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At least 739 records · Page 41

Quantum Sensed Electron Spin Resonance Discovery Platform (Final Report)

The properties of materials can change dramatically at the nanoscale new and useful properties can emerge. An example is found in the paramagnetism in iron oxide magnetic nanoparticles. Using magnetically sensitive nitrogen-vacancy centers in diamond, we developed a platform to study electron spin resonance of nanoscale materials. To implement the platform, diamond substrates were prepared with nitrogen vacancy centers near the surface. Nanoparticles were placed on the surface using a drop casting technique. Using optical and microwave pulsing techniques, we demonstrated T1 relaxometry and double electron-electron resonance techniques for measuring the local electron spin resonance. The diamond NV platform developed in this project provides a combination of good magnetic field sensitivity and high spatial resolution and will be used for future investigations of nanomaterials and quantum materials.

36 MATERIALS SCIENCE↗

Nanoscale X-ray Imaging and Dynamics of Electronic and Magnetic Materials

This project supported cutting-edge nanoscale characterization developments including X-ray Imaging by utilizing the power of Coherent X-ray Diffractive Imaging (CXDI). This research pioneered new directions in studies of nanoscale dynamics using X-ray Photon Correlation Spectroscopy (XPCS) and Ultrafast X-ray Scattering (UXS), extending our understanding of science and technology at the limits of ultrasmall (atomic/nanoscale) and ultrafast (from seconds to femtosecond dynamics). The research funded by this award spans a wide range of condensed matter and materials physics systems, from correlated oxides and nanomaterials to energy-related materials, and quantum materials for neuromorphic computing.

25 ENERGY STORAGE↗

Surface Charge at an Oil/Water Interface Promoting the Enhancement and Assignment of Water Combination Bands

Given the different polarities and distinct chemical structures, it is no wonder that oil and water are incompatible neighbors. They can be forced to cooperate if provided sufficient energy or a suitable intermediary. Emulsions are the result of such a cooperation, where an emulsifying agent (the intermediary) in the form of a surfactant or a cocktail of surface stabilizing compounds allows for the ‘mixing’ of oil and water. Surfactant stabilized emulsions that are nanoscale in size (nanoemulsions) have caught the attention of many because of their newly discovered use in the synthesis of nanomaterials, oil recovery, drug delivery, and food science. Unlike smaller emulsions (e.g. microemulsions with 2-20 nm diameters), very little is known about the molecular level properties of nanoemulsions (NEs) whose diameters are in the 100-500 nm range. One thing that is well known is the macroscopic properties of droplets from these two size regimes are dramatically different, often for reasons not yet fully understood. Nanoemulsions do not form spontaneously and require an external shear beyond ordinary procedures used to create micelles. This shear is required to overcome the effects of surface tension and create droplets in the nanoscale regime. Once formed, however, they can be stable for long periods of time, making them very attractive for commercial and pharmaceutical products requiring a long shelf life. What is not well known is the interfacial molecular processes that lead to the formation and stability of nanoemulsions including those stabilized by surfactants and/or polymers. Such knowledge is important in understanding the molecular structure-function relationship that assists in predicting what additives and solvents are necessary for a specific application. Key to advancing nanoemulsion utility is to develop the needed molecular-level understanding of the structure and bonding interactions present at the surface of these soft nanoparticles.

