Search NASA⌕ Search

SEARCH · Search NASA

Results for “self”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Correlating structure, self-assembly chemistry and conductivity of trithiocyanuric acid on Au(111)

The majority of candidates for simple model molecular-electronic components consist of a conductive π-conjugated hydrocarbon linker attached to at least two anchoring groups, such as thiols or isocyanides. It has been found that select molecules self-assemble on gold surfaces, creating one-dimensional conductive structures that act as “molecular wires”. Furthermore, these oligomers can form molecular bridges between gold nanoparticles, leading to the creation of simple molecular-electronic devices. This raises the question whether other π-conjugated molecular linkers could exhibit similar behavior that might offer a broader range of candidates for fabricating electronic devices. Trithiocyanuric acid (1,3,5-triazine-2,4,6-trithiol, TTCA) provides a possible candidate. TTCA (C3N3(SH)3) can exist as a trithiol or as a trithione in which hydrogens transfer to the sulfurs so that they are present with three C=N groups within the ring. TTCA exists naturally in the trithione form but converts into a trithiol when adsorbed onto an Ag(111) where it is vertically oriented. The structure of TTCA adsorbed on Au(111) is studied here using reflection-absorption infrared spectroscopy (RAIRS) where it is found to remain as the trithione isomer, but changes orientation as the coverage increases. Scanning-tunneling microscopy (STM) reveals that TTCA oligomerizes on Au(111) to form chains and triangular structures. The influence on molecular conductivity due to the differences in the adsorbate's isomeric structure was investigated using devices comprising either silver or gold nanoparticles deposited in the gap between gold nanoelectrodes. Both devices were found to conduct when dosed with TTCA, but the devices fabricated using silver were about 13 time more conductive than those made from gold nanoparticles, consistent with the π-conjugated structure formed on silver but not on gold. This implies that oligomers form both on silver and on gold and potentially increases the range of molecule-metal combinations that might be used to fabricate molecular-electronic devices.

Molecular electronics↗
DOE OSTI2025

Light-triggered electrochemical biosensor using singlet oxygen for self-powered operation and glucose detection

This study introduces a light-activated sensing strategy that integrates photosensitization with electrochemical detection. The sensor employs Eosin Y, a photosensitizer that generates singlet oxygen ( 1 O 2 ) via type II photosensitization. Immobilized within a thin polymer matrix on a carbon working electrode, Eosin Y produces 1 O 2 , under green light (520 nm) illumination, initiating a redox process that yields a measurable current. To incorporate biosensing capabilities and enable self-powered operation, this 1 O 2 – mediated process was coupled with glucose oxidase (GOx) to construct a fully operational glucose biosensor. The addition of glucose reverses the current flow by causing GOx to compete for electrons, with the resulting current magnitude correlating with glucose concentration providing a sensitive measure of glucose. The biosensor, as proof-of-principle, demonstrated excellent performance over a range of glucose concentrations (0–73 mM), achieving a detection limit (LOD) of 2.8 mM for steady state photocurrent under oxygen-saturated conditions. This platform leverages light and 1 O 2 as stimuli for tunable, on-demand signal control, offering a novel approach for adaptive, real-time biosensing technologies.

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

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗
DOE OSTI2025

Characterizing Absolute Orientations in DNA Self-Assembly of Single Molecules

DNA self-assembly of single molecules (i.e., dyes) with deterministic orientations is a powerful approach for engineering mo-lecular excitons. However, current determination methods of the dye orientation relative to DNA do not account for the orien-tation of the dye plane, which is a missing degree of freedom needed to define absolute three-dimensional orientations. In this work, we combine fluorescence-detected linear dichroism, defocused dipole imaging, and DNA points accumulation for imaging in nanoscale topography (DNA-PAINT) super-resolution microscopy to determine the absolute three-dimensional orientations of single Cy5 dyes relative to host DNA duplexes which includes the dye plane orientation. The data revealed that the absorption and emission dipoles are perpendicular to the DNA duplex, and the mean dye plane is parallel to the DNA bases, which supports the notion that Cy5 dyes intercalate between DNA base pairs. The presented methodology will inspire the investigation of the dye plane orientation for controlling dye arrangement configurations beyond spontaneous π-stacking between dyes as well as achieving novel dye-DNA arrangements.

