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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Experimental and Numerical Analysis of Skin-Stiffener Separation Using a Seven-Point Bend Configuration

Skin-stiffener separation in stiffened composite panels consists of a complex interaction between multiple scales of progressive damage and failure mechanisms. This work used a superposed cohesive element method of modeling resistance curve effects that represents the structural interface of a unidirectional tape skin and a fabric stiffener. Finite element models using cohesive elements with input properties obtained from tape-to-fabric interface characterization tests were compared to experimental results of a stable skin-stiffener separation characterization test using a seven-point bend fixture. This fixture deformed the stiffened panel specimens into a buckled configuration which induced mixed-mode interlaminar stress states at the skin-stiffener interface. The advantage of this fixture was the potential for more stable damage initiation and delamination growth compared to a stringer-stiffened panel under axial compression. Use of the superposed cohesive elements showed promise, but the characterization of interface material properties as input to the cohesive elements remains a crucial component to be investigated to ensure accurate prediction of skin-stiffener separation.

Kosztowny, Cyrus J. R.↗
NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗
DOE OSTI2024

Elucidating the mechanical and thermal response of nanotwinned Ni alloys

Transformative advances in nanoscale materials synthesis, characterization and modeling are enabling the synthesis of materials with unprecedent properties and greater understanding of the nanoscale mechanisms that underpin these properties. Nanotwinned Cu alloys have received considerable attention due to their impressive balance of strength and ductility, but they have limited microstructural stability. Recent instantiation of nanotwins in sputter deposited Ni-Mo-W, and several commercial Ni-based superalloys, point to the potential development of a new class of high temperature materials with a very beneficial suite of mechanical and physical properties. The experimental study described in this report was undertaken to elucidate the nanoscale origins of the thermal and mechanical behavior of nanotwinned Ni alloys. Micropillar compression experiments have shown nanotwinned Ni 85 Mo 15-x W x alloys to possess unusually high strengths above 3.5GPa and enhanced microstructural stability. The strength of these nanotwinned alloys is determined by the abrupt formation of shear bands. This study focused on identifying the nanoscale trigger, or triggers, for shear banding in nanotwinned materials using in situ experiments and atomic-scale postmortem analysis. Contrasting and comparing the mechanical response and postmortem nanostructures of “Mo-rich” and “W-rich” nanotwinned specimens elucidated the importance of the lateral motion of easy glide defects that results in erasure of twins and local coarsening of the nanotwinned microstructure. This twin coarsening was then associated with very localized plasticity, strain softening, and shear band formation. The difference between alloys was further studied by considering the role of various material factors: stacking fault energy, coherent twin boundary spacing and flatness, grain size, and the interactions of solute atoms with twin and grain boundaries. The effect of alloy composition and sputtering power and temperature were also investigated and used to control twin spacing and geometry. Combined with atomic-scale simulations, these experiments insights should allow us to identify strategies for achieving concomitant ultrahigh strength and ductility in nanotwinned Ni alloys. In parallel but synergistic studies, our work was buoyed by collaborative state-of-the-art nanoscale orientation and strain mapping at the DOE National Center for Electron Microscopy (NCEM). For example, novel 4D-STEM techniques were used to acquire nanoscale strain maps. The extremely fine twin spacing limited our measurements of atomic-scale thermal expansion within twins, but recent results from NCEM suggest that it will soon be possible to conduct such measurements and to unravel the origins of the novel thermal expansion characteristics of nanotwinned Ni alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Integrating multi-modal remote sensing, deep learning, and attention mechanisms for yield prediction in plant breeding experiments

