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DOE OSTI2026

A Monolithic Artificial Leaf for Solar Methanol Production from CO 2 and H 2 O

Methanol, an important liquid fuel and chemical feedstock, has yet to be produced using solar energy, H 2 O, and CO 2 as sole inputs in a standalone device. Here, this study directly addresses this longstanding challenge through presenting the first demonstration of unbiased solar methanol production from CO 2 and H 2 O with a monolithic artificial leaf design, surpassing the previous best energy efficiency in solar alcohol production by at least 1 order of magnitude. We first develop a new generation of photocathodes based on Si micropillar arrays and a cobalt tetraaminophthalocyanine molecular catalyst. By integrating a C 60 interlayer that facilitates unidirectional electron transfer through the semiconductor/catalyst interface, we realize a photovoltage of 500 mV, one of the highest recorded for single-junction Si-based photoelectrodes in aqueous CO 2 reduction, as well as unprecedented methanol formation with a Faradaic efficiency of 30% and a partial current density of 6.3 mA cm –2 . We further integrate the photocathode with a multijunction perovskite photovoltaic minimodule to afford a standalone solar fuel system, which demonstrates a light-to-methanol conversion efficiency of 0.8%, 32 times higher than the present record in light-to-alcohol conversion with an artificial leaf.

alcohols↗

NASA NTRS1978

Computer display and manipulation of biological molecules

This paper describes a computer model that was designed to investigate the conformation of molecules, macromolecules and subsequent complexes. Utilizing an advanced 3-D dynamic computer display system, the model is sufficiently versatile to accommodate a large variety of molecular input and to generate data for multiple purposes such as visual representation of conformational changes, and calculation of conformation and interaction energy. Molecules can be built on the basis of several levels of information. These include the specification of atomic coordinates and connectivities and the grouping of building blocks and duplicated substructures using symmetry rules found in crystals and polymers such as proteins and nucleic acids. Called AIMS (Ames Interactive Molecular modeling System), the model is now being used to study pre-biotic molecular evolution toward life.

Coeckelenbergh, Y.↗

NASA NTRS1993

Contamination design of a Scientific Instrument Protective Enclosure for the Hubble Space Telescope Servicing Mission

A Scientific Instrument Protective Enclosure (SIPE) was designed to accommodate second generation science instruments (SIs) for the Hubble Space Telescope (HST) First Servicing Mission (FSM). One of the main design drivers for the SIPE is to provide a protective environment for the SIs against particulate and molecular contaminants that pose a viable threat to the SI performance. The focus of this paper will detail the methodology incorporated in the design of the SIPE to provide a controlled environment for SI protection at the launch site, during pre-launch/launch activities, and during on-orbit operations in the Shuttle bay.

Hedgeland, Randy J.↗

NASA NTRS1996

An Intense Slit Discharge Source of Jet-Cooled Molecular Ions and Radicals (T(sub rot) less than 30 K)

A novel pulsed, slit supersonic discharge source is described for generating intense jet-cooled densities of radicals (greater than 10(exp 12)/cu cm) and molecular ions (greater than 10(exp 10)/cu cm) under long absorption path (80 cm), supersonically cooled conditions. The design confines the discharge region upstream of the supersonic expansion orifice to achieve efficient rotational cooling down to 30 K or less. The collisionally collimated velocity distribution in the slit discharge geometry yields sub-Doppler spectral linewidths, which for open-shell radicals reveals spin-rotation splittings and broadening due to nuclear hyperfine structure. Application of the slit source for high-resolution, direct IR laser absorption spectroscopy in discharges is demonstrated on species such as OH, H3O(+) and N2H(+).

Anderson, David T.↗

DOE OSTI2024

Geometry-complete diffusion for 3D molecule generation and optimization

Abstract Generative deep learning methods have recently been proposed for generating 3D molecules using equivariant graph neural networks (GNNs) within a denoising diffusion framework. However, such methods are unable to learn important geometric properties of 3D molecules, as they adopt molecule-agnostic and non-geometric GNNs as their 3D graph denoising networks, which notably hinders their ability to generate valid large 3D molecules. In this work, we address these gaps by introducing the Geometry-Complete Diffusion Model (GCDM) for 3D molecule generation, which outperforms existing 3D molecular diffusion models by significant margins across conditional and unconditional settings for the QM9 dataset and the larger GEOM-Drugs dataset, respectively. Importantly, we demonstrate that GCDM’s generative denoising process enables the model to generate a significant proportion of valid and energetically-stable large molecules at the scale of GEOM-Drugs, whereas previous methods fail to do so with the features they learn. Additionally, we show that extensions of GCDM can not only effectively design 3D molecules for specific protein pockets but can be repurposed to consistently optimize the geometry and chemical composition of existing 3D molecules for molecular stability and property specificity, demonstrating new versatility of molecular diffusion models. Code and data are freely available on GitHub .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

