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DOE OSTI2022

A de novo matrix for macroscopic living materials from bacteria

Engineered living materials (ELMs) embed living cells in a biopolymer matrix to create materials with tailored functions. While bottom-up assembly of macroscopic ELMs with a de novo matrix would offer the greatest control over material properties, we lack the ability to genetically encode a protein matrix that leads to collective self-organization. Here we report growth of ELMs from Caulobacter crescentus cells that display and secrete a self-interacting protein. This protein formed a de novo matrix and assembled cells into centimeter-scale ELMs. Discovery of design and assembly principles allowed us to tune the composition, mechanical properties, and catalytic function of these ELMs. This work provides genetic tools, design and assembly rules, and a platform for growing ELMs with control over both matrix and cellular structure and function.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Investigating Silver Nanoparticle Interactions with Quaternary Ammonium Functionalized Triblock Copolymers and Their Effect on Midblock Crystallinity

Interactions between silver nanoparticles and a cationic triblock copolymer significantly alter bulk material properties and can be tuned by functionalizing the polymer with different quaternary ammonium cations (QACs). In this work, poly-chloromethylstyrene-b-polycyclooctene-b-polychloromethylstyrene (PCMS-b-PCOE-b-PCMS) was quaternized with either methylpiperidinium (MPRD) or trimethylammonium (TMA). The surface interacting groups were identified using FT-IR to be the phenyl rings, the QACs from the outer blocks, and vinyl groups from the PCOE midblock. Changes in thermal characteristics and crystallinity were highly dependent on the QAC, uncovering differences in the nature of the interactions between silver and TMA or MPRD. Interactions induced by TMA greatly hinder crystalline domain formation and give rise to a higher water content, while MPRD promotes certain crystalline orientations and provides a greater degree of crystallinity with a lower water content. In this work, our findings demonstrate that bulk polymer characteristics can be tuned, a highly desirable attribute for many nanocomposite materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Tuning the Lifetimes of Photoinduced Deligation in a Metal–Organic Framework via Linker Functionalization

Recently photoinduced dynamic ligation in a metal–organic frameworks (MOFs) was reported, where a long-lived charge-transfer excited state (ca. 30 μs) featuring partial dissociation between the carboxylate linker and metal-based node was probed by time-resolved infrared (TRIR) spectroscopy. The study offers a new mechanistic perspective to evaluate the potential contribution from the excited state molecular configuration to the performance of MOF photocatalysts. In this work, by employing MIL-101(Fe) as the study platform, we have further explored the influence of intramolecular interactions on the stability of relevant excited states and demonstrated the effective tuning of their lifetimes through the incorporation of different functional groups into the system. The correlations between the varied excited state lifetimes and coordination configurations with specific functional groups (−NH 2 or −NO 2 ) was inferred from the analyses of infrared spectroscopic data and theoretical calculations, revealing the essential role of the intramolecular interactions (i.e., between the added functional groups and the carboxylate group) in the modulation of system energetics. Overall, the work presents a pathway to tune the excited state dynamics and expands the knowledge regarding the photoinduced dynamic ligation in carboxylate-based MOFs.

excited states↗

NASA NTRS1993

Nonlinear rescaling of control values simplifies fuzzy control

Traditional control theory is well-developed mainly for linear control situations. In non-linear cases there is no general method of generating a good control, so we have to rely on the ability of the experts (operators) to control them. If we want to automate their control, we must acquire their knowledge and translate it into a precise control strategy. The experts' knowledge is usually represented in non-numeric terms, namely, in terms of uncertain statements of the type 'if the obstacle is straight ahead, the distance to it is small, and the velocity of the car is medium, press the brakes hard'. Fuzzy control is a methodology that translates such statements into precise formulas for control. The necessary first step of this strategy consists of assigning membership functions to all the terms that the expert uses in his rules (in our sample phrase these words are 'small', 'medium', and 'hard'). The appropriate choice of a membership function can drastically improve the quality of a fuzzy control. In the simplest cases, we can take the functions whose domains have equally spaced endpoints. Because of that, many software packages for fuzzy control are based on this choice of membership functions. This choice is not very efficient in more complicated cases. Therefore, methods have been developed that use neural networks or generic algorithms to 'tune' membership functions. But this tuning takes lots of time (for example, several thousands iterations are typical for neural networks). In some cases there are evident physical reasons why equally space domains do not work: e.g., if the control variable u is always positive (i.e., if we control temperature in a reactor), then negative values (that are generated by equal spacing) simply make no sense. In this case it sounds reasonable to choose another scale u' = f(u) to represent u, so that equal spacing will work fine for u'. In the present paper we formulate the problem of finding the best rescaling function, solve this problem, and show (on a real-life example) that after an optimal rescaling, the un-tuned fuzzy control can be as good as the best state-of-art traditional non-linear controls.

