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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 OSTI2021

Steric Effect Tuned Ion Solvation Enabling Stable Cycling of High-Voltage Lithium Metal Battery

1,2-Dimethoxyethane (DME) is a common electrolyte solvent for lithium metal batteries. Various DME-based electrolyte designs have improved long-term cyclability of high-voltage full cells. However, insufficient Coulombic efficiency at the Li anode and poor high-voltage stability remain a challenge for DME electrolytes. Here, we report a molecular design principle that utilizes a steric hindrance effect to tune the solvation structures of Li + ions. In this work, we hypothesized that by substituting the methoxy groups on DME with larger-sized ethoxy groups, the resulting 1,2-diethoxyethane (DEE) should have a weaker solvation ability and consequently more anion-rich inner solvation shells, both of which enhance interfacial stability at the cathode and anode. Experimental and computational evidence indicates such steric-effect-based design leads to an appreciable improvement in electrochemical stability of lithium bis(fluorosulfonyl)imide (LiFSI)/DEE electrolytes. Under stringent full-cell conditions of 4.8 mAh cm –2 NMC811, 50 μm thin Li, and high cutoff voltage at 4.4 V, 4 M LiFSI/DEE enabled 182 cycles until 80% capacity retention while 4 M LiFSI/DME only achieved 94 cycles. This work points out a promising path toward the molecular design of non-fluorinated ether-based electrolyte solvents for practical high-voltage Li metal batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Data-Driven Discovery of Linear Molecular Probes with Optimal Selective Affinity for PFAS in Water

Approaches to tackle the wide and growing variety of highly persistent per- and polyfluoroalkyl substances (PFAS) are of pressing global need because of their detrimental human health effects, such as cancer, birth defects, and hormone imbalance. Sensitive, selective, and easy-to-use real-time sensors to monitor and detect PFAS and sorbents to extract them are critical to meeting government-mandated environmental concentrations. In this work, we combine all-atom molecular dynamics simulations, enhanced sampling, deep representational learning, and Bayesian optimization to perform high-throughput virtual screening for highly sensitive and selective molecular probes. Our molecular design space consists of 3850 linear hydrocarbon chains with varying degrees of halogenation with and without amine- and phosphine-based headgroups. By employing a data-driven search process, we efficiently explore the molecular design space to optimize the sensitivity to perfluorooctanesulfonic acid (PFOS) as a prototypical PFAS analyte and selectivity relative to a sodium dodecyl sulfate (SDS) interferent. We calculate 504 Gibbs free energies of probe-analyte and probe-interferent interactions and identify probes with PFOS association free energies of up to (-ΔG PFOS ) = 9.8 ± 0.2 kJ/mol and selectivities relative to SDS of (-ΔΔG PFOS–SDS ) = 3.1 ± 1.5 kJ/mol. A C 11 Br 23 P(CH 3 ) 2 probe containing 11 backbone brominated carbons and a tertiary phosphine headgroup possesses the most sensitive binding constant to PFOS within the defined search space of K b PFOS = 177.4 ± 12.7, and a semibrominated probe C 5 H 11 C 7 Br 14 N(CH 3 ) 2 containing 12 backbone carbons and a tertiary amine headgroup possesses the highest selectivity relative to SDS of K b PFOS /K b SDS = 4.6 ± 1.7. A retrospective analysis of our data to extract interpretable design rules reveals that the sensitivity of linear hydrogenated probes increases by approximately 1 kJ/mol per C–C bond. The addition or removal of halogen atoms and amine or phosphine headgroups produces nonmonotonic changes in both sensitivity and selectivity with changes to the sensitivity of up to 2.5 kJ/mol. Finally, this work places empirical limitations on the performance of a wide range of linear probes for PFOS detection and offers a generic strategy for high-throughput computational screening to promote selective and sensitive binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Side-chain ionization enables ultrafast intramolecular singlet fission in the azaquinodimethane skeleton

Singlet fission (SF) could significantly alleviate thermalization losses of high-energy photons, thus holding great potential for improving the power conversion efficiency of solar cells. Conventional SF materials require an intricate control of molecular packing motifs in the solid state to achieve efficient multiexciton generation. Small molecule intramolecular singlet fission (iSF) materials have emerged as promising alternatives and show great potential for practical device applications. However, the scope of such iSF materials remains rather limited, necessitating innovative molecular design strategies. Herein, we present how a side-chain ionization strategy leads to an iSF chromophore based on the azaquinodimethane (AQM) ring system. Systematic theoretical and spectroscopic analyses reveal that the direct attachment of electron-withdrawing ionic groups to the conjugated AQM core renders the originally fluorescent AQM nonemissive, leading to ionic AQM (iAQM) derivatives capable of ultrafast iSF to populate triplet-like species. Further fine-tuning of the iAQM skeleton imparts subtle intermolecular interactions that are indispensable for the efficient separation of triplet pairs following iSF in the aggregated state. Our findings offer unprecedented insights into molecular design and triplet exciton dynamics, laying the foundation for the discovery of rare molecular iSF materials.