In-Silico Design of Next Generation Cellulose-Derived Packaging Materials (CRADA Final Report)

Developing sustainable solutions for single-use packaging is an important objective to combat the environmental crisis of plastics pollution. Most embodiments of cellulose-based packaging materials, including CellophaneTM, are completely biodegradable in both terrestrial and marine environments. However, petroleum-derived alternatives offer some performance advantages for metrics such as moisture barriers and mechanical properties. This project leverages molecular dynamics simulation to investigate how molecular modifications to cellulose-based polymer assemblies impact their material properties. An important performance criterion for the modified materials was to retain biodegradability; thus, modifications by naturally occurring, biodegradable additives were the focus of this study. Specifically, we developed models with xylan and lignin of varying monomeric compositions into the cellulose matrix. The mechanical properties were investigated by performing stress-strain simulations, and the water barrier and hydrophobicity were investigated by simulating the water contact angle. Our findings indicate that the incorporation of xylan into the cellulose matrix tends to increase the mechanical properties with an optimal loading of ~27 wt%. We also predict that orienting the nanoscale directionality of the xylan chains such that they are perpendicular to the cellulose fibrils will dramatically increase mechanical strength. In contrast, the incorporation of lignin tends to weaken the composite at all loadings investigated. Simulations of water contact angle predicted that coating polymers on the surface of the cellulose assembly creates a more hydrophobic surface than incorporating them throughout the matrix. Of the coatings investigated, lignin resulted in the most hydrophobic surface, followed by pectin and keratin, which both imparted modest increases in hydrophobicity. Future experimental work done by Futamura will focus on designing material prototypes to capitalize on the predictions of performance enhancement obtained from molecular modeling. While substantial progress was made by the simulations performed in this project, there still exists a vast parameter space that we were unable to investigate, including branching, functional group decoration, and degree of polymerization of polymer additives. However, the methods developed in this initial investigation will facilitate more rapid evaluation of the impact of molecular characteristics on the performance of biopolymer composite materials and thereby accelerate future materials discovery efforts in this area.

36 MATERIALS SCIENCE↗

DOE OSTI2025

All-electron molecular tunnel ionization based on the weak-field asymptotic theory in the integral representation

Tunnel ionization (TI) underlies many important ultrafast processes, such as high-harmonic generation andstrong-field ionization. Among the existing theories for TI, many-electron weak-field asymptotic theory (ME-WFAT) is by design capable of accurately treating many-electron effects in TI. An earlier version of ME-WFATrelied on an accurate representation of the asymptotic tail of the orbitals, which hindered its implementation inGaussian-basis-set-based quantum chemistry programs. In this work, we reformulate ME-WFAT in the integralrepresentation, which makes the quality of the asymptotic tail much less critical, hence greatly facilitating itsimplementation in standard quantum chemistry packages. The integral reformulation introduced here is thereforemuch more robust when applied to molecules with arbitrary geometry. Here, we present several case studies, amongwhich is the CO molecule where some earlier theories disagree with experiments. Here we find that ME-WFATproduces the largest ionization probability when the field points from C to O, as experiments suggest. Anattractive feature of ME-WFAT is that it can be used with various types of multielectron methods whether ofdensity functional or multiconfiguration types, this inturn facilitates tunnel ionization calculation in systems exhibiting a strong multireference character.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2024

A Fluorinated Lewis Acidic Organoboron Tunes Polysulfide Complex Structure for High–Performance Lithium–Sulfur Batteries

Many challenges in lithium-sulfur (Li–S) batteries are associated with the radical change in lithium polysulfide (LPS) solubility during cycling, but chemical approaches to address such inconsistency are still lacking. Here, the use of a strong Lewis acidic fluorinated organoboron, tri(2,2,2-trifluoroethyl) borate (TFEB), is reported as a multi-functional mediator to simultaneously overcome multiple technical barriers in practical Li–S batteries. TFEB acts as an anion acceptor and forms strong molecular complexes with Lewis basic LPS. The TFEB-LPS complexes have consistent solubility across the full polysulfide spectrum and deliver several times improved better redox kinetics, unlocking a true redox catalytic mechanism that covers the majority of redox events in thick sulfur cathodes. As a result, Li–S batteries evaluated under practical conditions exhibit significantly improved discharge capacity, rate capability, and cycling stability with the addition of the TFEB additive. More importantly, TFEB also contributes to the stabilization of lithium anode in the presence of polysulfides by generating strong interfacial film. These attributes significantly improve the cycling stability of practical Li–S pouch cells, which are assembled with a unit energy density of 219 Wh kg –1 . Finally, the results provide new molecular insights on the design of unlocking solvation networks of practical Li–S systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