Vanlangingham, H.↗

DOE OSTI2022

Universal machine learning framework for defect predictions in zinc blende semiconductors

Our article introduces a universal predictive framework for point defect formation energies and charge transition levels in a wide chemical space of zinc blende semiconductors and possible impurity atoms selected from across the periodic table. This framework was developed by leveraging high-throughput quantum mechanical simulations benchmarked using some experimental data from the literature, as well as machine learning (ML)-based regressions techniques that map unique materials descriptors to computed defect properties and yield optimized and generalizable models. Furthermore, the power and utility of these models is revealed through quick predictions for thousands of new defects and screening of low-energy impurities, which may tune the equilibrium conductivity in the semiconductor. This work presents, to our knowledge, the largest density functional theory (DFT) dataset of defect properties in semiconductors and the largest DFT+ML-based screening of point defects in semiconductors to date.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Aqueous-soluble bipyridine cobalt($\tiny{II}$/$\tiny{III}$) complexes act as direct redox mediators in photosystem I-based biophotovoltaic devices

Sustainable energy production is critical for meeting growing worldwide energy demands. Due to its stability and reduction potential, photosystem I (PSI) is attractive as the photosensitizer in biophotovoltaic devices. Herein, we characterize aqueous and organic solvent soluble synthetic bipyridine-based cobalt complexes as redox mediators for PSI-based biophotovoltaics applications. Cobalt-based complexes are not destructive to protein and have appropriate midpoint potentials for electron donation to PSI. We report on PSI stability in organic solvents commonly used in biophotovoltaics. We also show the effects of a mixed organic solvent phase on PSI reduction kinetics, slowing reduction rates approximately 8–38 fold as compared to fully aqueous systems, with implications for dye regeneration rates in PSI-based biophotovoltaics. Further, we show evidence of direct electron transfer from cobalt complexes to PSI. Finally, we report on photocurrent generation from Co mediator-PSI biophotovoltaic devices. Taken together, we discuss the development of novel Co complexes and our ability to fine-tune their characteristics via functional groups and counteranion choice to drive interaction with a biological electron acceptor on multiple levels from redox midpoints, spectral overlap, and solvent requirements, among others. This work suggests that fine-tuning of redox active species for interaction with a biological partner is possible for the creation and improvement of low cost, carbon-neutral energy production in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Unexpected crystalline homogeneity from the disordered bond network in La(Cr 0.2 Mn 0.2 Fe 0.2 Co 0.2 Ni 0.2 )O 3 films

Designing and understanding functional electronic and magnetic properties in perovskite oxides requires controlling and tuning the underlying crystal lattice. In this work, we report the structure, including oxygen and cation positions, of a single-crystal, entropy stabilized perovskite oxide film of La(Cr 0.2 Mn 0.2 Fe 0.2 Co 0.2 Ni 0.2 )O 3 grown on SrTiO3 (001). The parent materials range from orthorhombic (LaCrO 3 , LaMnO 3 , and LaFeO 3 ) to rhombohedral (LaCoO 3 and LaNiO 3 ), and first principles calculations indicate that these structural motifs are nearly degenerate in energy and should be highly distorted site to site. Despite this extraordinary local configurational disorder on the B-site sublattice, we find a structure with unexpected macroscopic crystalline homogeneity with a clear orthorhombic unit cell, whose orientation is demonstrated to be controlled by the strain and crystal structure of the substrate for films grown on (La 0.3 Sr 0.7 )(Al 0.65 Ta 0.35 )O 3 and NdGaO 3 (110). Furthermore, quantification of the atom positions within the unit cell reveals that the orthorhombic distortions are small, close to LaCrO 3, which may be driven by a combination of disorder averaging and the average ionic radii. This is a step toward understanding the rules for designing crystal motifs and tuning functional properties through controlled configurational complexity.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Reticular Structural Diversification of Zirconium Metal–Organic Frameworks Through Angular Ligand Configuration Control

