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NASA NTRS1985

Kantian epistemology as an alternative to heroic astronomy

Theoretical and observational methods in astronomy have advanced to a point where certain of their outcomes are difficult to comprehend with the traditional categories of human knowledge. The philosophical discipline of epistemology, the theory of knowledge, is used here to address four current problems in observational astronomy, exobiology, cosmology, and quantum mechanics. The problems are united by an epistemological content which, when unrecognized, has resulted in some heroic solutions of an ad hoc nature. Kant's critical philosophy is employed because his work is consistent with basic attitudes in present-day physics and biology.

Mclaughlin, W. I.↗

DOE OSTI2020

Distonic radical anion species in cysteine oxidation processes

Oxidation of cysteine residues constitutes an important regulatory mechanism in the function of biological systems. Much of this behavior is controlled by the specific chemical properties of the thiol side-chain group, where reac-tions with reactive oxygen species take place. Herein, we in-vestigated the entire cysteine oxidation cycle Cys-SH ? Cys-SOnH (n = 1, 2, 3) using cryogenic negative ion photoelectron spectroscopy and quantum-chemical calculations. The conven-tional view on the first reversible oxidation step (n = 1) is as-sociated with sulfinate species. Yet our results indicate that an alternative option exists in the form of novel distonic radical anion •OS-CH2CH(NH2)-COO- with an unpaired electron on the thiol group and excess negative charge on the carboxylate. Higher order oxidation states (n = 2, 3) are thought to be asso-ciated with irreversible oxidative damage, and our results show that excess negative charge in those cases migrates to -SOn- group. Furthermore, these species are stable towards 1e oxidation, as opposed to the n = 1 case that undergoes intra-molecular proton transfer. The molecular level insights report-ed in this work provide direct spectroscopic evidences towards unique chemical versatility of Cys-sulfenic acid (Cys-SOH) in post-translational modifications of protein systems. This research was supported by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences (X.-B. W. and M. V.) and was performed at the EMSL, a national scientific user facility sponsored by DOE's Office of Biological and Environmental Research and located at the Pacific Northwest National Laboratory. Z. B. Q. acknowledges additional support from the National Natural Science Foundation of China (Grant No. 21873003 and 21503003) and the Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase) (Grant No. U1501501) and Super Computation of Shenzhen.

Qin, Zhengbo↗

DOE OSTI2021

Electric fields and potentials in condensed phases

The electric fields and potentials inside and at the interface of matter are relevant to many branches of physics, chemistry, and biology. Accurate quantification of these fields and/or potentials is essential to control and exploit chemical and physical transformations. Before we understand the response of matter to external fields, it is first important to understand the intrinsic interior and interfacial fields and potentials, both classically and quantum mechanically, as well as how they are probed experimentally. Here we compare and contrast, beginning with the hydrogen atom in vacuum and ending with concentrated aqueous NaCl electrolyte, both classical and quantum mechanical electric potentials and fields. Here, we make contact with experimental vibrational Stark, electrochemical, X-ray, and electron spectroscopic probes of these potentials and fields, outline relevant conceptual difficulties, and underscore the advantage of electron holography as a basis to better understand electrostatics in matter.

Kathmann, Shawn M.↗

DOE OSTI2022

Bioimaging Science Program: 2022 Principal Investigator Meetings Proceedings

The mission of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program’s Bioimaging Science Program (BSP) is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. The extended goal of dynamic imaging is to functionally connect cellular components and interdependent organisms. Information about the time and place of chemical reactions in situ can identify causal relationships between biological activators and downstream effectors. BSP held its annual PI meeting virtually February 28–March 1. Contributing investigators are convened to review progress and current state-of-the-art bioimaging research. Holding the 2022 BSP meeting as part of the broader Genomic Science Program (GSP) PI meeting allowed researchers to interact with the extended GSP community. This convergence provided a platform for networking and exchange of ideas with experts in other technologies and in target BSP application areas, helping to forge new multidisciplinary collaborations among investigators from the sister programmatic areas within BER’s Biological Systems Science Division. An important highlight of the BSP meeting was the keynote presentation by Nobel Laureate Dr. Joachim Frank on Time-Resolved Macromolecular Imaging using Cryo-EM. He discussed microfluidic mixing and fast freezing to capture nonequilibrium intermediate states during molecular binding and conformational changes. The action of molecular machines can be captured at nanometer resolution and millisecond discrimination. BSP PIs made presentations describing their research focus and progress in plenary sessions on bioimaging science and on quantum-enabled bioimaging science research projects. BSP research at universities and DOE laboratories is presented in this report. A final discussion of the BSP was organized by meeting plenary session chairs, who prepared the following Executive Summary of current BSP research, research challenges, future opportunities, and potential ideas for expanding the BSP’s impact and interactions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Coherences of Photoinduced Electron Spin Qubit Pair States in Photosystem I

