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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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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Automated solar collector installation design including version management

Embodiments may include systems and methods to create and edit a representation of a worksite, to create various data objects, to classify such objects as various types of predefined “features” with attendant properties and layout constraints. As part of or in addition to classification, an embodiment may include systems and methods to create, associate, and edit intrinsic and extrinsic properties to these objects. A design engine may apply of design rules to the features described above to generate one or more solar collectors installation design alternatives, including generation of on-screen and/or paper representations of the physical layout or arrangement of the one or more design alternatives. Some embodiments may provide viewing, creating, and manipulating of multiple versions of a solar collector layout design for a particular installation worksite. The use of versions may allow analysis of alternative layouts, alternative feature classifications, and cost and performance data corresponding to alternative design choices. Version summary information providing a representative comparison between versions across a number of dimensions may be provided.

14 SOLAR ENERGY↗
DOE OSTI2025

Interface Engineering using Vapor Transport Deposited Perovskite Films for Solar Cells

The overarching goal of this project was to demonstrate the viability of vapor transport deposition (VTD) for the fabrication of efficient and stable metal-halide perovskite solar cells. VTD is a solvent-free alternative to conventional solution-processing of the light-absorbing, perovskite active layer. Since solution-processing frequently requires the use of toxic solvents, transition to a dry-processing approach has the potential to remove an obstacle to facile and economically meaningful commercialization. Further, VTD bears similarity to existing industrially-relevant processing approaches used for the production of thin-film CdTe solar modules, suggesting the potential for rapid adoption and transition to industry. The results described within this report offer design rules for the processing of metal-halide perovskites via VTD and new insights into the design of deposition systems to inform future applications.

14 SOLAR ENERGY↗
DOE OSTI2025

Autonomous phase mapping of gold nanoparticles synthesis with differentiable models of spectral shape

Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis, characterization, and data-driven decision-making. We present a closed-loop workflow for the on-demand synthesis and structural characterization of colloidal gold nanoparticles, enabling direct mapping from composition to nanoscale structure. Our framework leverages differentiable models of spectral shape to address two central tasks in self-driving labs: (a) phase mapping, or identifying compositional regions with distinct structural behavior; and (b) material retrosynthesis, or optimizing compositions for target structure. Using functional data analysis, we develop a data-driven model with generative pre-training, active learning, and high-throughput experiments to predict spectral responses across composition space. We demonstrate the approach on seed-mediated growth of gold nanoparticles, showcasing its ability to extract design rules, reveal secondary interactions, and efficiently navigate morphology space. Gradient-based optimization of the models enables inverse design, making this a unified platform.

36 MATERIALS SCIENCE↗
DOE OSTI2023

New Chemical Dopant and Counterion Mechanism for Organic Electrochemical Transistors and Organic Mixed Ionic–Electronic Conductors

Abstract Organic mixed ionic–electronic conductors (OMIECs) have varied performance requirements across a diverse application space. Chemically doping the OMIEC can be a simple, low‐cost approach for adapting performance metrics. However, complex challenges, such as identifying new dopant materials and elucidating design rules, inhibit its realization. Here, these challenges are approached by introducing a new n‐dopant, tetrabutylammonium hydroxide (TBA‐OH), and identifying a new design consideration underpinning its success. TBA‐OH behaves as both a chemical n‐dopant and morphology additive in donor acceptor co‐polymer naphthodithiophene diimide‐based polymer, which serves as an electron transporting material in organic electrochemical transistors (OECTs). The combined effects enhance OECT transconductance, charge carrier mobility, and volumetric capacitance, representative of the key metrics underpinning all OMIEC applications. Additionally, when the TBA + counterion adopts an “edge‐on” location relative to the polymer backbone, Coulombic interaction between the counterion and polaron is reduced, and polaron delocalization increases. This is the first time such mechanisms are identified in doped‐OECTs and doped‐OMIECs. The work herein therefore takes the first steps toward developing the design guidelines needed to realize chemical doping as a generic strategy for tailoring performance metrics in OECTs and OMIECs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tuning the Mechanical and Electric Properties of Conjugated Polymer Semiconductors: Side–Chain Design Based on Asymmetric Benzodithiophene Building Blocks