Wu, Zixiang↗
DOE OSTI2022

Data-driven design of molecular nanomagnets

Three decades of research in molecular nanomagnets have raised their magnetic memories from liquid helium to liquid nitrogen temperature thanks to a wise choice of the magnetic ion and coordination environment. Still, serendipity and chemical intuition played a main role. In order to establish a powerful framework for statistically driven chemical design, here we collected chemical and physical data for lanthanide-based nanomagnets, catalogued over 1400 published experiments, developed an interactive dashboard (SIMDAVIS) to visualise the dataset, and applied inferential statistical analysis. Our analysis shows that the Arrhenius energy barrier correlates unexpectedly well with the magnetic memory. Furthermore, as both Orbach and Raman processes can be affected by vibronic coupling, chemical design of the coordination scheme may be used to reduce the relaxation rates. Indeed, only bis-phthalocyaninato sandwiches and metallocenes, with rigid ligands, consistently present magnetic memory up to high temperature. Analysing magnetostructural correlations, we offer promising strategies for improvement, in particular for the preparation of pentagonal bipyramids, where even softer complexes are protected against molecular vibrations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Synthetic Nuances to Maximize n-Type Organic Electrochemical Transistor and Thermoelectric Performance in Fused Lactam Polymers

A series of fully fused n-type mixed conduction lactam polymers p(g 7 NC n N), systematically increasing the alkyl side chain content, are synthesized via an inexpensive, nontoxic, precious-metal-free aldol polycondensation. Employing these polymers as channel materials in organic electrochemical transistors (OECTs) affords state-of-the-art n-type performance with p(g 7 NC 10 N) recording an OECT electron mobility of 1.20 x 10 -2 cm 2 V -1 s -1 and a μC* figure of merit of 1.83 F cm -1 V -1 s -1. In parallel to high OECT performance, upon solution doping with (4-(1,3-dimethyl-2,3-dihydro-1H-benzoimidazol-2-yl)phenyl)dimethylamine (N-DMBI), the highest thermoelectric performance is observed for p(g 7 NC 4 N), with a maximum electrical conductivity of 7.67 S cm -1 and a power factor of 10.4 μWm -1 K -2 . These results are among the highest reported for n-type polymers. Importantly, while this series of fused polylactam organic mixed ionic-electronic conductors (OMIECs) highlights that synthetic molecular design strategies to bolster OECT performance can be translated to also achieve high organic thermoelectric (OTE) performance, a nuanced synthetic approach must be used to optimize performance. Herein, we outline the performance metrics and provide new insights into the molecular design guidelines for the next generation of high-performance n-type materials for mixed conduction applications, presenting for the first time the results of a single polymer series within both OECT and OTE applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

SAN-Based Block Polymers as a Platform for Manufacturing Strong Isoporous Membranes

Ultrafiltration (UF) membranes are ubiquitous in water purification and bioprocessing. However, co-designing their mechanical and transport properties remains challenging because of the broad pore size distributions at the surface and within the bulk that result from nonsolvent-induced phase separation (NIPS) – their typical manufacturing process. These distributions influence the hydrodynamic resistance to water flow and the stress concentrations around the pores. Developing advanced UF membranes requires innovative molecular designs that offer control over the surface and bulk pores, as well as the mechanical properties of the load-bearing, polymer. Here, we introduce a platform for designing UF membranes by leveraging solution self-assembly of block polymers and chain architectures with pendant polar groups. The block polymers consist of a poly(styrene-co-acrylonitrile) hydrophobic block, which is known for its strength, and a poly(4-vinyl pyridine) hydrophilic block, which drives solution self-assembly. We focus on a series of block polymers with constant molecular weight, M n ≈ 115 kDa, SAN fraction, 75 wt.%, and varying acrylonitrile content, 0 to 40 mol%, to demonstrate that: (i) RAFT dispersion copolymerization of acrylonitrile and styrene provides a facile route to synthesize strong block polymers, (ii) incorporation of acrylonitrile into the hydrophobic block enhances membrane strength by facilitating chain entanglements and dipole-dipole interactions, and (iii) acrylonitrile alters the balance between membrane permeance and rejection, even when the membranes feature similar surface and bulk pores. Overall, our results provide insights into the molecular design of UF membranes with enhanced mechanical and separation properties, contributing to the development of materials for water and energy technologies.