36 MATERIALS SCIENCE↗
DOE OSTI2024

STORM Super-Resolution Visualization of Self-Assembled γPFD Chaperone Ultrastructures in Methanocaldococcus jannaschii

Gamma-prefoldin (γPFD), a unique chaperone found in the extremely thermophilic methanogen Methanocaldococcus jannaschii, self-assembles into filaments in vitro, which so far have been observed using transmission electron microscopy and cryo-electron microscopy. Utilizing three-dimensional stochastic optical reconstruction microscopy (3D-STORM), here we achieve ~20 nm resolution by precisely locating individual fluorescent molecules, hence resolving γPFD ultrastructure both in vitro and in vivo. Through CF647 NHS ester labeling, we first demonstrate the accurate visualization of filaments and bundles with purified γPFD. Next, by implementing immunofluorescence labeling after creating a 3xFLAG-tagged γPFD strain, we successfully visualize γPFD in M. jannaschii cells. Through 3D-STORM and two-color STORM imaging with DNA, we show the widespread distribution of filamentous γPFD structures within the cell. These findings provide valuable insights into the structure and localization of γPFD, opening up possibilities for studying intriguing nanoscale components not only in archaea but also in other microorganisms.

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

Light-Modulated Self-Assembly of Synthetic Nanotubes

Artificial biomolecular polymers with the capacity to respond to stimuli are emerging as a key component to the development of living materials and synthetic cells. Here, in this work, we demonstrate artificial DNA tubular nanostructures that form in response to light in a dose-dependent manner. These nanotubes assemble from programmable DNA tile motifs that are engineered to include a UV-responsive domain so that UV irradiation activates nanotube self-assembly. We demonstrate that the nanotube formation speed can be tuned by adjusting the UV dose. We then couple the light-dependent activation of tiles with RNA transcription, making it possible to control nanotube formation via concurrent physical and biochemical stimuli. Finally, we illustrate how UV activation effectively controls nanotube assembly in confinement as a rudimentary stimulus-responsive cytoskeletal system that can achieve various conformations in a minimal synthetic cell. This study contributes new tile designs that are immediately useful to building biomolecular scaffolds with controllable dynamics in response to multiple stimuli.

DNA nanotechnology↗
DOE OSTI2024

Robust Self-Healing Adhesives Based on Dynamic Urethane Exchange Reactions

Thermoset polyurethanes (PUs) have been successfully reprocessed as covalent adaptable networks (CANs) by catalyzing carbamate exchange. Here we extend bond exchange beyond the internal network cross-links to create a dynamic urethane adhesive. Interfacing PU CANs to substrates with nucleophilic functional groups creates adhesives capable of reversible transcarbamoylation with the substrate, which has not been demonstrated previously by CAN adhesives. Two types of thermoset PU films were synthesized, one containing the green carbamate exchange catalyst Zr(tmhd)4 and the other containing no catalyst. Although otherwise identical in chemical and network properties, as indicated by FT-IR spectroscopy and dynamic mechanical thermal analysis (DMTA), the film containing catalyst showed dynamic bond exchange behavior through stress relaxation analysis. When evaluated as an adhesive, the CAN film exhibited self-healing properties and retained its adhesive strength for five cycles, which is attributed to reversible covalent bonding to the glass substrate. Furthermore, this work expands industrially relevant CANs to structural adhesives and demonstrates their potential value in an application that presently employs PUs as single-use materials.

adhesive↗
DOE OSTI2025

Self-Aligned Fluorinated-Organic Ligand for Boosting the Performance of Perovskite Solar Cells

Surface passivation is evident to be one of the most efficient approaches to achieve high efficiency with superior stability of perovskite solar cells (PeSCs). However, most previous approaches to surface passivation involve adding an additional coating process either before or after perovskite film fabrication, thereby introducing an extra processing step and significantly increasing production costs. Here, a simple yet novel one-step interfacial passivation approach was implemented by utilizing the self-aligning properties of fluorinated organic ligands (F4TmI) within a perovskite precursor solution. The inherent propensity of the ligand to spontaneously anchor onto the surface of perovskite guides the crystallization process of perovskites, thus largely enhancing the device performance and humidity stability. The optimized F4TmI-based devices achieved an efficiency of 21.1%, surpassing that of the control (19.8%). Furthermore, the device stability significantly improved after the incorporation of F4TmI, maintaining 78.9 and 95.1% of its initial efficiency after aging at 60 °C and 60% relative humidity, respectively, for 330 h.