In both plant breeding and crop management, interpretability plays a crucial role in instilling trust in AI-driven approaches and enabling the provision of actionable insights. The primary objective of this research is to explore and evaluate the potential contributions of deep learning network architectures that employ stacked LSTM for end-of-season maize grain yield prediction. A secondary aim is to expand the capabilities of these networks by adapting them to better accommodate and leverage the multi-modality properties of remote sensing data. In this study, a multi-modal deep learning architecture that assimilates inputs from heterogeneous data streams, including high-resolution hyperspectral imagery, LiDAR point clouds, and environmental data, is proposed to forecast maize crop yields. The architecture includes attention mechanisms that assign varying levels of importance to different modalities and temporal features that, reflect the dynamics of plant growth and environmental interactions. The interpretability of the attention weights is investigated in multi-modal networks that seek to both improve predictions and attribute crop yield outcomes to genetic and environmental variables. This approach also contributes to increased interpretability of the model's predictions. The temporal attention weight distributions highlighted relevant factors and critical growth stages that contribute to the predictions. The results of this study affirm that the attention weights are consistent with recognized biological growth stages, thereby substantiating the network's capability to learn biologically interpretable features. Accuracies of the model's predictions of yield ranged from 0.82-0.93 R 2 ref in this genetics-focused study, further highlighting the potential of attention-based models. Further, this research facilitates understanding of how multi-modality remote sensing aligns with the physiological stages of maize. The proposed architecture shows promise in improving predictions and offering interpretable insights into the factors affecting maize crop yields, while demonstrating the impact of data collection by different modalities through the growing season. By identifying relevant factors and critical growth stages, the model's attention weights provide valuable information that can be used in both plant breeding and crop management. The consistency of attention weights with biological growth stages reinforces the potential of deep learning networks in agricultural applications, particularly in leveraging remote sensing data for yield prediction. To the best of our knowledge, this is the first study that investigates the use of hyperspectral and LiDAR UAV time series data for explaining/interpreting plant growth stages within deep learning networks and forecasting plot-level maize grain yield using late fusion modalities with attention mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Effect of Tungsten L-PBF Feedstock Modification on Performance in Bending

Additively manufactured tungsten is a candidate refractory material for high-temperature aerospace and nuclear fusion/fission applications. The printability of pure tungsten is challenged by cracking defects arising from the metal’s high ductile-to-brittle transition temperature and low solubility of interstitial impurities. Furthermore, the cast microstructure inherent to the laser powder bed fusion (L-PBF) process has limited strength compared to worked microstructures common in wrought tungsten. Aside from process-related techniques to mitigate defects and increase strength (e.g., heated build chambers, multi-laser systems, low oxygen environmental control, etc.), micro-alloying additions can positively influence tungsten printability. In this work, pure tungsten L-PBF feedstock was modified with 1 wt% additions of ceramic compound nano-powders. Wrought and printed bars were evaluated in four-point bending. Flexural strength and fractography were primary means of comparison to assess the effect of the feedstock modification on printed tungsten mechanical performance.

Tungsten-based alloys↗
NASA NTRS1981

Spacelab 2 pointed experiments

Thirteen experiments have been selected for development for the multidisciplinary Spacelab 2 mission. They include three solar physics instruments and an atmospheric physics investigation mounted on the Instrument Pointing System (IPS), a two-axis gimballed X-ray experiment, an infrared telescope scanned about a single axis, and several fixed instruments. Integration of the IPS with its instruments and integration of the entire experiment complement into a flight mission has been a most demanding, complex task which has evolved as the Shuttle carrier vehicle, Spacelab, the IPS, and the experiments have matured. Mechanical interactions between all of these elements, thermal design restrictions, Shuttle and IPS operational constraints, mission duration, pointed instrument collision avoidance, and many other factors have impacted the scientific and engineering objectives of all of the experiments. Not all of the impacts have been adverse, however, and four types of joint science between previously unrelated experiments have so far been generated. This paper summarizes the current state of mission planning, particularly as it relates to the achievement of the scientific and engineering objectives of the pointed experiments. It discusses some of the compromises that have been made to satisfy the diverse requirements and capabilities of the hardware, the planning to date for joint solar observations from the IPS, and some system problems which remain.