36 MATERIALS SCIENCE↗

Materials genome innovation for computational software (magics) center

Functional layered material (LM) architectures will dominate nanomaterials science in this century. We have developed theory, modeling, simulation, and software and data tools that enhance understanding and AI guide synthesis, enable characterization of complex structures, and improve capabilities in the predictive design and growth of LMs. Research at the Center has focused on: Computational synthesis and characterization: AI guided synthesis and experimental synthesis of stacked LMs with tailored properties via optimized chemical vapor deposition (CVD) growth and liquid-phase exfoliation; study defects, edges, grain boundaries, wrinkling of atomic layers and their effects on chemical, mechanical, electrical, and optical properties. Far-from-equilibrium processes: Joint experimental and simulation based probe of electronic processes with NAQMD and ultrafast X-ray free-electron laser (XFEL) and ultrafast electron diffraction (UED) facilities at Stanford. Experimentally validate NAQMD by ultrafast electron diffraction and X-ray spectroscopy studies of structural and excited state dynamics, shape fluctuations, and phonon dynamics. Scalable software: Simulation engines for desktop-to-exascale platforms using low-overhead, linear-scaling QMD algorithms; divide-conquer-recombine NAQMD with electronic excitations; extended-Lagrangian reactive molecular dynamics (RMD), machine learning (ML) based neural-network quantum molecular dynamics (NNQMD), and super-state accelerated molecular dynamics (AMD) and kinetic Monte Carlo codes; thermal and electrical transport software; and design 3D architectures of LMs with desired functionality using scalable software. Distribution of software and data, and training: Software and simulation-experimental data generated within the Center are distributed to the materials science community via Berkeley Materials Project (MP) framework. We have also organized three workshops for software distribution and training at USC (Nov. 2017, Mar. 2018) and Gaithersburg, MD (Nov. 2018) to train researchers, with the last one in focused on underrepresented groups, in collaboration with Howard University which is one of the largest HBCUs. The Center supported a total of 46 personnel and 6 undergraduate students. These include 14 faculty, 11 postdoctoral research associates, 20 graduate research assistants, and mentored 6 undergraduate students. This resulted in the publications of 63 research papers that include 46 publications on Reactive and Quantum Dynamics Simulations, 13 publications on Machine Learning for Quantum Materials, and 4 publications on Quantum Computing.

2D Materials↗

Process Intensification for Nanostructure Aluminum Extrusions

A new technology called Shear Assisted Processing and Extrusion (ShAPE™), pioneered at the Pacific Northwest National Laboratory (PNNL), has the potential to revolutionize the US extrusion industry. Maturation of the ShAPE™ process would create a new cross cutting US manufacturing technology that advances three key the objectives within AMO; namely, nanomaterials processing, process intensification, and materials for extreme and harsh environments. PNNL and SCM Metals Products, Inc. (SCM), a division of Kymera International, will collaborate to mature the ShAPE™ extrusion process beyond TRL 3 to increase the likelihood of its adoption by industry. PNNL’s custom (one-of-a-kind in the world) ShAPE™ machine will be used to extrude round rods of high strength aluminum alloy feedstock powder provided by SCM. As proof-of-concept, PNNL has previously extruded 5 mm diameter rods with SCM aluminum alloy powder AL-12.4TM. This project aims to scale up the process to a diameter of 25 mm while retaining the excellent mechanical properties achieved for the 5 mm diameter rods. The degree of process intensification with ShAPE™ will also be estimated. The primary objectives of this project are as follows. 1) Fabricate 25 mm diameter nanostructured extrusions in bulk, directly from AL-12.4TM aluminum alloy powder without the need for canning, degassing, compaction, and other intermediate steps typical of powder metallurgy extrusion. 2) Achieve a microstructure with an ultrafine grained (UFG <1 µm) aluminum matrix having refined and homogenously distributed nanoscale second phases. 3) Show that the ram force can be significantly reduced compared to conventional powder metallurgy extrusion of the same material and estimate the extent of process intensification that may be possible with ShAPE™. 4) Demonstrate improved high-temperature mechanical properties compared to conventional extrusion of the same material. The following tasks will be undertaken to achieve these objectives. PNNL will develop the die set and process parameters necessary to fabricate Al-12.4TM extrusions with a 25 mm diameter. Microstructural analysis will be performed by PNNL while mechanical testing will be conducted by SCM. With information learned from the process development and characterization, PNNL will perform an estimate of the degree of process intensification that may be possible with ShAPE™.

42 ENGINEERING↗

Additively Manufactured, Lightweight, Low-Cost Composite Vessels for Compressed Natural Gas Fuel Storage

This project will develop a process to combine AM via direct ink writing (DIW) technology for CFC printing and to use design optimization tools pioneered at LLNL, with advances in resin/composite formulation enabled by chemical and nano-material modification to produce lightweight low-cost CNG tanks. Our approach will yield sub-scale prototype composite pressure tanks equivalent to Type-5 CNG vessel designs that demonstrate a potential cost-benefit advantage. Central to our vision is using agile AM and design based on computationally informed DIW of both short and continuous CF, further coupled with high-performance thermoset polymer matrixes modified by emergent nanomaterials. Our single-stage, multi-material AM technology, combined with a decreased volume fraction of CF and an increased proportion of economically advantaged short fiber, all together drive the reduction in manufacturing time and overall cost. Importantly, reductions in continuous fiber and overall fiber volume fraction will be achieved without detriment to the mechanical strength of the composite vessel. This will be achieved by employing a single process using multi materials grading involving a thermoset resin “ink” modified with aligned nanoplatelets to leverage the efficient tortuous-path gas barrier effect, printed as an inner flexible gas barrier as the initial stage in our manufacturing process before compositionally grading the AM feedstock in real-time to transition to a rigid, structural CF-filled resin. The proposed hybrid construction is projected to achieve pressure ratings at a service range of 2,900–3,600 psi with a 3× burst safety factor comparable to conventional filament-wound composite tanks with an estimated 30–50% reduction in total manufacturing cost.