NCAP: Noncanonical Amino Acid Parameterization Software for CHARMM Potentials

Noncanonical Amino Acids (NCAAs) provide numerous avenues for introduction of novel functionality to peptides and proteins. NCAAs can be incorporated through solid phase synthesis or genetic code expansion in conjugation with heterologous expression of the encoded protein modification. Due to the difficulty of synthesis, wide chemical space and lack of empirically resolved structures modeling the effects of NCAA mutation is critical for rational protein design. To evaluate the structural and functional perturbations NCAAs introduce we utilize molecular potentials that describe the forces in protein structure. Most potentials such as CHARMM are designed to model canonical residues but can be parameterized in include novel NCAAs. Here, in this work, we introduce NCAP a software package to generate CHARMM compatible parameters from quantum chemical calculation. Unlike currently available tools NCAP is designed to recognize NCAA structure and automatically bridge the gap between DFT calculations and potential parameters. For our software we discuss workflow, validation against canonical parameter sets and comparison to published NCAA-protein structures.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1998

Computational Nanoelectronics and Nanotechnology at NASA ARC

Both physical and economic considerations indicate that the scaling era of CMOS will run out of steam around the year 2010. However, physical laws also indicate that it is possible to compute at a rate of a billion times present speeds with the expenditure of only one Watt of electrical power. NASA has long-term needs where ultra-small semiconductor devices are needed for critical applications: high performance, low power, compact computers for intelligent autonomous vehicles and Petaflop computing technology are some key examples. To advance the design, development, and production of future generation micro- and nano-devices, IT Modeling and Simulation Group has been started at NASA Ames with a goal to develop an integrated simulation environment that addresses problems related to nanoelectronics and molecular nanotechnology. Overview of nanoelectronics and nanotechnology research activities being carried out at Ames Research Center will be presented. We will also present the vision and the research objectives of the IT Modeling and Simulation Group including the applications of nanoelectronic based devices relevant to NASA missions.

Saini, Subhash↗

NASA NTRS1998

Computational Nanoelectronics and Nanotechnology at NASA ARC

Both physical and economic considerations indicate that the scaling era of CMOS will run out of steam around the year 2010. However, physical laws also indicate that it is possible to compute at a rate of a billion times present speeds with the expenditure of only one Watt of electrical power. NASA has long-term needs where ultra-small semiconductor devices are needed for critical applications: high performance, low power, compact computers for intelligent autonomous vehicles and Petaflop computing technolpgy are some key examples. To advance the design, development, and production of future generation micro- and nano-devices, IT Modeling and Simulation Group has been started at NASA Ames with a goal to develop an integrated simulation environment that addresses problems related to nanoelectronics and molecular nanotecnology. Overview of nanoelectronics and nanotechnology research activities being carried out at Ames Research Center will be presented. We will also present the vision and the research objectives of the IT Modeling and Simulation Group including the applications of nanoelectronic based devices relevant to NASA missions.

Saini, Subhash↗

DOE OSTI2024

ReaxFF Reactive Force Field for Exploring Electronically Switchable Polarization in Zn 1– x Mg x O Ferroelectric Semiconductors

Cation misfit in traditional ferroelectric crystals offers a new material platform that can drive electronic components toward structural miniaturization and high-density integration, enabling deviation from von-Neumann architectures. Here, we explore ferroelectricity in Zn 1–x Mg x O, a nontraditional ferroelectric material with tunable properties. Using data from density-functional theory calculations, we have developed a ReaxFF reactive force field to explore the ferroelectric properties of Zn 1–x Mg x O and reveal the hysteresis behavior. We discover that ferroelectric switching can be observed at a critical thickness of 10 nm with a residual polarization of ~100 μC/cm 2 . Our analysis indicates that an increase in Mg-substitution correlates with a decrease in the coercive field. We also observe a strong temperature dependence of the coercive field in Zn 1–x Mg x O, with values decreasing as the temperature increases. Additionally, we find that the distribution of Mg atoms significantly impacts the coercive field, with a clustered distribution leading to a substantial increase. In particular, a decrease in coercive field values is observed when Mg atoms are randomly distributed, compared to uniform distribution. Furthermore, leveraging tunable hysteresis behavior offered by varied percentages and distribution of Mg-substitution provides valuable insights into the design of next-generation functional devices and will inspire further investigations.