Reticular chemistry offers practical guidelines for enlarging and enriching the arsenal of metal–organic frameworks (MOFs). However, reticular expansion to access mesoporous structures remains challenging due to limitations in achieving precise control over both the size and configuration during building units’ extension. Herein, we combine ligand isomerization and functionalization strategies to regulate the ligand configuration by systematically replacing aryl C–H groups with N atoms, resulting in angular dicarboxylate ligands with various symmetries. The assembly between a 4,4′-(pyridine-2,6-diyl)dibenzoic acid ligand (1N, C 2 symmetry) and 12-connected Zr 6 cluster leads to the formation of a pseudo ftw topology framework (NU-2611), where one pair of nose-to-nose 1N ligands resembles a tetra-topic ligand. When a 6,6′-(1,3-phenylene)dinicotinic acid ligand (2N, C S symmetry) was used, another pseudo ftw network NU-2612 was obtained with a 2-fold framework interpenetration. Interestingly, the planar [2,2′:6′,2″-terpyridine]-5,5″-dicarboxylic acid ligand (3N, C 2V symmetry) yielded an intriguing mesoporous Zr-MOF with kag topology. NU-2613 represents the first example of kag Zr-MOF designed to include large, well-defined mesopores. The diversity of these MOFs was further enhanced through post-synthetic metalation of linkers. Particularly, metalation of the chelating 3N ligand with Fe 3+ in NU-2613 enables efficient catalytic transformation within the functionalized channels. This work contributes insight into the reticular expansion of Zr-MOFs by finely-tuning the ligand planarity, advancing the structure diversification of mesoporous frameworks for specific applications.

Cluster chemistry↗

DOE OSTI2022

Tracking carrier and exciton dynamics in mixed-cation lead mixed-halide perovskite thin films

Mixed-cation lead mixed-halide perovskites simultaneously possess structural stability and high power conversion efficiency. A thorough study of both carrier and exciton dynamics is needed to understand the photophysical properties that underpin its superior photovoltaic performance. By utilizing a broadband transient absorption spectroscopy, we observe the carrier and exciton dynamics in a FA 0.85 Cs 0.15 Pb(I 0.97 Br 0.03 ) 3 (FCPIB) perovskite by simultaneously resolving the carrier and exciton contribution to the transient change of the absorption spectra, from which the carrier density and exciton oscillator strength can be determined. Our data reveal a quick and significant conversion of the photogenerated carriers to excitons, on top of the usual carrier recombination process. Moreover, the decay of carrier density shows a change of kinetics from a second-order recombination at high pump fluence to a third-order recombination at low pump fluence. Our analysis utilizes band anharmonicity, presents an independent determination of electronic temperature and quasi-Fermi energy, and reveals an interesting interplay among the processes of carrier cooling, exciton formation/decay and carrier recombination, all as a function of time after photoexcitation. Our work demonstrates the use of pump fluence as a knob to tune the relative populations of carriers and excitons in halide perovskite materials.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

A Generalized, Compactly-Supported Correlation Function for Data Assimilation Applications