03 NATURAL GAS↗

The Scientific Case for Concurrent Neutron and X-ray Scattering and Spectroscopy

The interrogation of materials with X-rays or neutrons to determine the structure, energetics, and dynamics of materials is fundamental to advancing materials' physical and chemical science and developing innovative material technologies. A transcending challenge in developing novel materials is that progress hinges on understanding the structure and dynamics across multiple time and length scales in complex materials that feature multiple components, interfaces, and compositions. Despite the ever-growing demands on materials’ characterization, existing approaches are almost exclusively based on isolated X-ray or neutron scattering, i.e., an approach commensurate with the more narrowly defined needs of fifty years ago. A three-day workshop sponsored by the U.S. National Science Foundation (NSF) analyzed the demand for concurrent neutron and X-ray (NeX) experiments. It was held at the Spring Hill Suites, San Jose, California, from June 2 to 4, 2022. In this workshop, 70 national and international experts ascertained the crucial need to establish NeX capabilities to advance the science of complex materials and systems in the US. Here, we illustrate the need for NeX scattering and spectroscopy experiments by showcasing examples that span areas as diverse as biomaterials, energy science, soft matter, and nanomaterials. To provide NeX capability will require new instrumentation that enables concurrent experiments. Affected areas include chemistry, soft matter, quantum materials, pure and applied chemistry, bioscience, geoscience, and applied materials. NeX benefits research outcomes due to the complementarity of the two techniques, which is essential for better model refinement. While joint refinement of data from separate neutron and X-ray experiments is critical to avoid ambiguities, especially in multiphase-multicomponent materials, concurrent experiments overcome scientific and technical barriers associated with single measurements, separated by location and, thus, time. Among all the examples, these factors introduce uncertainties in the results that complicate data analysis. [1,2] [3] While models are strongly sample-dependent, the principles of joint refinement are generally applicable to these disciplines, including the development of advanced parameterization, modeling, and analysis techniques that also consider the temporal and spatial resolutions of the two methods, leading to unambiguous data interpretation. Solutions for technical barriers must be found to realize NeX experiments, including developing robust sample environments that meet the optical requirements of neutrons and X-rays.

36 MATERIALS SCIENCE↗

Building Artificial Layered Solids from the Bottom-up: Materials by Design to Enable New Energy Technologies

This final technical report summarizes the key accomplishments on this DOE Early Career Program award received by PI Guihua Yu at the University of Texas at Austin. The main goal of this ECP award was to develop synthetic methodologies, self-assembly approaches towards structurally controlled nanosheets-like solids from the bottom up, and to understand and characterize their chemical/physical characteristics for the design of future-generation energy devices with novel functions and properties, that will have direct implications for energy science and technologies such as energy storage and conversion, and catalysis. The project accomplished these goals by completing the following objectives: • Rational design, synthesis, and self-assembly of structurally-controlled molecular ‘nanosheets’ materials. Moving beyond conventional van der Waals two-dimensional crystals, this project enables new synthesis and processing strategies to develop ultrathin nanosheets materials, from inorganic transition-metal oxides-based, to hybrid organic-inorganic nanomaterials, with structural factors such as facet, thickness and pore structure being well controlled during synthesis or assembly processes. • Fundamental understanding and electrochemical characterization of these assembled molecular ‘nanosheets’ materials via charge/mass transport studies through electrochemical intercalation of different metal ions for next-generation energy storage, as well as electrocatalytic studies using this new material platform for understanding catalytic reaction kinetics and the roles of surface functionalization and interface interactions owing to atomic thickness, nanoscale porosity, and other structural factors.

