovskite oxides using machine learning

Abstract The compositional and structural variety inherent to oxide perovskites spawn wide-ranging applications. In perovskites, the band gap E g , a key material parameter for these applications, can be optimally controlled by varying the composition. Here, we implement a hierarchical screening process in which two cross-validated and predictive machine learning models for band gap classification and regression, trained using exhaustive datasets that span 68 elements of the periodic table, are applied sequentially. The classification model separates wide band gap materials, with E g ≥ 0.5 eV, from materials which have zero or relatively small band gaps, namely E g < 0.5 eV, and the second regression model quantitatively predicts the gap value of the wide band gap compounds. The study down-selects 13,589 cubic oxide perovskite compositions that are predicted to be experimentally formable, thermodynamically stable, and have a wide band gap. Of these, a subset of 310 compounds, which are predicted to be stable and formable with a confidence greater than 90%, are identified for further investigation. Our models are methodically analyzed via performance metrics and inter-dependence of model features to gain physical insight into the band gap prediction problem. Design maps to identify the variation of band gap with substitution of different elements are also presented.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Effects of catalyst droplets on wire growth and the resulting branched structures during VLS growth

Vapor-liquid-solid (VLS) method is vastly employed to grow hierarchical structures with unique properties. However, key questions remain, such as what controls the branched structures and what the roles of catalyst droplet size are during the growth. Here, an in-depth understanding of the kinetics of the nucleation, growth, and subsequent coalescence processes of Bi liquid catalyst droplets is provided by direct observation of PbSe branched wire growth in an environmental transmission electron microscope. This brings a kinetic control of the branch density by varying the parameters, such as temperature. In addition, the dependence of wire growth rate on the catalyst droplet size is revealed, i.e., the smaller the catalyst size the larger the wire growth rate, unlike the wire growth controlled by Gibbs-Thomson effect, possibly due to different mass transport pathways and atomic surface diffusion. These results extend the fundamental understanding of the VLS growth mechanism of branched structures and benefit the structure design of hierarchical materials with tailored properties.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Modelica-based system modeling for studying control-related faults in chiller plants and boiler plants serving large office buildings

System modeling is critical when studying operation faults in chiller plants and boiler plants. However, current fault models have difficulties faithfully representing the operation of chiller plants and boiler plants under the effects of those faults, especially the control-related ones. In this study, we present a systematic method to develop high-fidelity models for approximating the behaviors of chiller plants and boiler plants under faulty conditions. Compared to existing ones, the resulting fault models have two advantages: first, they better characterize the dynamic patterns in the system operation. In those models, control architecture and control logic are faithfully implemented. Thus, they can be used to study control-related faults, such as incorrect staging control due to sensor bias and mistuned feedback control. Second, they are readily extensible and can support large-scale investigations to explore different faulty conditions/scenarios. Those models are established in a hierarchical structure while modules in each layer can be redeclared and parameterized at upper layers. In such a case, modifications to the models can be realized through model modifiers and the process can be easily streamlined with scripts. We applied the proposed models in a comprehensive fault impact evaluation of the 13 control-related faults of chiller and boiler plants. In this evaluation, the proposed plant model is coupled with the EnergyPlus thermal load model to study the impact of various faulty scenarios. Based on the evaluation results, we identified the faults that have the most significant impacts on the operation of the chiller and boiler plants, respectively. We also found that the relationship between the impacts of the studied faults and the severity level of the faults are highly non-linear

Huang, Sen↗

DOE OSTI2023

Mechanical responses of architected boron carbide-aluminum lattice composites fabricated via reactive metallic infiltration of hierarchical pore structures

The incorporation of micro and nanoscale constituents in a hierarchical order improves mechanical properties of bulk structures while inducing controlled deformation. However, these features have seldomly been applied to the fabrication of cermet materials due to manufacturing constraints. Here, overcoming previous limitations, boron carbide cermets with embedded aluminum lattices were produced using a combination of additive manufacturing and gelcasting techniques. Kelvin cell and octet truss scaffolds were printed, cast and burned out so the negative volume could be infiltrated with metal to form an architected cermet. Computed microtomography scans reveal full aluminum infiltration of the volume with high fidelity to the target architecture. Equibiaxial flexural tests showed localized crack propagation in lattice-reinforced cermets and that samples with imbedded architecture required nearly double the energy for complete failure. Overall, the addition of an internal aluminum lattice limits abrupt fracture of the composite and provides a method for tuning its mechanical response with architected ratios of metal to ceramic.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Bridging 20 Years of Soil Organic Matter Frameworks: Empirical Support, Model Representation, and Next Steps