Correlation functions play an essential role in modern data assimilation, where they are used to model covariances given a set of tunable parameters or applied as tapering functions to localize covariances in ensemble-based schemes. One of the most widely-used correlation functions in data assimilation is the Gaspari and Cohn (1999) piecewise-rational, compactly-supported parametric correlation function (hereafter referred to as GC99). The GC99 correlation function is useful due to its tunable cut-off parameter c and Gaussian-like shape achieved when the parameter a is set to one-half. These properties are attractive for tapering functions in data assimilation applications. However, the GC99 correlation function is homogeneous over Euclidean 3-space and isotropic when restricted to the sphere, properties that may be less than ideal for some geophysical applications. GC99 is also compactly-supported on a sphere of fixed radius, which requires tuning of the cut-off parameter c that can depend on the specific application. This work presents a generalization of the GC99 correlation function that allows the cut-off parameter c and shape parameter a to vary over space to gain more flexibility in shape while maintaining its compact support property. The function, which we call the Generalized Gaspari Cohn (GenGC) correlation function, introduces inhomogeneity in Euclidean 3-space and anisotropy when restricted to the sphere by allowing both parameters c and a to vary, as functions, over the spatial domain. The GC99 correlation function is a special case of GenGC where the functions c and a are held constant, as fixed parameters rather than functions. The GenGC correlation function also generalizes the follow-on to the work of Gaspari and Cohn (1999) presented in Gaspari et al. (2006), which allowed a to vary while keeping c fixed. We illustrate through simple one- and two-dimensional examples the variety of inhomogeneous and anisotropic correlation functions GenGC can produce by varying c and a over space, and suggest applications where they may be useful in data assimilation, such as covariance modeling or localization. In particular, we describe how the GenGC correlation function can be used to construct covariances using correlation length and variance fields derived from dynamics. For example, the correlation length field for advective dynamics is governed by a partial differential equation (PDE) in N spatial dimensions, where N is the number of space dimensions of the state. Correlation length fields can be determined from this PDE and used with GenGC to construct the corresponding correlations. We can then approximate the full covariance by rescaling by the variance, which also satisfies a PDE in N spatial dimensions for advective dynamics. Thus we can approximate the full covariance without solving the covariance PDE, which is in 2N spatial dimensions, by solving just two PDEs each in only N spatial dimensions. This approach to evolving the correlation length and variance fields, then reconstructing the correlations using GenGC, is suggested as an alternative to current methods of covariance modeling in data assimilation algorithms.

GC99↗

DOE OSTI2023

Transient Stability Preventive Control via Tuning the Parameters of Virtual Synchronous Generators

This paper presents an optimal preventive control (OPC) method to improve the power system transient stability via tuning the transient parameter of virtual synchronous generators. The novelty of this work is that we formulate the preventive control as an optimization problem so that inverter parameters can be adjusted at the pre-contingency stage. A reinforcement learning (RL)-driven method is proposed to solve the OPC problem with the fault energy-based reward function. An ANDES-based RL environment is also developed. Versatile functions included in the proposed environment have been presented in this paper. The proposed OPC formulation, the RLdriven method, and the fault energy-based reward function are verified on several standard test systems.

Inverter-based resources, virtual synchronous gene↗

DOE OSTI2021

Cation-size mismatch as a predictive descriptor for structural distortion, configurational disorder, and valence-band splitting in II-IV-N2 semiconductors

The II-IV-N2 class of heterovalent ternary nitrides has gained significant interest as alternatives to the III-nitrides for electronic and optoelectronic applications. In this study, we apply first-principles calculations based on density functional theory to systematically investigate the effects of structural distortions due to cation size mismatch on the configurational disorder of the cation sublattice and the valence band structure in this class of materials. We find that larger size mismatch between the group-II and the group-IV cations results in stronger lattice distortions from the ideal hexagonal ratio, which in turn inhibits the propensity of these materials toward octet-rule violating cation disorder. We also demonstrate that the formation energy of a single cation antisite pair, which is fast and simple to calculate, is a strong indicator of a material's propensity toward disorder. Furthermore, the breaking of in-plane symmetry leads to a splitting of the top three valence bands at Γ, which is also directly related to the magnitude of structural distortions. Our work demonstrates that the structural and functional properties of the II-IV-N2 materials can be finely tuned through controllable structural distortions that stem from the choice of cations.