Urban, E. W.↗
DOE OSTI2025

Challenges in Continuous In-Field Critical Current Testing of High-Temperature Superconducting Tapes: Thermal and Mechanical Perspectives

High-temperature superconductors (HTS) are essential for ultra-high-field applications requiring exceptional current-carrying capacity under extreme conditions. However, systematic characterization of critical current in long-length conductors remains challenging due to complex thermal, electromag netic, and mechanical interactions during continuous testing. This study reports the development of a continuous in-field magnetization testing system for position-dependent critical current measurement in HTS tapes at 20 K under 7.5 T fields applied normal to the tape plane, enabling identification of performance-limiting regions that could compromise magnet stability. Here, the system addresses two fundamental challenges inherent to cryogenic reel to-reel testing. First, thermal management requires continuous cooling of a moving conductor to 20 K, achieved through liquid nitrogen precooling combined with a 100 W@20 K Gifford McMahon cryocooler. Second, screening currents in high fields generate Lorentz forces that induce twisting, bowing, and potential delamination. To mitigate these risks, we propose mechanical reinforcement and active current density suppression strategies. Numerical simulations using the stream function formulation reveal four primary failure modes: frictional heating at guide interfaces, unstable equilibria causing deformation, transverse current-induced stresses at guide transitions, and unsupported forces in vertical spans. Our mitigation strategies include PTFE coated guides to minimize friction, spring-loaded stabilization mechanisms to maintain tape alignment, controlled pre-heating using the liquid nitrogen thermal jacket to suppress critical current at stress points, and optimized guide positioning to minimize force accumulation. The experimental system is nearing completion, with testing planned to commence within two months. Preliminary validation at 65 K under 0.5 T demonstrates strong correlation between simulation-predicted mechanical instabilities and observed critical current variations during conductor tran sitions through the measurement region. These findings establish a robust foundation for quality assurance protocols essential to next-generation superconducting magnet applications.

Chen, Siwei [Princeton Plasma Physics Laboratory (↗
NASA NTRS2014

Insights on TTL Dehydration Mechanisms from Microphysical Modelling of Aircraft Observations

The Tropical Tropopause Layer (TTL), a transition layer between the upper troposphere and lower stratosphere in the tropics, serves as the entryway of various trace gases into the stratosphere. Of particular interest is the transport of water vapor through the TTL, as WV is an important greenhouse gas and also plays a significant role in stratospheric chemistry by affecting polar stratospheric cloud formation and the ozone budget. While the dominant control of stratospheric water vapor by tropical cold point temperatures via the "freeze-drying" process is generally well understood, the details of the TTL dehydration mechanisms, including the relative roles of deep convection, atmospheric waves and cloud microphysical processes, remain an active area of research. The dynamical and microphysical processes that influence TTL water vapor concentrations are investigated in simulations of cloud formation and dehydration along air parcel trajectories. We first confirm the validity of our Lagrangian models in a case study involving measurements from the Airborne Tropical TRopopause EXperiment (ATTREX) flights over the central and eastern tropical Pacific in Oct-Nov 2011 and Jan-Feb 2013. ERA-Interim winds and seasonal mean heating rates from Yang et al. (2010) are used to advance parcels back in time from the flight tracks, and time-varying vertical profiles of water vapor along the diabatic trajectories are calculated in a one-dimensional cloud model as in Jensen and Pfister (2004) but with more reliable temperature field, wave and convection schemes. The simulated water vapor profiles demonstrate a significant improvement over estimates based on the Lagrangian Dry Point, agreeing well with aircraft observations when the effects of cloud microphysics, subgrid-scale gravity waves and convection are included. Following this approach, we examine the dynamical and microphysical control of TTL water vapor in the 30ºS-30ºN latitudinal belt and elucidate the dominant processes in the winter and summer seasons. Implications of the TTL dehydration processes for the regulation of global stratospheric humidity will be discussed.