14 SOLAR ENERGY↗
DOE OSTI2025

Self-Sensing Composites via an Embedded 3D-Printed PVDF-MoS 2 Nanosensor for Structural Health Monitoring

Carbon fiber (CF)-reinforced epoxy composites are widely used in vehicle applications, where early damage detection is crucial for reliability and safety. To address this need, we developed a self-sensing epoxy/CF composite by embedding a PVDF-MoS 2 nanosensor via an embedded 3D printing method. By harnessing the intrinsic curing kinetics of epoxy, we tailored its rheological properties to optimize the embedded printing process, enabling precise and reliable support for sensor filaments without compromising the composite’s structural and functional integrity. Through comprehensive rheological and kinetic analysis, we established a quantitative relationship among curing temperature, conversion rate, and resulting yield modulus─defining a narrow processing window essential for successful sensor integration. Specifically, we identified that an epoxy yield modulus range of 180–294 Pa and a conversion rate below 10% are critical to support the PVDF-MoS 2 filament architecture. Here, this embedded 3D printing method produces complex and multimaterial PVDF-MoS 2 sensors within an epoxy matrix with minimal deformation and reduced postprocessing, which is scalable and adaptable for industrial applications. Under cyclic loading, the embedded sensors exhibited stable signals under constant loads and increased voltage signals in response to crack formation (17–35% higher) and catastrophic failure (1 order of magnitude higher), effectively capturing structural changes in real time. This study demonstrates the potential of PVDF-MoS 2 nanocomposite sensor materials for real-time structural health monitoring in epoxy–CF composite systems, enabling early detection of defects and stress anomalies, significantly reducing the risk of unexpected failures, and enhancing structural reliability.

PVDF-MoS2 sensor↗
DOE OSTI2026

Engineering CoO x ‑Based Self-Supported Anodes for Pure-Water-Fed Anion-Exchange-Membrane Electrolysis

Commercial membrane electrolyzers rely on acidic fluorocarbon membranes and ionomers, requiring the use of expensive IrO x -based oxygen-evolution catalysts. Anion-exchange-membrane water electrolyzers (AEMWEs) operate in an alkaline environment, enabling the use of non-precious-metal catalysts. Here, we study and engineer CoO x -based catalyst-coated anodes deposited via hydrothermal synthesis directly onto porous transport layers both with and without thermal annealing. The self-supported, nanoneedle-structured Co3O4 anode, formed by annealing the as-synthesized cobalt carbonate hydroxide, Co­(CO3) x (OH) y , outperforms the baseline Co3O4 nanoparticle ink-based anode in pure-water-fed AEMWE due to the improved catalyst-layer continuity and thus number of electroactive Co species. The as-synthesized and unannealed Co­(CO3) x (OH) y , however, appears to undergo substantial conversion to a more-active CoO x (OH) y phase predominantly at the surface, with nominal Co3+ present and higher electrical conductivity, lowering the cell voltage to ∼200 mV at 1.0 A·cm–2 in pure-water-fed AEMWE compared to the conventional Co3O4 nanoparticle anodes. We analyze the differences in electrode electrochemical response between pure-water and KOH feed modes, finding distinct activation and degradation modes. The Co­(CO3) x (OH) y anode shows significant activation and slower degradation linked to the conversion to oxyhydroxide. We propose catalyst layer designs that promote both hydroxide and electron transport, alongside interfacial engineering strategies to obtain high performance while mitigating anode degradation.

anion-exchange-membrane water electrolysis↗
DOE OSTI2024

Self-Powered Circularly Polarized Light Detection Enabled by Chiral Two-Dimensional Perovskites with Mixed Chiral–Achiral Organic Cations

Direct detection of circularly polarized light (CPL) holds great promise for the development of various optical technologies. Chiral 2D organic–inorganic halide perovskites make it possible to fabricate CPL-sensitive photodetectors. However, selectively detecting left-handed circularly polarized (LCP) and right-handed circularly polarized (RCP) light remains a significant challenge. Herein, we demonstrate a greatly enhanced distinguishability of photodiode-type CPL photodetectors based on chiral 2D perovskites with mixed chiral aryl (R)-(+),(S)-(–)-α-methylbenzylammonium (R,S-MBA) and achiral alkyl n-butylammonium (nBA) cations. The (R,S-MBA 0.5 nBA 0.5 ) 2 PbI 4 perovskites exhibit a 10-fold increase in circular dichroism signals compared to (R,S-MBA) 2 PbI 4 perovskites. Here, the CPL photodetectors based on the mixed-cation perovskites exhibit self-powered capabilities with a specific detectivity of 2.45 × 10 12 Jones at a o V bias. Notably, these devices show high distinguishability (gres) factors of –0.58 and +0.54 based on (R,S-MBA 0.5 nBA 0.5 ) 2 PbI 4 perovskites, respectively, surpassing the performance of (R-MBA) 2 PbI 4 -based devices by over 3-fold and setting a record for CPL detectors based on chiral 2D n = 1 perovskites.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Self-Assembling and Pore-Forming Peptoids as Antimicrobial Biomaterials