Kute, Malhar (ORCID:0000000214364564)↗

DOE OSTI2020

Over 15% Efficiency Polymer Solar Cells Enabled by Conformation Tuning of Newly Designed Asymmetric Small‐Molecule Acceptors

Abstract The prosperous period of polymer solar cells (PSCs) has witnessed great progress in molecule design methods to promote power conversion efficiency (PCE). Designing asymmetric structures has been proved effective in tuning energy level and morphology, which has drawn strong attention from the PSC community. Two hepta‐ring and octa‐ring asymmetric small molecular acceptors (SMAs) (IDTP‐4F and IDTTP‐4F) with S‐shape and C‐shape confirmations are developed to study the relationship between conformation shapes and PSC efficiencies. The similarity of absorption and energy levels between two SMAs makes the conformation a single variable. Additionally, three wide‐bandgap polymer donors (PM6, S1, and PM7) are chosen to prove the universality of the relationship between conformation and photovoltaic performance. Consequently, the champion PCE afforded by PM7: IDTP‐4F is as high as 15.2% while that of PM7: IDTTP‐4F is 13.8%. Moreover, the S‐shape IDTP‐4F performs obviously better than their IDTTP‐4F counterparts in PSCs regardless of the polymer donors, which confirms that S‐shape conformation performs better than the C‐shape one. This work provides an insight into how conformations of asymmetric SMAs affect PCEs, specific functions of utilizing different polymer donors to finely tune the active‐layer morphology and another possibility to reach an excellent PCE over 15%.

Guo, Qing↗

DOE OSTI2022

Titrating Controlled Defects into Si-LTA Zeolite Crystals Using Multiple Organic Structure-Directing Agents

Controlling defects in zeolites is crucial for tuning their adsorption and catalytic properties. In this work, we have performed an integrated zeolite synthesis, spectroscopy, and density functional theory study to test the limit of F– as a charge-balancing agent that mitigates defects in siliceous zeolites. We focused on the synthesis of siliceous zeolite LTA at 150 °C with 1,2-dimethyl-3-(4-methylbenzyl) imidazolium as the primary organic structure-directing agent (OSDA) and tetramethyl ammonium (TMA) as the secondary OSDA. By varying the amount of TMA in the synthesis gel, positive charges were titrated into the resulting as-made Si-LTA. Surprisingly, we found that greater TMA concentration does not induce more F– to enter into the zeolite. 29Si solid-state MAS NMR, Raman spectroscopy, and density functional theory suggest that this system has surpassed its capacity for F– to balance OSDA charge, and additional positive charge is balanced by Si–O– framework defects. The number of defects in the as-made Si-LTA can be precisely titrated by the amount of TMA in the zeolite structures. For the Si-LTA synthesized without TMA, framework defects formed in the early stage of crystal growth were found to heal during later crystallization, leading to defect-free Si-LTA. However, for the Si-LTA synthesized with TMA, the defects formed in early stages do not heal. A DFT thermodynamic analysis explains that crowding of Si-LTA pores by TMA impedes defect healing; this prediction is corroborated by synthesis experiments at an elevated temperature (170 °C). These results indicate that F– can have a limited capacity to balance OSDA charge in zeolite synthesis, opening up a third route to zeolite synthesis intermediate between the fluoride and hydroxide routes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2024

Optimized bandpasses for the Habitable Worlds Observatory's exoEarth survey

A primary scientific goal of the future Habitable Worlds Observatory will be the direct detection and characterization of Earth-like planets. Estimates of the exoplanet yields for this concept will help guide mission design through detailed trade studies. It is therefore critical that yield estimation codes optimally adapt observations to the mission’s performance parameters to ensure accurate trade studies. To aid in this, we implement wavelength optimization in yield calculations for the first time, allowing the yield code to determine the ideal detection and characterization bandpasses. We use this capability to confirm the observational wavelength assumptions made for the large UV/Optical/IR surveyor, design B (LUVOIR-B) study, namely that the optimum detection wavelength is 500 nm for the majority of targets and the optimum wavelength to detect water is near 1000 nm, given LUVOIR-B’s assumed instrument performance parameters. We show that including the wavelength-dependent albedo of an Earth twin as a prior provides no significant benefit to the yields of exoEarth candidates and caution against tuning observations to modern Earth twins. We also show that coronagraphs whose inner working angles are similar to step functions may benefit from wavelength optimization and demonstrate how wavelength-dependent instrument performance can impact the optimum wavelengths for detection and characterization. The optimization methods we implement automate wavelength selection and remove uncertainties regarding these choices, helping to adapt the observations to the instrument’s performance parameters.