deformation↗
DOE OSTI2022

Functionalizing aromatic compounds with optical cycling centres

Molecular design principles provide guidelines for augmenting a molecule with a smaller group of atoms to realize a desired property or function. Here, we demonstrate that these concepts can be used to create an optical cycling centre, the Ca(I)–O unit, that can be attached to a number of aromatic ligands, enabling the scattering of many photons from the resulting molecules without changing the molecular vibrational state. Such capability plays a central role in quantum state preparation and measurement, as well as laser cooling and trapping, and is therefore a prerequisite for many quantum science and technology applications. We provide further molecular design principles that indicate the ability to optimize and expand this work to an even broader class of molecules. This represents a great step towards a quantum functional group, which may serve as a generic qubit moiety that can be attached to a wide range of molecular structures and surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Molecular-level design of alternative media for energy-saving pilot-scale fibrillation of nanocellulose

The outstanding mechanical properties, light weight, and biodegradability of cellulose nanofibrils (CNFs) make them promising components of renewable and sustainable next-generation reinforced composite biomaterials and bioplastics. Manufacturing CNFs at a pilot scale requires disc-refining fibrillation of dilute cellulose fibers in aqueous pulp suspensions to shear the fibers apart into their nanodimensional forms, which is, however, an energy-intensive process. Here, in this study, we used atomistic molecular dynamics (MD) simulation to examine media that might facilitate the reduction of interactions between cellulose fibers, thereby reducing energy consumption in fibrillation. The most suitable medium found by the simulations was an aqueous solution with 0.007:0.012 wt.% NaOH:urea, and indeed this was found in pilot-scale experiments to reduce the fibrillation energy by ~21% on average relative to water alone. The NaOH:urea-mediated CNFs have similar crystallinity, morphology, and mechanical strength to those formed in water. The NaOH and urea act synergistically on CNFs to aid fibrillation but at different length scales. NaOH deprotonates hydroxyl groups leading to mesoscale electrostatic repulsion between fibrils, whereas urea forms hydrogen bonds with protonated hydroxyl groups thus disrupting interfibril hydrogen bonds. This suggests a general mechanism in which an aqueous medium that contains a strong base and a small organic molecule acting as a hydrogen-bond acceptor and/or donor may be effectively employed in materials processes where dispersion of deprotonable polymers is required. The study demonstrates how atomic-detail computer simulation can be integrated with pilot-scale experiments in the rational design of materials processes for the circular bioeconomy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Intrinsic glassy-metallic transport in an amorphous coordination polymer

Conducting organic materials, such as doped organic polymers, molecular conductors and emerging coordination polymers4, underpin technologies ranging from displays to flexible electronics. Realizing high electrical conductivity in traditionally insulating organic materials necessitates tuning their electronic structure through chemical doping6. Furthermore, even organic materials that are intrinsically conductive, such as single-component molecular conductors, require crystallinity for metallic behavior. However, conducting polymers are often amorphous to aid durability and processability. Using molecular design to produce high conductivity in undoped amorphous materials would enable tunable and robust conductivity in many applications, but there are no intrinsically conducting organic materials that maintain high conductivity when disordered. Here we report an amorphous coordination polymer, Ni tetrathiafulvalene tetrathiolate, which displays markedly high electronic conductivity (up to 1,200 S cm –1 ) and intrinsic glassy-metallic behavior. Theory shows that these properties are enabled by molecular overlap that is robust to structural perturbations. This unusual set of features results in high conductivity that is stable to humid air for weeks, pH 0–14 and temperatures up to 140 °C. Furthermore, these findings demonstrate that molecular design can enable metallic conductivity even in heavily disordered materials, raising fundamental questions about how metallic transport can exist without periodic structure and indicating exciting new applications for these materials.

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

Determining best practices for using genetic algorithms in molecular discovery

Genetic algorithms (GAs) are a powerful tool to search large chemical spaces for inverse molecular design. However, GAs have multiple hyperparameters that have not been thoroughly investigated for chemical space searches. In this tutorial, we examine the general effects of a number of hyperparameters, such as population size, elitism rate, selection method, mutation rate, and convergence criteria, on key GA performance metrics. Here, we show that using a self-termination method with a minimum Spearman’s rank correlation coefficient of 0.8 between generations maintained for 50 consecutive generations along with a population size of 32, a 50% elitism rate, three-way tournament selection, and a 40% mutation rate provides the best balance of finding the overall champion, maintaining good coverage of elite targets, and improving relative speedup for general use in molecular design GAs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bayesian optimization for chemical products and functional materials