Here, this publication presents the first comprehensive experimental study of electron spin coherences in photosynthetic reaction center proteins, specifically focusing on photosystem I (PSI). The ultrafast electron transfer in PSI generates spin-correlated radical pairs (SCRPs), which are entangled spin pairs formed in well-defined spin states (Bell states). Since their discovery in our group in the 1980s, SCRPs have been extensively used to enhance our understanding of structure–function relationships in photosynthetic proteins. More recently, SCRPs have been utilized as tools for quantum sensing. Electron spin decoherence poses a significant challenge in realizing practical applications of electron spin qubits, particularly the creation of quantum entanglement between multiple electron spins. This work is focused on the systematic characterization of decoherence in SCRPs of PSI. These decoherence times were measured as electron spin echo decay times, termed phase memory times (T M ), at various temperatures. Decoherence was recorded on both transient SCRP states P 700 + A 1 – and thermalized states. Our study reveals that T M exhibits minimal dependence on the biological species, biochemical treatment, and paramagnetic species. The analysis indicates that nuclear spin diffusion and instantaneous diffusion mechanisms alone cannot explain the observed decoherence. As a plausible explanation we discuss the assumption that the low-temperature dynamics of methyl groups in the protein surrounding the unpaired electron spin centers is the main factor governing the loss of the spin coherence in PSI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

A Mechanistic Understanding of Nonclassical Crystal Growth in Hydrothermally Synthesized Sodium Yttrium Fluoride Nanowires

Sodium yttrium fluoride (NaYF 4 ) is an important upconverting material with many potential uses in chemistry, materials science, and biology, which can be synthesized hydrothermally in both cubic (α) and hexagonal (β) crystallographic polymorphs. Understanding the mechanisms underlying the phase conversion between the cubic and hexagonal polymorphs is of great interest to help inform future synthetic efforts, for example in the design of atomically precise quantum materials with well-defined sizes and morphologies. In this work, we use a combination of analytical transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM), powder X-ray diffraction (XRD), in situ liquid cell TEM, atom probe tomography (APT), and extended X-ray absorption fine structure (EXAFS) measurements to show that the hexagonal NaYF 4 nanowires form through a nonclassical crystal growth mechanism involving the formation and subsequent oriented attachment of mesocrystals consisting of cubic (α) phase units. Additionally, EXAFS measurements suggest that substitutional Yb 3+ point defects within NaYF 4 are distributed evenly throughout the crystal lattice without clustering and also that they may exhibit selective substitution into one of the two possible trivalent yttrium sites in the unit cell for hydrothermally synthesized β-NaYF 4 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Scalable molecular dynamics on CPU and GPU architectures with NAMD

NAMD is a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

high-performance computing↗

DOE OSTI2023

Ultrafast Dynamics of Photosynthetic Light Harvesting: Strategies for Acclimation Across Organisms

Photosynthetic light harvesting exhibits near-unity quantum efficiency. The high efficiency is achieved through a series of energy and charge transfer steps within a network of pigment-containing proteins. Remarkably, high efficiency is conserved across many organisms despite differences in the protein structures and organization that allow each organism to respond to its own biological niche and the stressors within. In this review, we highlight recent progress toward understanding how organisms maintain optimal light-harvesting ability by acclimating to their environment. First, we review the building blocks of photosynthetic light harvesting, energy transfer, and time-resolved spectroscopic techniques. Then, we explore how three classes of photosynthetic organisms—purple bacteria, cyanobacteria, and green plants—optimize their light-harvesting apparatuses to their particular environment. Overall, research has shown that photosynthetic energy transfer is robust to changing environmental conditions, with each organism utilizing its own strategies to optimize photon capture in its particular biological niche.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2009