36 MATERIALS SCIENCE↗

Final Technical Report - Rapid Surface Microanalysis using a Low Temperature Plasma

This project focused on improving our current understanding and scientific knowledge in the area of plasma-surface interactions and plasma assisted material synthesis related to advanced microelectronics and nanotechnology. Current challenges include: controlling the interaction of Low Temperature Plasma (LTP) with a single layer of atoms to manufacture integrated circuits, continued miniaturization of integrated circuits, LTP processing of material surfaces and thin films to enable industrial scale fabrication of advanced microelectronics, synthesis of new materials, nanomaterials, nanotubes, and complex materials, Technology developed in this subtopic is of value to either (i) enable scans of surfaces (~1 sq. cm area) using various microscopies (electron, optical, other) at high resolution (micron or sub-micron resolution) rapidly (hours or days rather than years to complete a high-resolution scan of such a large surface area), or (ii) enable scans of surfaces (~1 sq. cm area) using various microscopies (electron, optical, other) at relatively low resolution rapidly, then apply algorithms to select spots for micron-scale imaging. Sputtering occurs when particles of a solid material are ejected from its surface by energetic particles from a plasma. While the degradation of the solid material and the subsequent deposition of the ejected material onto vulnerable surfaces are the usual subjects of sputtering studies, plasma science has yet to be combined with sputtering to create new diagnostics devices and systems. Small changes in the design of the plasma discharge device make it possible to create broad plasma beams for rapid scanning or small plasma beams to obtain the distribution of ejected elements with micron resolution. In the high-resolution use, the ion flux is extracted from the gas-discharge plasma and focused by a spherical emission surface to micron sizes onto the target specimen, providing very local sputtering and local elemental analysis. We call this “self-focusing”. The radiation from the excited and ionized sputtered atoms is recorded by a spectrometer through a window and fiberglass cable and analyzed with standard software packages used for optical glow discharge spectroscopy. Computer simulations of beam formation were used to verify and optimize the designs to be tested. A prototype was designed, constructed, and used to start experiments of beam formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

LDRD 227829: Multifunctional Composite LDRD: Radiation Effect on CeO 2 -HDPE Composites

Commercial high-density polyethylene (HDPE) is lightweight with excellent mechanical properties but has limited thermal stability. To enhance this, lanthanide-based nanomaterials like CeO 2 were mixed with HDPE. Using a twin-screw extruder improved dispersion. This study examines the effects of neutron, X-rays and gamma radiation on the crystallinity of polymer of CeO 2 -HDPE composites.

36 MATERIALS SCIENCE↗

2019 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is necessary to meet the continual challenging national workforce needs that arise as computational science and engineering problems continue to grow in scope and complexity. Computational science and engineering (CSE) is a multidisciplinary approach that uses scientific computing to solve practical problems methods and to supply technical tools across the scientific discovery spectrum. In particular, the DOE CSGF emphasizes high-performance computing (HPC) that enables CSE that advances science and engineering in directions important to the DOE and the economy in general. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines, such as biology and cosmology, have been transformed through the augmentation of scientific observation via HPC. At government laboratories and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, renewable energy, fusion-reactor design, additive manufacturing, nanomaterials for next-generation batteries and transistors, and turbine and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development — including continuing to rise to the challenge of pandemic-related research. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing.” An explosion in scientific and technological data has driven the need for increasingly sophisticated HPC to transform those data into scientific understanding. With access to more and more data and the proliferation of HPC, Machine Learning and Artificial Intelligence are experiencing a renaissance, complementing the now well-established use of computational simulation. Indeed, in its September 2020 subcommittee report on “AI/ML, Data Intensive Science and High-Performance Computing”, the DOE Advanced Scientific Computing Advisory Committee (ASCAC) explicitly called for a fellowship program to train computational and data scientists to tackle exascale and data-intensive computing challenges. This collaboration of empirical and theory-based modeling will increasingly inform federal policymakers whose decisions affect American society and future generations, and it requires highly skilled and intellectually agile computational scientists who can support the fast-moving DOE National Laboratory research environment. In fact, the DOE CSGF program has explicitly and consistently addressed this need.

97 MATHEMATICS AND COMPUTING↗

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Engineered Colloidal Hetero-nanocrystals for Photocatalytic Hydrogen Production

This research is focused on the development of novel semiconductor hetero-structured nanocrystals which can convert solar energy into hydrogen using photocatalytic water splitting reactions. The newly developed nanomaterials could produce cost-effective chemical fuel by employing less-energy intensive technology.