Understanding molecular design rules for stretchable polymer semiconductors is important for enabling next generation stretchable electronic circuits. To simultaneously improve both electrical properties and mechanical stretchability, a design strategy is reported in introducing conjugated rigid fused-rings with bulky side groups in semiconducting polymers. In this work, the understanding of this design concept is improved by systematically investigating the effect of different types of bulky side groups asymmetrically substituted on conjugated polymer semiconductor backbones. Specifically, four types of side groups are investigated, including naphthalene (NaPh), biphenyl (PhPh), thienylphenyl (ThPh), and alkylphenyl (C4Ph), asymmetrically substituted on benzodithiophene units, namely asy-BDT. With the four types of side groups installed on BDT-containing conjugated polymers in an asymmetrical fashion, it is observed that they reduced the polymer chain aggregation and film crystallinity, hence improving the film stretchability. Furthermore, the fully conjugated polymer back-bone allows maintenance of good charge carrier mobilities. Specifically, polymer PDPP-C4Ph (with C4Ph side groups) shows the highest mobility in the fully stretchable transistor and maintained its mobility even after being subjected to hundreds of stretching-releasing cycles at 25% strain. Altogether, the results provide anunderstanding of the use of asymmetrically substituted fused-ring conjugated polymer structures to tune mechanical and charge transport properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Electronically active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from π-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water-soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence–structure–function relations remain poorly characterized. Here, we employ coarse-grained molecular dynamics simulations within an active learning protocol employing deep representational learning and Bayesian optimization to efficiently identify molecules capable of assembling pseudo-1D nanoaggregates with good stacking of the electronically active π-cores. We consider the DXXX-OPV3-XXXD oligopeptide family, where D is an Asp residue and OPV3 is an oligophenylenevinylene oligomer (1,4-distyrylbenzene), to identify the top performing XXX tripeptides within all 20 3 = 8000 possible sequences. By direct simulation of only 2.3% of this space, we identify molecules predicted to exhibit superior assembly relative to those reported in prior work. Spectral clustering of the top candidates reveals new design rules governing assembly. This work establishes new understanding of DXXX-OPV3-XXXD assembly, identifies promising new candidates for experimental testing, and presents a computational design platform that can be generically extended to other peptide-based and peptide-like systems.

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

HetArch: Heterogeneous Microarchitectures for Superconducting Quantum Systems

Noisy Intermediate-Scale Quantum Computing (NISQ) has dominated headlines in recent years, with the longer-term vision of Fault-Tolerant Quantum Computation (FTQC) offering significant potential but at currently intractable resource costs and quantum error correction (QEC) overheads. For problems of interest, FTQC will require millions of physical qubits with long coherence times, high-fidelity gates, and compact sizes to surpass classical systems. Just as heterogeneous specialization has offered scaling benefits in classical computing, it is likewise gaining interest in FTQC. However, systematic use of heterogeneity in either hardware or software elements of FTQC systems remains a serious challenge due to the vast design space and the variable physical constraints. This paper meets the challenge of making heterogeneous FTQC design practical by introducing HetArch, a toolbox for designing heterogeneous quantum systems, and using it to explore heterogeneous design scenarios. Using a hierarchical approach, we successively break quantum algorithms into smaller operations (akin to classical application kernels), thus greatly simplifying the design space and resulting tradeoffs. Specializing to superconducting systems, we then design optimized heterogeneous hardware composed of varied superconducting devices, abstracting physical constraints into design rules that enable devices to be assembled into standard cells optimized for specific operations, which, in turn, form heterogeneous modules optimized for quantum subroutines. Finally, we provide a heterogeneous design space exploration framework which reduces the simulation burden by a factor of 10^4 or more and allows us to characterize optimal design points. We use these techniques to design superconducting quantum modules for entanglement distillation, error correction, and code teleportation, reducing error rates by 2.6×, 10.7×, and 3.4× compared to homogeneous systems.