36 MATERIALS SCIENCE↗

NASA NTRS2011

Experimental and Modeling Studies of the Combustion Characteristics of Conventional and Alternative Jet Fuels. Final Report

The objectives of this project have been to develop a comprehensive set of fundamental data regarding the combustion behavior of jet fuels and appropriately associated model fuels. Based on the fundamental study results, an auxiliary objective was to identify differentiating characteristics of molecular fuel components that can be used to explain different fuel behavior and that may ultimately be used in the planning and design of optimal fuel-production processes. The fuels studied in this project were Fischer-Tropsch (F-T) fuels and biomass-derived jet fuels that meet certain specifications of currently used jet propulsion applications. Prior to this project, there were no systematic experimental flame data available for such fuels. One of the key goals has been to generate such data, and to use this data in developing and verifying effective kinetic models. The models have then been reduced through automated means to enable multidimensional simulation of the combustion characteristics of such fuels in real combustors. Such reliable kinetic models, validated against fundamental data derived from laminar flames using idealized flow models, are key to the development and design of optimal combustors and fuels. The models provide direct information about the relative contribution of different molecular constituents to the fuel performance and can be used to assess both combustion and emissions characteristics.

Meeks, Ellen↗

DOE OSTI2025

Evaluating the Structural Response of Amphiphilic Monolayers to Environmental Stimuli

Amphiphilic monolayers composed of end groups with distinct polar and nonpolar functional groups offer rapid and reversible interfacial adaptation in response to environmental stimuli such as a change in interfacial medium polarity. We have synthesized and characterized a suite of monolayers with functional groups of competing polarity designed to reconfigure their interfacial chemical composition in response to solvent polarity. In these films, the end group is designed to be able to reorient and expose the functional groups that minimize the interfacial free energy between the film and the environment. Using a combination of spectroscopic, computational, and wettability studies, we have investigated the responsive interfacial behavior of different end groups upon exposure to environments with varying polarities. Contact angle measurements across a series of polar and dispersive probe liquids reveal trends that reflect the underlying molecular flexibility and composition. Vibrational sum frequency generation (SFG) spectroscopy and atomistic molecular dynamics (MD) simulations confirm solvent-driven reorientation of the end groups, with restructuring observed at the interface. To quantify these effects, we have developed a surface energy calculation model that incorporates solvent-induced surface rearrangements into the estimations. Our findings reveal a strong dependence of surface energy and switching behavior on the length and flexibility of the functionalities in the end group, which affects the exposure of certain interfacial compositions under different solvents. These results offer new insights into the design of adaptive monolayers and provide a framework for evaluating solvent-responsive surfaces.

functional groups↗

DOE OSTI2026

Carbon-Based Quantum Information Science with Symmetry Protected Topological States (Final Report, DOE-BES award DE-SC0023105)

This research program established the scientific foundation for the rational, bottom-up design, synthesis, isolation, and investigation of symmetry-protected topological (SPT) electron spin qubits embedded in graphene nanoribbons (GNRs). The work focused on integrating atomically precise low-dimensional carbon nanostructures with emerging quantum logic architectures, providing a pathway toward scalable quantum materials for next-generation computing and sensing technologies. A central component of the program was the elucidation of fundamental relationships between real-space molecular architecture, local spin density distributions, electronic band dispersion, and energy level alignment in atomically precise GNR systems. These correlations define key operational parameters of SPT qubits and were systematically investigated to establish quantitative benchmarks against established molecular and solid-state spin qubit platforms. Attention was given to properties critical for quantum device performance, e.g. decoherence times, spectral sharpness of energy transitions, and tunable exchange interactions between spin states. The research demonstrated that these parameters can be engineered with atomic precision through scalable bottom-up synthetic strategies. Theory-guided design played a central role in identifying candidate structures hosting topologically protected spin states. Experimental validation was performed using both ensemble measurements and single-molecule characterization. In addition to advances in quantum materials synthesis, the program developed and applied spin-sensitive scanning probe microscopy techniques capable of directly probing quantum states and dynamic processes with atomic-scale spatial resolution. These capabilities enabled direct observation and characterization of quantum structures at the single-atom level. While the research activities were primarily hypothesis-driven fundamental investigations, the program adopted a comprehensive materials-by-design framework aimed at translating scientific discoveries into technological concepts compatible with scalable and intelligent manufacturing approaches.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A Robotic High-Throughput Grid-Search Platform for Mapping Phase Behavior in Triblock Copolymer–Homopolymer Blends