Abstract In the past few decades, there has been an evolution in our understanding of soil organic matter (SOM) dynamics from one of inherent biochemical recalcitrance to one deriving from plant‐microbe‐mineral interactions. This shift in understanding has been driven, in part, by influential conceptual frameworks which put forth hypotheses about SOM dynamics. Here, we summarize several focal conceptual frameworks and derive from them six controls related to SOM formation, (de)stabilization, and loss. These include: (a) physical inaccessibility; (b) organo‐mineral and ‐metal stabilization; (c) biodegradability of plant inputs; (d) abiotic environmental factors; (e) biochemical reactivity and diversity; and (f) microbial physiology and morphology. We then review the empirical evidence for these controls, their model representation, and outstanding knowledge gaps. We find relatively strong empirical support and model representation of abiotic environmental factors but disparities between data and models for biochemical reactivity and diversity, organo‐mineral and ‐metal stabilization, and biodegradability of plant inputs, particularly with respect to SOM destabilization for the latter two controls. More empirical research on physical inaccessibility and microbial physiology and morphology is needed to deepen our understanding of these critical SOM controls and improve their model representation. The SOM controls are highly interactive and also present some inconsistencies which may be reconciled by considering methodological limitations or temporal and spatial variation. Future conceptual frameworks must simultaneously refine our understanding of these six SOM controls at various spatial and temporal scales and within a hierarchical structure, while incorporating emerging insights. This will advance our ability to accurately predict SOM dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Non-unimodal and non-concave relationships in the network Macroscopic Fundamental Diagram caused by hierarchical streets

Unimodal, concave relationships between average network productivity and accumulation or density aggregated across spatially compact regions of urban networks—so called network Macroscopic Fundamental Diagrams (MFDs)—have recently been shown to exist on homogeneous street networks. When present, MFD relationships facilitate the modeling of traffic congestion at a regional level and have led to the development of various regional traffic control strategies. However, real street networks are not homogeneous—they generally have a hierarchical structure where some streets (e.g., arterials) promote higher mobility than others (e.g., local roads). Here, this paper examines how the presence of hierarchical roadway structures may potentially cause non-unimodal patterns in a network's MFD. These are observed using three types of tools: analytical models of simple network structures, simulations of various idealized roadway networks, and empirical data. The impacts of street hierarchy depend on how vehicles use different roadway types to move within the network; i.e., their routing strategy. The findings suggest that the presence of roadway hierarchies may lead to MFDs that have non-unimodal or non-concave patterns on the free-flow branch when vehicles route themselves according to user equilibrium principles, which is closest to what would be observed in realistic situations. Such patterns are contrary to what is traditionally assumed in most MFD-based modeling frameworks. However, the unimodal and concave MFD should be expected under system optimal routing conditions that maximize network productivity for a given traffic state.

42 ENGINEERING↗

DOE OSTI2023

Improving EV Charging Resilience under a Device Fault Condition

This paper presents a multi-layer control framework that can improve resilience of an electric vehicle (EV) charging system when a device fault occurs in an EV charger power converter. The multi-layer framework built in a hierarchical structure allows fast protection and device fault ride through (DFRT), active status monitoring, and control optimization to improve the charging resilience. The feasibility and the effectiveness of the DFRT response and the control optimization are verified through controller hardware-in-the-loop demonstration.

Kim, Namwon↗

DOE OSTI2020

Hierarchical Polyelemental Nanoparticles as Bifunctional Catalysts for Oxygen Evolution and Reduction Reactions

Efficient electrocatalysts are critical in various clean energy conversion and storage systems. Polyelemental nanomaterials are attractive as multi-functional catalysts due to their wide compositions and synergistic properties. However, controlled synthesis of polyelemental nanomaterials is difficult due to their complex composition. Herein, we present a one-step synthetic strategy to fabricate a hierarchical polyelemental nanomaterial, which contains ultrasmall precious metal nanoparticles (IrPt, ~5 nm) anchored on spinel-structure transition metal oxide nanoparticles. The polyelemental nanoparticles serve as excellent bifunctional catalysts for the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR). The mass catalytic activity of the polyelemental nanoparticles is 7-times higher than that of Pt in ORR and 28-times that of Ir in OER at the same overpotentials, demonstrating the high activity of the bifunctional electrocatalyst. We attribute this outstanding performance to the controlled multiple elemental composition, mixed chemical states, and large electroactive surface area. The hierarchical nanostructure and polyelemental design of these nanoparticles offers a general and powerful alternative material for catalysis, solar cells, and more.