telescopes↗

DOE OSTI2025

Metastable Clusters and Competitive Solvation Tune Ion Pairing at Liquid Interfaces

The balance of hydrophobic and hydrophilic interactions underlies emergent phenomena in complex multicomponent chemical systems. Here, we show that a supposedly ‘non–interacting’ nonpolar phase can be used to competitively solvate amphiphilic molecules at an oil/aqueous interface. This solvation, as probed by surface specific nonlinear spectroscopy and simulations, results in a molecularly thin corrugated phase boundary featuring metastable assemblies that alter the hydrogen bonding networks of water and the apparent ‘hard/soft’ descriptors used to describe ionic interactions. We show that competitive solvation enhances amphiphile mobility, opening up otherwise energetically inaccessible complexes that transiently interact with aqueous phase ions. These transient species impact ensemble binding affinities and may represent the molecular agents responsible for aspects of ionic transport and function. In conclusion, the result of this work highlights how seemingly unrelated nonpolar interactions feedback onto aqueous phase chemical phenomena, providing a pathway to tune phase separation and self-assembly to access new reaction pathways using interfaces for a range of chemical and biological systems.

Anions↗

DOE OSTI2025

Alkali-induced catalytic tuning at metal and metal oxide interfaces

Alkali metals have been recognized as effective promoters in heterogeneous catalysis, capable of enhancing catalytic activity and tuning product distributions. Over the past few decades, significant efforts have been made aiming to reveal the mechanisms underlying the promoting effect of alkalis. However, the roles that alkali metals play in the catalytic process remain elusive due to challenges in capturing their catalytic behaviours upon exposure to reactive environments. This review summarizes recent surface science and theoretical studies of alkali (potassium, cesium)-decorated metal and metal oxide model catalysts, revealing the crucial tuning by alkalis of activity and selectivity for CO 2 hydrogenation. The analysis of electronic structures identifies the selective binding mechanism of the positively charged alkali ions on the surface, being able to reduce the surface work function and lead to strong electron polarization on the surfaces. Depending on the alkali–support interaction, the deposition of alkalis can selectively modify the bindings of reaction intermediates involved in CO 2 hydrogenation via the interplay among the ionic, covalent and electrostatic tunings. As a result, CO 2 can be effectively activated and converted into diverse products at the alkali–support interface, ranging from formic acid to methanol and ethanol. The identified selective bond-tuning advances the application of alkalis in promoting catalytic activity and controlling catalytic selectivity at alkali–support interfaces.

03 NATURAL GAS↗

DOE OSTI2025

Geo-Responsive Chemomechanics in Aluminum Oxyhydroxide via Alkali-Driven Dehydroxylation for Supercritical Geothermal Systems

Widespread use of enhanced geothermal systems can revolutionize global renewable electrical power access, yet its advancement is hindered by the inherent instability of Portland cement-based chemistries for geothermal well construction under high-temperature corrosive conditions. Here, in this work, we demonstrate the tunable mechanical performance of aluminum oxyhydroxides as cementitious materials through an alkali-controlled dehydroxylation reaction pathway for long-term applications under supercritical geothermal environments. Notably, the synthesized aluminum oxyhydroxides demonstrate remarkable stability, maintaining superior mechanical performance under supercritical conditions for over 30 days. Synchrotron X-ray diffraction, spectroscopy measurements and geochemical thermodynamic modeling uncover that the gibbsite dehydroxylation pathway functions as a key dial for tuning the chemomechanics, rendering the aluminum oxyhydroxide a strong cementitious material. By uncovering the mechanistic role of alkali-driven dehydroxylation, this work proposes a cementitious chemistry distinct from conventional Portland cement and geopolymer-dominated alkali-activated systems, laying the groundwork for developing next-generation cementitious materials for supercritical geothermal energy exploitation.

15 GEOTHERMAL ENERGY↗