08 HYDROGEN↗

Comprehensive Diagnostics for Bond-Selective Nanocarbon Growth in Plasmas

This award was continuation funding for our previously supported efforts into carbon nanoparticle synthesis with tunable bond hybridization, including for luminescent carbon nanoparticles, amorphous carbon nanoparticles, and eventually nanodiamond. Beginning in early 2021 we supported preliminary experiments with in-house funds. In February 2021 our user proposal to the PCRF to investigate this topic was accepted and our experiments at PCRF took place in July 2022. DOE awarded this proposal to support data analysis based on those experiments, and supported the continued efforts towards finalizing that work. With those results and further efforts, we will be able to finalize our early research into nucleation and growth of carbon nanoparticles for a long-term objective of selective bonding in carbon and other nanomaterials grown in low-temperature plasmas. We made several important discoveries.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Survey of Technologies to Meet PAG limits for Detection of Cesium-137 in Water

The goal of this report is to evaluate the process of adding a sorbent to the sampling process to preconcentrate Cs-137 and then analyze the sorbent to provide a rapid assessment of results to guide decisions on drinking water sources and the protection of the public. Multiple unit design variables were considered: sample configuration/geometry, sorbent efficiency, sample volume. Model simulations demonstrated through these unit design efficiencies that 10 L of sample volume processed through a sorbent provides nearly two orders of magnitude improvement in sample counting time to provide results to a decision maker than the current process. Over 60 publications and reports concerning Cs-137 and sorbents were evaluated. The key attributes were readiness of sorbent to be deployed in a mobile laboratory environment, and minimum sample preparation and conditioning. Examples of sorbents not considered further included nanomaterials, which have not been evaluated at a commercial scale and are limited in availability. The recommended sorbents for further consideration include: ferrocyanide salts, zeolite, and chemically modified granular activated carbon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Boride-based Ceramic Super-high Temperature Thermocouples in Harsh Environments (Final Scientific/Technical Report)

An electromotive force (emf) can be generated along a temperature gradient between the cold end and hot end of a thermoelectric material, termed the Seebeck effect. Based on the Seebeck effect, metallic alloys have been extensively employed to detect temperatures for centuries, named thermocouples. However, commercially available thermocouple alloys suffer from limitations, such as oxidation, chemical degradation, and poor long-term stability under high-temperature harsh environments. This DOE-funded project aimed to develop high-temperature, chemically tolerant thermocouples suitable for operation in extreme environments relevant to semiconducting thermoelectric materials. The research focused on boride-based semiconducting thermoelectric compounds as candidates for next-generation thermocouples with enhanced oxidation resistance, chemical stability, and thermal robustness under conditions representative of charcoal-fired electricity facilities. During the funded years, boride materials were synthesized using an arc-plasma technique under ambient air and argon atmospheres, enabling scalable and cost-effective production compared with conventional boride fabrication methods. The synthesized borides were processed into nanostructured powders, followed by consolidation into dense bulk materials using a spark plasma sintering (SPS) bottom-up approach. Comprehensive characterization was performed, including microstructural analysis, electrical transport measurements, and optical and thermal property evaluation. Both p-type and n-type boride electric legs were fabricated and integrated into boride-based thermocouples. The thermal and irradiation stabilities of the boride nanomaterials and bulk thermoelectric materials were systematically evaluated to assess suitability for long-term operation in harsh environments. Additionally, 12 students were broadly hands-on trained spanning the full research workflow, including word processing and technical editing (e.g., LATEX for manuscript and poster preparation), data collection and analysis (using Python and related libraries and hardware interfaces), sample preparation (including arc-plasma synthesis and spark plasma sintering), and advanced characterization techniques (such as X-ray diffraction, UV–vis spectroscopy, electron microscopy, differential thermal analysis (DTA), and Seebeck coefficient measurements, etc). Overall, this project demonstrated the feasibility of boride-based thermoelectric materials as durable high-temperature thermocouples, providing a promising pathway toward robust temperature sensing technologies aligned with DOE energy infrastructure and extreme-environment monitoring needs.