25 ENERGY STORAGE↗

DOE OSTI2024

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

closed-loop validation↗

DOE OSTI2025

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

14 SOLAR ENERGY↗

DOE OSTI2024

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services: Preprint

closed-loop validation↗

DOE OSTI2023

Hourglass–Shaped Nanocages with Concaved Structures Based on Selective Self–Complementary Coordination Ligands and Tunable Hierarchical Self–Assembly

Three-dimensional (3D) structures constructed via coordination-driven self-assemblies have recently garnered increasing attention due to the challenges in structural design and potential applications. In particular, developing new strategy for the convenient and precise self-assemblies of 3D supramolecular structures is of utmost interest. Introducing the concept of self-coordination ligands, herein the design and synthesis of two meta-modified terpyridyl ligands with selective self-complementary coordination moiety are reported and their capability to assemble into two hourglass-shaped nanocages SA and SB is demonstrated. Within these 3D structures, the meta-modified terpyridyl unit preferably coordinates with itself to serve as concave part. By changing the arm length of the ligands, hexamer (SA) and tetramer (SB) are obtained respectively. In-depth studies on the assembly mechanism of SA and SB indicate that the dimers could be formed first via self-complementary coordination and play crucial roles in controlling the final structures. Moreover, both SA and SB can go through hierarchical self-assemblies in solution as well as on solid–liquid interface, which are characterized by transmission electron microscope (TEM) and scanning tunneling microscopy (STM). As a result, it is further demonstrated that various higher-order assembly structures can be achieved by tuning the environmental conditions.

3D metallo-supramolecules↗

DOE OSTI2024

Assembly of short amphiphilic peptoids into nanohelices with controllable supramolecular chirality

Abstract A long-standing challenge in bioinspired materials is to design and synthesize synthetic materials that mimic the sophisticated structures and functions of natural biomaterials, such as helical protein assemblies that are important in biological systems. Herein, we report the formation of a series of nanohelices from a type of well-developed protein-mimetics called peptoids. We demonstrate that nanohelix structures and supramolecular chirality can be well-controlled through the side-chain chemistry. Specifically, the ionic effects on peptoids from varying the polar side-chain groups result in the formation of either single helical fiber or hierarchically stacked helical bundles. We also demonstrate that the supramolecular chirality of assembled peptoid helices can be controlled by modifying assembling peptoids with a single chiral amino acid side chain. Computational simulations and theoretical modeling predict that minimizing exposure of hydrophobic domains within a twisted helical form presents the most thermodynamically favorable packing of these amphiphilic peptoids and suggests a key role for both polar and hydrophobic domains on nanohelix formation. Our findings establish a platform to design and synthesize chiral functional materials using sequence-defined synthetic polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Green Electrode Processing Enabled by Fluoro-Free Multifunctional Binders for Lithium-Ion Batteries

The eco-friendly processing of conjugated polymer binder for lithium-ion batteries demands improved polymer solubility by introducing functional moieties, while this strategy will concurrently sacrifice polymer conductivity. Employing the polyfluorene-based binder poly(2,7-9,9 (di(oxy-2,5,8-trioxadecane))fluorene) (PFO), soluble in water-ethanol mixtures, a novel approach is presented to solve this trade-off, which features integration of aqueous solution processing with subsequent controlled thermal-induced cleavage of solubilizing side chains, to produce hierarchically ordered structures (HOS). The thermal processing can enhance the intermolecular π–π stacking of polyfluorene backbone for better electrochemical performance. Notably, HOS-PFO demonstrated a substantial 6–7 orders of magnitude enhancement in electronic conductivity, showcasing its potential as a functional binder for lithium-ion batteries. As an illustration, HOS-PFO protected SiOx anodes, utilizing in situ side chain decomposition of PFO surrounding SiOx particles after aqueous processing are fabricated. HOS-PFO contributed to the stable cycling and high-capacity retention of practical SiOx anodes (3.0 mAh cm -2 ), without the use of any conducting carbon additives or fluorinated electrolyte additives. It is proposed that this technique represents a universal approach for fabricating electrodes with conjugated polymer binders from aqueous solutions without compromising conductivity.

25 ENERGY STORAGE↗