Bacterial infections have been a serious threat to mankind throughout history. Natural antimicrobial peptides (AMPs) and their membrane-disruption mechanism have generated an immense interest in the design and development of synthetic mimetics that could overcome the intrinsic drawbacks of AMPs, such as their susceptibility to proteolytic degradation. Herein, by exploiting the self-assembly and pore-forming capabilities of sequence-defined peptoids, we discovered a new family of low molecular weight peptoid antibiotics that exhibit excellent broad-spectrum activity and high selectivity toward a panel of clinically significant Gram-positive and Gram-negative bacterial strains, including vancomycin-resistant E. faecalis (VREF), methicillin-resistant S. aureus (MRSA), methicillin-resistant S. epidermidis (MRSE), E. coli, P. aeruginosa, and K. pneumoniae. Tuning peptoid sidechain chemistry and structure enabled us to tune the efficacy of antimicrobial activity. Mechanistic studies using Transmission Electron Microscopy (TEM), bacterial membrane depolarization and lysis, and time-kill kinetics assays along with molecular dynamics simulations reveal that these peptoids kill both Gram-positive and Gram-negative bacteria through a membrane-disruption mechanism. In conclusion, these robust and biocompatible peptoid-based antibiotics can provide a valuable tool for combating the emerging drug resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Self-Assembly of Accumulated Sphingolipids into Cytotoxic Fibrils in Globoid Cell Leukodystrophy and Their Inhibition by Small Molecules In Vitro

Globoid cell leukodystrophy (GLD) is a rare hereditary inborn error of metabolism due to recessive mutations that cause loss of function of the enzyme galactosylceramidase (GALC). This results in the accumulation of the sphingolipids galactosylceramide (GalCer) and galactosylsphingosine (GalSph) in the lysosomes of neuronal cells. The accumulated GalCer and GalSph in cerebral macrophages of GLD patients are neurotoxic to oligodendrocytes and Schwann cells, leading to demyelination in the nervous system. The disease typically presents with infantile onset in the first six months of life and death by age 2. Here, we identified a supramolecular structure of GalCer and GalSph that may contribute to GLD pathology. Using biophysical assays commonly used for studying proteinaceous amyloids, e.g., amyloidspecific dyes, microscopical imaging, and a series of analytical methods (FTIR, PXRD, and SAXS), we demonstrate that both GalCer and GalSph can self-assemble in vitro into highly organized fibrils reminiscent of fibrils of amyloidogenic proteins. These fibrils exhibit significant cytotoxicity to both neuronal and oligodendroglial cells. Using an inhibitor of the GALC enzyme in cell culture to mimic the GLD pathophysiology, we could detect the accumulation of these fibrils in cells. We also observed that small molecules, which are bona fide inhibitors of proteinaceous amyloids, effectively mitigated the formation of the GalCer and GalSph fibrillar structures in vitro. Finally, the small molecule ameliorated the cytotoxic effects of the sphingolipid fibrils in SH-SY5Y cells, suggesting a potential avenue for therapeutic intervention in GLD orphan disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Accelerating Structure–Property Relationship Discovery with Multimodal Machine Learning and Self-Driving Microscopy

Microscopy combined with local spectroscopy is widely used to correlate nanoscale structure with functional properties in materials, but conventional measurements rely heavily on human-selected sampling locations and predefined targets, limiting data set diversity and the potential for discovery. Here, we present a framework that integrates autonomous microscopy with dual-novelty deep kernel learning (DN-DKL) for adaptive data acquisition and a dual variational autoencoder (VAE) for representation learning. DN-DKL actively guides the microscopy toward structurally and spectroscopically novel regions, enabling efficient collection of large spectral data sets. Dual-VAE embeds local structures and spectroscopic responses into a shared latent manifold that serves as a structure–property relationship map. We applied this framework for the investigation of halide perovskite films by using conductive atomic force microscopy. The results reveal distinct hysteresis behaviors that are linked to specific nanoscale structural motifs, including grain boundary junction points that show hysteresis under different bias conditions and asymmetric grain boundaries that suppress the charge transport. This framework establishes a general strategy that leverages the complementary strengths of self-driving microscopy, machine learning, and human expertise to accelerate scientific discovery in functional materials.