Quantum Computing, Quantum Physics, Computer Archi↗
DOE OSTI2025

Discovery of unconventional and nonintuitive self-assembling peptide materials using experiment-driven machine learning

Prediction of peptide secondary structure is challenging because of complex molecular interactions, sequence-specific behavior, and environmental factors. Traditional design strategies, based on hydrophobicity and structural propensity, can be biased and could indeed prevent discovery of interesting, diverse, and unconventional peptides with desired nanostructure assembly. Using β sheet formation in pentapeptides as a case study, we used an integrated high-throughput experimental workflow and an artificial intelligence–driven active learning framework to improve prediction accuracy of self-assembly. By focusing on sequences where machine learning (ML) predictions deviate from conventional design strategies, we synthesized and tested 268 pentapeptides, successfully finding 96 forming β sheet assemblies, including unconventional sequences (e.g., ILFSM, LMISI, MITIY, MISIW, and WKIYI) not predicted by traditional methods. Our ML models outperformed conventional β sheet propensity tables, revealing useful chemical design rules. A web interface is provided to facilitate community access to these models. This work highlights the value of ML-driven approaches in overcoming the limitations of current peptide design strategies.

Talluri, Y. Nissi [Indian Inst. of Technology (IIT↗
DOE OSTI2023

Design and Scoping Tests on Alloy 617 Using Notched Specimen Geometry to Validate Methods for Multiaxial Stress Relaxation

In FY 2022, a development effort was initiated at the US Department of Energy’s Oak Ridge National Laboratory (ORNL) to examine the multiaxial stress-relaxation behavior and multiaxial stress-state effect on the creep-fatigue (CF) performance for Alloy 617 at elevated temperatures. This effort supported the development of the design rules in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), Section III, Division 5. In this work, two types of the notch specimen geometries were designed. An inelastic constitutive model was used to investigate the stress triaxiality and elastic follow-up effects on the notch specimens under CF deformation in the finite element (FE) simulations. The numerical study demonstrated that the stress triaxiality and elastic follow-up caused by the notches both play significant roles in the stress-relaxation behavior. In addition, Alloy 617 CF experiments were designed, and the testing on the notch specimens is ongoing. CF test failure data will be generated on the specimens with notches under various conditions in FY 2023, and the results will be used to validate methods for accounting for the multiaxial stress relaxation effect in the design code.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Controlling Interfacial Energetics and Charge Transfer Rates in 2D Semiconductors: Fundamental Studies en Route to Photoelectrochemical Energy Conversion Beyond the Shockley-Queisser Limit (Final Scientific/Technical Report)

Current photovoltaic and solar-to-fuel technologies do not fully utilize the energy of sunlight because excess photon energy above the semiconductor band gap is rapidly lost as heat through hot-carrier thermalization. Overcoming this loss mechanism is critical, as hot-carrier-based energy conversion systems are predicted to exceed the conventional efficiency limit of ~33%. This project advanced fundamental understanding of hot-carrier energy conversion in two-dimensional (2D) semiconductors, with a focus on monolayer MoS 2 . Using a combination of electrochemical microscopy and in situ ultrafast spectroscopic measurements, this research directly demonstrated hot-carrier extraction from monolayer MoS 2 photoelectrodes in proof-of-concept liquid junction solar cells. These measurements established that hot-carrier transfer can compete with ultrafast carrier cooling at solid–liquid interfaces, providing unambiguous experimental evidence that hot-carrier extraction is feasible in atomically thin semiconductors under operating photoelectrochemical conditions. Beyond demonstration, the project identified design rules for tuning hot-carrier extraction rates relative to cooling rates in 2D semiconductor photoelectrodes. The outcomes of this research provide foundational thermodynamic and kinetic insights for the rational design of next-generation hot-carrier-enabled solar energy conversion systems. These findings have broad implications for photoelectrochemical solar fuels production, electrocatalysis, and emerging energy conversion architectures that seek to harness nonequilibrium charge carriers for enhanced efficiency.