Complexity for Survival of Living Systems

A logical connection between the survivability of living systems and the complexity of their behavior (equivalently, mental complexity) has been established. This connection is an important intermediate result of continuing research on mathematical models that could constitute a unified representation of the evolution of both living and non-living systems. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the two most relevant being Characteristics of Dynamics of Intelligent Systems (NPO- 21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; and Self-Supervised Dynamical Systems (NPO- 30634) NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72. As used here, living systems is synonymous with active systems and intelligent systems. The quoted terms can signify artificial agents (e.g., suitably programmed computers) or natural biological systems ranging from single-cell organisms at one extreme to the whole of human society at the other extreme. One of the requirements that must be satisfied in mathematical modeling of living systems is reconciliation of evolution of life with the second law of thermodynamics. In the approach followed in this research, this reconciliation is effected by means of a model, inspired partly by quantum mechanics, in which the quantum potential is replaced with an information potential. The model captures the most fundamental property of life - the ability to evolve from disorder to order without any external interference. The model incorporates the equations of classical dynamics, including Newton s equations of motion and equations for random components caused by uncertainties in initial conditions and by Langevin forces. The equations of classical dynamics are coupled with corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces that are gradients of the information potential, which, in turn, is a function of the probability densities. The probability densities are associated with mental images both self-image and nonself images (images of external objects that can include other agents). The evolution of the probability densities represents mental dynamics. Then the interaction between the physical and metal aspects of behavior is implemented by feedback from mental to motor dynamics, as represented by the aforementioned fictitious forces. The interaction of a system with its self and nonself images affords unlimited capacity for increase of complexity. There is a biological basis for this model of mental dynamics in the discovery of mirror neurons that learn by imitation. The levels of complexity attained by use of this model match those observed in living systems. To establish a mechanism for increasing the complexity of dynamics of an active system, the model enables exploitation of a chain of reflections exemplified by questions of the form, "What do you think that I think that you think...?" Mathematically, each level of reflection is represented in the form of an attractor performing the corresponding level of abstraction with more details removed from higher levels. The model can be used to describe the behaviors, not only of biological systems, but also of ecological, social, and economics ones.

Zak, Michail↗

DOE OSTI2020

Non-thermal resistive switching in Mott insulator nanowires

Abstract Resistive switching can be achieved in a Mott insulator by applying current/voltage, which triggers an insulator-metal transition (IMT). This phenomenon is key for understanding IMT physics and developing novel memory elements and brain-inspired technology. Despite this, the roles of electric field and Joule heating in the switching process remain controversial. Using nanowires of two archetypal Mott insulators—VO 2 and V 2 O 3 we unequivocally show that a purely non-thermal electrical IMT can occur in both materials. The mechanism behind this effect is identified as field-assisted carrier generation leading to a doping driven IMT. This effect can be controlled by similar means in both VO 2 and V 2 O 3 , suggesting that the proposed mechanism is generally applicable to Mott insulators. The energy consumption associated with the non-thermal IMT is extremely low, rivaling that of state-of-the-art electronics and biological neurons. These findings pave the way towards highly energy-efficient applications of Mott insulators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Evidence of Atypical Structural Flexibility of the Active Site Surrounding of an [FeFe] Hydrogenase from Clostridium beijerinkii