atomic force microscopy↗
DOE OSTI2024

Self‐Potential Tomography Preconditioned by Particle Swarm Optimization—Application to Monitoring Hyporheic Exchange in a Bedrock River

Abstract A self‐potential (SP) data‐inversion algorithm was developed and tested on an analytical model of electrical‐potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP‐monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock‐lined riverbed. The algorithm combined stochastic source‐localization by particle‐swarm‐optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least‐squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical‐model data to evaluate the algorithm performance. Results indicated that true parameters of single‐source models were inverted and approximated with small residual error, whereas inversion of analytical‐model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non‐uniqueness of the inverse‐model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point‐scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP‐monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Utilizing integrated neutron diffraction and elastoplastic self-consistent crystal plasticity model to quantitatively assess the strengthening mechanism in Al–12.5Ce and Al–12.5Ce–0.4Mg alloys

An integrated in-situ neutron diffraction and elastic plastic self-consistent crystal plasticity (EPSC-CP) modeling scheme is performed on a binary Al–12Ce alloy and a ternary Al–12Ce–0.4Mg alloys. Using this scheme, the constitutive parameters, i.e. elastic constants and slip system parameters of individual phases can be calibrated which can be used in microstructure-based CP models to predict materials performance. From this study, it is shown that the elastic constants of Al 11 Ce 3 intermetallics calculated from density function theory calculation in the literature are rather accurate. When applied to the EPSC-CP model, the lattice strains of both the binary and ternary alloys are correctly predicted as compared with experiments, and large lattice strain differences between Al (100) plane and Al 11 Ce 3 (010) plane are demonstrated. The slip system parameters calibrated by the scheme shows that the addition of 0.4 wt% Mg in the alloy has little influence on the critical resolved shear stress of initial dislocation glide in the Al matrix which caused plastic yield in the material. This can be explained by the very dilute Mg solute content in the Al solid solution, causing large spacing of Al–Mg lattice misfit sites and little impact on resistance of dislocation glide at initial yield. The 0.4 wt% Mg addition, on the other hand, has a large influence on the hardening term in the slip system parameters, indicating those Al–Mg misfit sites do help dislocation accumulation during the deformation. The impact of dilute Mg addition on the Al slip system parameters is also reflected in the flow behavior of the ternary alloy: little impact on the yield stress, but a large impact on working hardening and tensile strength of the materials which is consistent with the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Self-Supervised and Interpretable Anomaly Detection Using Network Transformers

Machine learning and deep neural networks (DNNs) have been proposed as a tool to identify anomalies in computer network communications. However, due the obfuscated nature of off-the-shelf machine learning models, their output often does not provide enough information to isolate the source of the anomaly to take corrective measures. In this article, we introduce the network transformer (NeT), a DNN model for anomaly detection that incorporates the graph structure of the communication network in order to improve interpretability. Further, the presented approach has the following advantages: first, enhanced interpretability by incorporating the graph structure of computer networks; second, provides a hierarchical set of features that enables analysis at different levels of granularity; second, self-supervised training that does not require labeled data. The NeT model was evaluated on a set of anomalous scenarios executed in a real industrial control system. The presented approach successfully identified the anomalies, the devices affected, and the specific connections causing the anomalies, providing a data-driven hierarchical approach to analyze the behavior of a cyber network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Effect of pattern transfer process on roughness of block copolymer patterns from directed self-assembly

Block copolymer-directed self-assembly (DSA) remains promising for improving pattern quality and reducing the stochastic variations that challenge high numerical aperture extreme ultraviolet lithography. Equally critical is refining pattern transfer methods for accurately transferring the rectified DSA features to the underlying substrate. We compare two atomic layer deposition (ALD)-based techniques: sequential infiltration synthesis (SIS) and dry liftoff, applied to polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) DSA patterns. Both methods utilize aluminum oxide hard masks, with one synthesized through infiltration into the PMMA domains and the other through conformal ALD coating. High-resolution scanning electron micrographs were analyzed to measure line edge, width, and placement roughness for both the line (PMMA) and space (PS) features. Although both methods yielded similar overall 3σ rms roughness, they differed significantly in the frequency-dependent power spectral density (PSD) profiles. SIS reduced line placement roughness at length scales associated with the polymer pitch, but increased space width roughness at low frequencies, whereas dry liftoff mimicked the frequency content of the original guiding pattern. This study underscores the importance of PSD evaluation in selecting optimal pattern transfer strategies for specific applications.

Block copolymers↗