The design of chemical-based products and functional materials is vital to modern technologies, yet remains expensive and slow. Artificial intelligence and machine learning offer new approaches to leverage data to overcome these challenges. Herein this review focuses on recent applications of Bayesian optimization (BO) to chemical products and materials including molecular design, drug discovery, molecular modeling, electrolyte design, and additive manufacturing. Numerous examples show how BO often requires an order of magnitude fewer experiments than Edisonian search. The essential equations for BO are introduced in a self-contained primer specifically written for chemical engineers and others new to the area. Finally, the review discusses four current research directions for BO and their relevance to product and materials design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Using Artificial Neural Networks to Predict Physical Properties of Membrane Polymers

Membrane polymers are a promising technology for use in many challenging gas separation applications. Here, the techniques of computer-aided molecular design can be used to search through the massive molecular space of heteropolymers and develop a set of likely candidate repeat units matching specific physical property targets. However, reasonably accurate property prediction algorithms are needed, but these algorithms must be very fast in order to be combined with an optimization framework. Artificial neural networks (ANNs), a branch of machine learning, are applied in this work to predict the physical properties of polymers. All of the physical properties investigated were found to be predicted by ANNs with R 2 scores exceeding 0.82.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

On the role of asymmetric molecular geometry in high-performance organic solar cells

Although asymmetric molecular design has been widely demonstrated effective for organic photovoltaics (OPVs), the correlation between asymmetric molecular geometry and their optoelectronic properties is still unclear. To access this issue, we have designed and synthesized several symmetric-asymmetric non-fullerene acceptors (NFAs) pairs with identical physical and optoelectronic properties. Interestingly, we found that the asymmetric NFAs universally exhibited increased open-circuit voltage compared to their symmetric counterparts, due to the reduced non-radiative charge recombination. From our molecular-dynamic simulations, the asymmetric NFA naturally exhibits more diverse molecular interaction patterns at the donor (D):acceptor (A) interface as compared to the symmetric ones, as well as higher D:A interfacial charge-transfer state energy. Moreover, it is observed that the asymmetric structure can effectively suppress triplet state formation. These advantages enable a best efficiency of 18.80%, which is one of the champion results among binary OPVs. Therefore, this work unambiguously demonstrates the unique advantage of asymmetric molecular geometry, unveils the underlying mechanism, and highlights the manipulation of D:A interface as an important consideration for future molecular design.

14 SOLAR ENERGY↗
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 OSTI2022

Role of Molecular Simulations in the Design of Metal–Organic Frameworks for Gas-Phase Thermocatalysis: A Perspective

Here, metal organic frameworks (MOFs) are highly tunable porous crystalline solids with spatially and electronically isolated catalytically active sites that have been demonstrated for a variety of thermo-, redox-, and photocatalytic reactions. Their tunable natures and relatively well-defined active sites make them advantageous for catalyst design, and molecular simulations have proven highly valuable in this endeavor. However, complexities in the MOF structure require advanced simulation strategies that accurately capture quantum chemistry at the strongly correlated transition metal cation active sites, compositional and structural changes caused by finite temperature and pressure reaction conditions, and transport effects in variously sized pore environments. Luckily, several groups have started using such simulation strategies, paving the way for rich opportunities to design MOF catalysts. Herein, we highlight such examples and provide a perspective on the needs for molecular simulations in the design of MOF catalysts moving forward.

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

Data-Driven Strategies for Accelerated Materials Design

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency. In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Direct Aerobic Generation of a Ferric Hydroperoxo Intermediate Via a Preorganized Secondary Coordination Sphere

Enzymes exert control over the reactivity of metal centers with precise tuning of the secondary coordination sphere of active sites. One particularly elegant illustration of this principle is in the controlled delivery of proton and electron equivalents in order to activate abundant but kinetically inert oxidants such as O 2 for oxidative chemistry. Chemists have drawn inspiration from biology in designing molecular systems where the secondary coordination sphere can shuttle protons or electrons to substrates. However, a biomimetic activation of O 2 requires the transfer of both protons and electrons, and molecular systems where ancillary ligands are designed to provide both of these equivalents are comparatively rare. Here, we report the use of a dihydrazonopyrrole (DHP) ligand complexed to Fe to perform exactly such a biomimetic activation of O 2 . In the presence of O 2 , this complex directly generates a high spin Fe(III)-hydroperoxo intermediate which features a DHP• ligand radical via ligand-based transfer of an H atom. This system displays oxidative reactivity and ultimately releases hydrogen peroxide, providing insight on how secondary coordination sphere interactions influence the evolution of oxidizing intermediates in Fe-mediated aerobic oxidations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