We present a high-throughput experimental investigation of the phase behavior in triblock copolymers (PS-b-PB-b-PS and PS-b-PI-b-PS) and polystyrene (PS) homopolymer blends as a function of homopolymer molecular weight (MW) and blend ratio. Using a robotic thin-film processing platform (NOVA) integrated with Grazing Incidence Small-Angle X-ray Scattering (GISAXS) and Atomic Force Microscopy (AFM), we systematically mapped the order–disorder transition (ODT) boundaries and domain spacing evolution across a broad MW range (4.0–101.3 kDa) with varying homopolymer loadings (10% to 90%). The results reveal three distinct regimes: low-MW homopolymers, corresponding to the wet-brush regime produced only gradual domain swelling before disordering at high blend ratios (weight fraction); medium-MW homopolymers, corresponding to thedry-brush regime induced significant domain spacing increase up to 80% followed by earlier disordering, while high-MW homopolymers led to macrophase separation with minimal changes in domain spacing. Additionally, coarse-grained molecular dynamics simulations confirmed our experimental finding that in the low-MW region, the PS homopolymer uniformly distributed in the PS domain. These findings demonstrate that homopolymer molecular weight critically governs both the extent of domain swelling and the onset of disorder in triblock copolymer systems. This high-throughput platform enables the rapid mapping of composition–morphology relationships and can be integrated with AI/ML tools for designing next-generation nanostructured polymers.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Structured for success: conjugated polymer binders with tailored composition and architecture for lithium-ion batteries

Conjugated polymer binders are replacing conventional binders in lithium-ion batteries. Herein, we examine how molecular engineering and hierarchical nanostructuring govern binder functionality and electrochemical performance. Lithium-ion batteries (LIBs) are the leading energy storage technology, yet enhancing their energy density and cycle life remains critical. Significant progress has been made in high-capacity anodes and high-voltage cathodes, but their performance is hindered by electrode degradation, where it is related to the behaviors of binders at the surface and interface. Conventional non-conductive binders like poly(vinylidene difluoride) (PVDF), combined with conductive additives, often fail to maintain electrical pathways under repeated volume changes. Alternatively, conjugated polymer binders have emerged as a superior alternative, simultaneously offering intrinsic conductivity, mechanical flexibility, and strong adhesion through π-conjugated backbones and functional groups. Their tunable molecular structure enables efficient electron/ion transport while mitigating electrode cracking. Additionally, the development of hierarchically ordered nanostructures in conjugated polymer binder can further enhance their electrochemical performance. This review examines the design principles of conjugated polymer binders, focusing on molecular engineering and nanostructural control to optimize their performance in high-loading electrodes, such as silicon-based anodes. By addressing key challenges in binder functionality, these advanced materials pave the way for next-generation high-energy-density LIBs.

Jin, Xiuyu↗

DOE OSTI2026

Molecular concentration field design using closed-form steady-state solutions

Control over spatial concentration fields represents a fundamental challenge in designing synthetic biological systems and programmable soft materials. While nature creates morphogen gradients that orchestrate complex developmental processes, synthetic approaches have largely relied on empirical optimization and computationally intensive simulations. Here, we present an analytical framework for steady-state concentration fields generated by finite-sized localized sources in diffusion–degradation systems and derive closed-form solutions for one-, two-, and three-dimensional geometries. By expressing these solutions in dimensionless form, we show that gradient steepness and spatial structure are organized by the Thiele modulus, which captures the competition between diffusion and degradation length scales. The analysis reveals distinct design regimes: in degradation-dominated systems, gradient shape is governed by exponential decay and becomes dimension-independent, whereas in diffusion-dominated systems, gradient magnitude and extent follow dimension-dependent power-law scaling. Building on these results, we introduce a quantitative design strategy that uses threshold-based criteria to program concentration ranges by tuning physically accessible parameters, most directly the production rate, while holding transport and degradation properties fixed. Comparisons with numerical solutions and reported experimental systems demonstrate consistency with the predicted scaling behavior. Together, this work provides a generalizable and physically transparent framework for designing steady-state concentration fields in synthetic biological and soft matter systems, enabling predictive control of gradient-mediated organization without reliance on extensive numerical optimization.

Kim, Dong Woo [Johns Hopkins University, Baltimore↗