14 SOLAR ENERGY↗
DOE OSTI2026

A Unified Beam-Dynamics and Hardware Design Framework for Hybrid Nonlinear-Kicker Injection in NSLS-II

Nonlinear kickers (NLKs) enable off-axis injection in ultralow-emittance storage rings by providing a strong kick to the injected beam while remaining nearly transparent to the stored beam. In hybrid schemes, a conventional four-kicker bump defines the injected trajectory, and the NLK reduces the first-turn action under constrained beam offset and optics conditions. Effective operation additionally requires stable and reproducible first-turn injection trajectories. We develop a compact action–angle framework that expresses NLK dynamics in terms of Courant–Snyder invariants and yields an analytical bound on achievable action reduction. This formulation provides direct design rules for NLK placement, phase advance, injected-beam offset, and kicker field profile. Within this framework, we identify the 8-wire NLK as a practical baseline and extend its design by relaxing the square-geometry constraint, enabling inward shifting of the off-axis field peak while preserving on-axis field and gradient cancellation. Application to the NSLS-II lattice shows how aperture, pulsed-power, and mechanical constraints combine to determine a coupled design solution. Multi-turn tracking confirms that candidate NLK locations maintain sufficient stay-clear (aperture-clearance) margin, while the optimized wire geometry reduces the required current and Lorentz force load. The results establish a unified approach for NLK-assisted injection design and provide a practical pathway for upgrades in diffraction-limited storage rings.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Analytical Bit-Error Model of NAND Flash Memories for Dosimetry Application

In this work, we provide an analytical model for the total ionizing dose (TID) effects on the bit error statistics of commercial flash memory chips. We have validated the model with experimental data collected by irradiating several commercial NAND flash memory chips from different technology nodes. We find that our analytical model can project bit errors at higher TID values (~ 20 krad(Si)) from measured data at lower TID values (<1 krad(Si)). Based on our model and the measured data, we have formulated basic design rules for using a commercial flash memory chip as a dosimeter. We discuss the impact of NAND chip-to-chip variability, noise margin and the intrinsic errors on the dosimeter design using detailed experimentation.

3-D NAND↗
DOE OSTI2022

De novo protein design of photochemical reaction centers

Abstract Natural photosynthetic protein complexes capture sunlight to power the energetic catalysis that supports life on Earth. Yet these natural protein structures carry an evolutionary legacy of complexity and fragility that encumbers protein reengineering efforts and obfuscates the underlying design rules for light-driven charge separation. De novo development of a simplified photosynthetic reaction center protein can clarify practical engineering principles needed to build new enzymes for efficient solar-to-fuel energy conversion. Here, we report the rational design, X-ray crystal structure, and electron transfer activity of a multi-cofactor protein that incorporates essential elements of photosynthetic reaction centers. This highly stable, modular artificial protein framework can be reconstituted in vitro with interchangeable redox centers for nanometer-scale photochemical charge separation. Transient absorption spectroscopy demonstrates Photosystem II-like tyrosine and metal cluster oxidation, and we measure charge separation lifetimes exceeding 100 ms, ideal for light-activated catalysis. This de novo-designed reaction center builds upon engineering guidelines established for charge separation in earlier synthetic photochemical triads and modified natural proteins, and it shows how synthetic biology may lead to a new generation of genetically encoded, light-powered catalysts for solar fuel production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Toward the Prediction and Control of Glass Transition Temperature for Donor–Acceptor Polymers

Semiconducting donor–acceptor (D–A) polymers have attracted considerable attention toward the application of organic electronic and optoelectronic devices. However, a rational design rule for making semiconducting polymers with desired thermal and mechanical properties is currently lacking, which greatly limits the development of new polymers for advanced applications. Here, polydiketopyrrolopyrrole (PDPP)-based D–A polymers with varied alkyl side-chain lengths and backbone moieties are systematically designed, followed by investigating their thermal and thin film mechanical responses. The experimental results show a reduction in both elastic modulus and glass transition temperature (Tg) with increasing side-chain length, which is further verified through coarse-grained molecular dynamics simulations. Informed from experimental results, a mass-per-flexible bond model is developed to capture such observation through a linear correlation between Tg and polymer chain flexibility. Using this model, a wide range of backbone Tg over 80 °C and elastic modulus over 400 MPa can be predicted for PDPP-based polymers. This study highlights the important role of side-chain structure in influencing the thermomechanical performance of conjugated polymers, and provides an effective strategy to design and predict Tg and elastic modulus of future new D–A polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