20 FOSSIL-FUELED POWER PLANTS↗

New principles of self‐organization created through the interplay of DNA condensates, microtubules, and motors

Bioinspired design—which holds great promise for a new generation of materials that are robust to defects, scalable under green manufacture, environmentally responsive, and programmably reconfigurable—requires mastery over molecular self-organization. Yet, from its specific mechanisms to most general architectures, the principles governing self-organization remain poorly understood and not even fully enumerated. For living systems, one obvious architectural principle is the modular reuse of a few simple molecular components in myriad combinations to achieve more complex phenomena. For example, the mechanical tasks of a cell are driven by the nonequilibrium dynamics of cytoskeletal filaments and molecular motors—the same filaments and motors, reprogrammed by a variety of modulators, perform tasks ranging from cell movement to division. Similarly, many compartmentalization tasks are performed by liquid-like condensates of simple components, which act as membraneless organelles to localize particular molecules in space and time (e.g. for gene regulation or RNA processing). In a few cases, condensates combine and interact with the cytoskeleton to create still more complex phenomena, e.g. the nucleation of microtubule asters from the centrosome (a protein condensate) to form the mitotic spindle during cell division. Very little is known about the fundamental mechanisms of such filament-plus-condensate phenomena. Despite few examples, the landscape of behaviors that can be achieved through the combination of condensates, filaments, and motors appears vast. However, exploration has been hindered by a lack of systems that have sufficiently programmable and dynamically tunable interactions between component condensates, filaments, and motors. We proposed to combine programmable DNA condensates, filamentous microtubules, and light-controlled motors into self-organizing systems whose principles go beyond those that have been observed in nature. In one limit, our systems will use microtubules and motors to create the molecular analog of a network of roads, which will organize droplets of DNA condensates capable of carrying molecular cargo. DNA condensates coupled to motors will flow from one microtubule aster hub to another, with their direction and timing controlled by DNA circuits. In another limit, microtubules will swim through bulk DNA condensates and exhibit strong interactions with boundaries between different types of condensates. Microtubule swimmers will reflect, get trapped, or refract at boundaries, under a mechanical analog of the classical optical index of refraction. DNA condensates having different mechanical indexes of refraction will be used to construct the analog of optical lenses, so that microtubule swimmers can be manipulated like light—collimated, diffracted, focused, and sorted based on properties analogous to wavelength. These two limits define two new architectures, within which multiple new mechanistic principles for self-organization will be discovered and explored. To explore these architectures, the motor-based coupling between DNA condensates and filaments will be controlled in time and space through the use of opto-proteins that create reversible links between DNA condensates and motors upon illumination. For each principle of interest, patterns of light will create virtual experiments by defining patterns of activity where DNA condensates walk along filaments, or filaments swim through condensates, and patterns of inactivity which will serve either as controls, or as boundary conditions vital to create the desired phenomena. This research serves the goals of Basic Energy Sciences Biomolecular Material Program by elucidating the principles by which the emergent, nonequilibrium behavior of collections of DNA condensates, motors, and microtubules can be programmed by environmental light patterns to create complex motion and materials transport. Because DNA condensates can be readily coupled to virtually any high performance nanomaterial, from carbon nanotubes, to metal nanoparticles, to light harvesting systems, this work provides a path to the construction, self-maintenance and reconfiguration of materials relevant to the Department of Energy.

60 APPLIED LIFE SCIENCES↗

Graphene oxide gluing layer enabling macroscale tribology applications of pristine graphene

In recent studies of two-dimensional (2D) nanomaterial-based solid lubricants, the importance of durability has been emerging for real engineering-scale applications. To achieve this, a transfer layer formation is essential to prevent the wear of the mechanical systems. However, it has been challenging for pristine graphene (PG) to induce a material transfer due to chemical inertness. In this study, we suggest an easy-to-process strategy to promote the huge material transfer of the PG onto the counterpart contacting material. We utilized graphene oxide (GO) as a gluing layer between the PG film and the counterpart contact surface to realize the superior tribological performance. The high interaction energy of the GO from its functional groups makes a contribution to the material transfer of PG, which is unveiled by a systematic analysis of the counterpart contact surface and the wear track. The huge solid transfer layer not only makes a wear-resistant contact interface between the transfer layer and the underlying film by densification and oxidation, but also reduces surface interaction energies, finally resulting in a significant improvement in durability.

graphene oxide (GO)↗