[FeFe] hydrogenase from Clostridium beijerinkii (CbHydA1) is an unusual hydrogenase in that it can withstand prolonged exposure to O 2 by reversibly converting into an O 2 -protected, inactive state (Hinact). It has been indicated in the past that an atypical conformation of the “SC 367 CP” loop near the [2Fe] H portion of the six-iron active site (H-cluster) allows the Cys367 residue to adopt an “off-H + -pathway” orientation, promoting a facile transition of the cofactor to Hinact. Here, we investigated the electronic structure of the H-cluster in the oxidized state (H ox ) that directly converts to Hinact under oxidizing conditions and the related CO-inhibited state (H ox -CO). We demonstrate that both states exhibit two distinct forms in electron paramagnetic resonance (EPR) spectroscopy. The ratio between the two forms is pH-dependent but also sensitive to the buffer choice. Our IR and EPR analyses illustrate that the spectral heterogeneity is due to a perturbation of the coordination environment of the H-cluster’s [4Fe4S] H subcluster without affecting the [2Fe] H subcluster. Overall, we conclude that the observation of two spectral components per state is evidence of heterogeneity of the environment of the H-cluster likely associated with conformational mobility of the SCCP loop. Such flexibility may allow Cys367 to switch rapidly between off- and on-H + -pathway rotamers. Consequently, we believe such structural mobility may be the key to maintaining high enzymatic activity while allowing a facile transition to the O 2 -protected state.

08 HYDROGEN↗

DOE OSTI2024

Modeling prebiotic chemistries with quantum accuracy at classical costs

Molecular Dynamics (MD) simulations using classical force-fields are commonly employed in numerous scientific investigations. However, many natural processes involve bond breaking and quantum forces. This complexity is compounded by the presence of multiple competing length and timescales. For example, accurately modeling the thermodynamics and dynamics of a chemical reaction requires accounting for the concerted movements of numerous solvent molecules and ions with their own fast or slow timescales. While widely used static Density Functional Theory (DFT) calculations at 0 temperature can be beneficial for such investigations, they do not account for dynamics, and lack precision in describing the molecular environments. They particularly fail at correct, rigorous treatments of finite-temperature fluctuations, and thus generalization to experimentally relevant conditions. In PNAS Benayad et al develop a scalable, generalizable approach for designing Neural Network Potentials (NNPs) that can handle chemical reactivity in solvated systems with quantum accuracy at classical costs. Specifically, they study phosphoester bond formation and rupture, which is fundamentally relevant to the Phosphorus-Oxygen bond formation central to life, and especially for the RNA world hypothesis. The framework developed here has the potential to generalize to different chemical reactions of energy and biological relevance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Engineered chirality of one-dimensional nanowires

The origin and function of chirality in DNA, proteins, and other building blocks of life represent a central question in biology. Observations of spin polarization and magnetization associated with electron transport through chiral molecules, known collectively as the chiral induced spin selectivity effect, suggest that chirality improves electron transfer. Using reconfigurable nanoscale control over conductivity at the LaAlO 3 /SrTiO 3 interface, we create chiral electron potentials that explicitly lack mirror symmetry. Quantum transport measurements on these chiral nanowires reveal enhanced electron pairing persisting to high magnetic fields (up to 18 tesla) and oscillatory transmission resonances as functions of both magnetic field and chemical potential. We interpret these resonances as arising from an engineered axial spin-orbit interaction within the chiral region. The ability to create one-dimensional electron waveguides with this specificity creates opportunities to test, via analog quantum simulation, theories about chirality and spin-polarized electron transport in one-dimensional geometries.

Science & Technology - Other Topics↗

DOE OSTI2023

Development of $\mathrm{AMOEBA}$ Polarizable Force Field for Rare-Earth La 3+ Interaction with Bioinspired Ligands

Rare-earth metals (REMs) are crucial for many important industries, such as power generation and storage, in addition to cancer treatment and medical imaging. One promising new REM refinement approach involves mimicking the highly selective and efficient binding of REMs observed in relatively recently discovered proteins. However, realizing any such bioinspired approach requires an understanding of the biological recognition mechanisms. In this report we developed a new classical polarizable force field based on the AMOEBA framework for modeling a lanthanum ion (La 3+ ) interacting with water, acetate, and acetamide, which have been found to coordinate the ion in proteins. The parameters were derived by comparing to high-level ab initio quantum mechanical (QM) calculations that include relativistic effects. The AMOEBA model, with advanced atomic multipoles and electronic polarization, is successful in capturing both the QM distance-dependent La 3+ –ligand interaction energies and experimental hydration free energy. A new scheme for pairwise polarization damping (POLPAIR) was developed to describe the polarization energy in La 3+ interactions with both charged and neutral ligands. Simulations of La3+ in water showed water coordination numbers and ion–water distances consistent with previous experimental and theoretical findings. Water residence time analysis revealed both fast and slow kinetics in water exchange around the ion. This new model will allow investigation of fully solvated lanthanum ion–protein systems using GPU-accelerated dynamics simulations to gain insights on binding selectivity, which may be applied to the design of synthetic analogues.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Data for "Integrated Green Biorefinery for the Production of Anthocyanins, Fermentable Sugars, and High Pure Lignin from Miscanthus × giganteus "