De novo Materials Design of Catalytic Surface Motifs for Water-Gas-Shift (Final Progress Report DOE Grant DE-SC0019281)

This project was aimed at developing innovative theoretical methods and models to understand essential catalysis-relevant issues such as CO 2 conversion, fuel cells, and lithium batteries. Through collaborations with experimentalists, we strive to develop new quantum and machine learning methods for the understanding of surface and interfacial chemistry that can empower the design of energy and sustainability systems. Overall, our work under this grant brings cross-disciplinary insights into catalytic materials, microenvironments, and other conditions, which can serve to provide design rules for the next generation of catalysts.

25 ENERGY STORAGE↗
DOE OSTI2026

Understanding Depolymerization and Repolymerization Toward Repurposing Polymer Waste Into Valuable Chemicals & Materials

The versatility of synthetic polymers has led to their continual and escalating production that has accompanied mismanagement at their end-of-life. Exploring and understanding complementary avenues to repurpose plastic waste beyond traditional mechanical recycling can unlock new opportunities in providing feedstock flexibility, securing supply chains, recovering valuable materials, and enabling new valorization paths. Chemical recycling allows for the return to monomers, tailored oligomers, and polymers, even from mixed states of post-consumer waste plastics. This review article summarizes our research team's efforts on elucidating key insights surrounding plastic depolymerization and repolymerization into valorized products. We revealed organocatalyst design rules lead to highly effective and selective deconstruction of condensation polymers. The intricacies of tailoring the reaction environment to produce products of specific lengths and desired functionalities transform low-value waste feedstocks into high-performance materials with embedded circularity. Other types of polymers, including polyolefins and polyakenamers, have also been designed and converted into valuable products. There remain opportunities for further developments such as low-energy and precision depolymerization, adoption of cutting-edge small molecule transformation to access functionalized polymer scaffolds typically inaccessible otherwise, as well as precision design and understanding through the aid of advanced tools.

Galan, Nick [ORNL]↗
DOE OSTI2022

ClusterCAD 2.0: an updated computational platform for chimeric type I polyketide synthase and nonribosomal peptide synthetase design

Abstract Megasynthase enzymes such as type I modular polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs) play a central role in microbial chemical warfare because they can evolve rapidly by shuffling parts (catalytic domains) to produce novel chemicals. If we can understand the design rules to reshuffle these parts, PKSs and NRPSs will provide a systematic and modular way to synthesize millions of molecules including pharmaceuticals, biomaterials, and biofuels. However, PKS and NRPS engineering remains difficult due to a limited understanding of the determinants of PKS and NRPS fold and function. We developed ClusterCAD to streamline and simplify the process of designing and testing engineered PKS variants. Here, we present the highly improved ClusterCAD 2.0 release, available at https://clustercad.jbei.org. ClusterCAD 2.0 boasts support for PKS-NRPS hybrid and NRPS clusters in addition to PKS clusters; a vastly enlarged database of curated PKS, PKS-NRPS hybrid, and NRPS clusters; a diverse set of chemical ‘starters’ and loading modules; the new Domain Architecture Cluster Search Tool; and an offline Jupyter Notebook workspace, among other improvements. Together these features massively expand the chemical space that can be accessed by enzymes engineered with ClusterCAD.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Auto Procedure Parsing: A Natural Language Processing Approach

Nuclear Power Plant (NPP) operating procedure is “a set of rules that describes how actions on the plant should be made if a certain system goal should be accomplished. U.S. NPPs use paper-based procedures (PBPs). PBPs are difficult to use. Common errors with PBPs are: following the wrong procedure, omit a step etc. Computer based procedures (CPBs) offer great improvement in ensuring plant safety. Some studies rely on experienced operators to understand the procedure content and then reorganize the procedure with digitally executable capabilities. Other studies utilize the procedure format to design rules to extract information from the operating procedures. Existing studies in procedure parsing are manual, laborious and extract limited information. This study aims to automatically extract critical information from operating procedures for generating computer interpretable representation of procedures. Such representation can further be used for automatic dynamic human reliability analysis and CPB design etc.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