Miscanthus x giganteus (Mxg) is a promising perennial crop for producing natural colorants, renewable fuels, and bioproducts. However, natural recalcitrance and high pretreatment cost are major barriers to their complete conversion. In this study, a green processing method has been investigated for efficient recovery of natural pigments (anthocyanins), fermentable sugars, and pure lignin from Mxg genotypes using choline chloride-based natural deep eutectic solvents (NADES) systems. Interestingly, choline chloride: lactic acid (ChCl: LA) NADES-processed biomass resulted in 67.8 ± 2.1 μg g−1 of anthocyanins from dry biomass. A maximum of 87.4%–94.1% glucose yield was achieved after enzymatic saccharification. The effective extraction of lignin with high purity with higher β-aryl ether (βO4) bonds from advanced crops is crucial for lignin valorization. Notably, highly pure lignin (≈93.4% ± 1.4%) is achieved after low-temperature NADES pretreatment while retaining lignin’s native structure. 31P nuclear magnetic resonance demonstrated that total phenolics for ChCl: LA-lignin resulted in 1.20 mmol g−1 hydroxyls. The relative monolignol composition of syringyl (S), guaiacyl (G), and p-hydroxyphenyl (H) is 19.0, 65.7, and 14.3%, respectively, as evidenced by heteronuclear single quantum coherence analysis. This study provides a novel approach for obtaining high-purity lignin for catalytic depolymerization for oligomers and bifunctional monoaromatics production and leverages current cellulosic biorefinery technologies.

biomass analytics↗

DOE OSTI2025

femto-PIXAR: a self-supervised neural network method for reconstructing femtosecond X-ray free electron laser pulses

X-ray Free Electron Lasers (X-FELs) operate in a wide range of lasing configurations for a broad variety of scientific applications at ultrafast time-scales such as structural biology, materials science, and atomic and molecular physics. Shot-by-shot characterization of the X-FEL pulses is crucial for analysis of many experiments as well as tuning the X-FEL performance. However, for the weak pulses found in advanced configurations, e.g. those needed for coherent, two-pulse studies of quantum materials, there is no current method for reliably resolving pulse profiles. Here we show that a physics-based U-net model can reconstruct the individual pulse power profiles for sub-picosecond pulse separation without the need for simulations. Using experimental data from weak X-FEL pulse pairs, we demonstrate we can learn the pulse characteristics on a shot-by-shot basis when conventional methods fail.

43 PARTICLE ACCELERATORS↗

NASA NTRS2002

Nanotube Sensors

Under this project, we explored the feasibility of utilizing carbon nanotubes in sensing applications. The grant primarily supported a graduate student, who worked on a number of aspects of the electrical properties of carbon nanotubes in collaboration with other researchers in my group. The two major research accomplishments are described below. The first accomplishment is the demonstration that solution carbon nanotube transistors functioned well in an electrolyte environment. This was important for two reasons. First, it allowed us to explore the ultimate limits of nanotube electronic performance by using the electrolyte as a highly effective gate, with a dielectric constant of approximately 80 and an effective insulator thickness of approximately 1 nm. Second, it showed that nanotubes function well under biologically relevant conditions (salty water) and therefore offer great promise as biological sensors. The second accomplishment was the demonstration that a voltage pulse applied to an AFM tip could be used to electrically cut carbon nanotubes. We also showed that a carefully applied pulse could also 'nick' a nanotube, creating a tunnel barrier without completely breaking the tube. Nicking was employed to make, for example, a quantum dot within a nanotube.

McEuen, Paul L.↗