stratosphere↗
NASA NTRS2009

Software Health Management: A Short Review of Challenges and Existing Techniques

Modern spacecraft (as well as most other complex mechanisms like aircraft, automobiles, and chemical plants) rely more and more on software, to a point where software failures have caused severe accidents and loss of missions. Software failures during a manned mission can cause loss of life, so there are severe requirements to make the software as safe and reliable as possible. Typically, verification and validation (V&V) has the task of making sure that all software errors are found before the software is deployed and that it always conforms to the requirements. Experience, however, shows that this gold standard of error-free software cannot be reached in practice. Even if the software alone is free of glitches, its interoperation with the hardware (e.g., with sensors or actuators) can cause problems. Unexpected operational conditions or changes in the environment may ultimately cause a software system to fail. Is there a way to surmount this problem? In most modern aircraft and many automobiles, hardware such as central electrical, mechanical, and hydraulic components are monitored by IVHM (Integrated Vehicle Health Management) systems. These systems can recognize, isolate, and identify faults and failures, both those that already occurred as well as imminent ones. With the help of diagnostics and prognostics, appropriate mitigation strategies can be selected (replacement or repair, switch to redundant systems, etc.). In this short paper, we discuss some challenges and promising techniques for software health management (SWHM). In particular, we identify unique challenges for preventing software failure in systems which involve both software and hardware components. We then present our classifications of techniques related to SWHM. These classifications are performed based on dimensions of interest to both developers and users of the techniques, and hopefully provide a map for dealing with software faults and failures.

Pipatsrisawat, Knot↗
NASA NTRS2013

Heteroclinic, Homoclinic Connections Between the Sun-Earth Triangular Points and Quasi-Satellite Orbits for Solar Observations

Investigation of new orbit geometries exhibits a very attractive behavior for a spacecraft to monitor space weather coming from the Sun. Several orbit transfer mechanisms are analyzed as potential alternatives to monitor solar activity such as a sub-solar orbit or quasi-satellite orbit and short and long heteroclinic and homoclinic connections between the triangular points L(sub 4) and L(sub 5) and the collinear point L(sub 3) of the Circular Restricted Three-Body Problem (CRTBP) in the Sun-Earth system.

Moon↗
NASA NTRS1989

Unsteady stagnation-point heat transfer during passage of a concentrated vortex

The unsteady boundary layer due to a single rectilinear vortex filament approaching a 2-D stagnation point is investigated. Assuming the vortex remains far from the surface, incompressible potential flow theory is used to determine the time dependent inviscid flow field. The unsteady boundary layer equations are solved by an alternating-direction-implicit finite-difference method. Two mechanisms which cause fluctuations in heat transfer are the unsteady velocity field in the boundary layer and secondly, the unsteady total temperature at the edge of the boundary layer. The relative importance of these mechanisms is dependent upon the total temperature fluctuations relative to the imposed temperature difference. As a vortex approaches a stagnation point it may be forced to one side of the stagnation line or the other, depending on its initial position. Results are presented for both of these cases.

Rigby, David L.↗
NASA NTRS2024

Bending Performance of Tungsten Printed Via Laser Powder Bed Fusion With Ceramic Dispersion Modified Powder Feedstock

Additively manufactured tungsten is a candidate refractory material for high-temperature aerospace and nuclear fusion/fission applications. The printability of pure tungsten is challenged by cracking defects arising from the metal’s high brittle-to-ductile transition temperature and low solubility of interstitial impurities. Furthermore, the cast microstructure inherent to the laser powder bed fusion (L-PBF) process has limited strength compared to worked microstructures common in wrought tungsten. Aside from process-related techniques to mitigate defects and increase strength (e.g., heated build chambers, multi-laser systems, low oxygen environmental control, etc.), micro-alloying additions can positively influence tungsten printability and strength. In this work, pure tungsten L-PBF feedstock was modified with 1 wt% additions of ceramic compound nano-powders. Wrought and printed bars were evaluated in four-point bending. Flexural strength and fractography were primary means of comparison to assess the effect of the feedstock modification on printed tungsten mechanical performance.

Additive Manufacturing↗
NASA NTRS1977

An experimental investigation of the trailing edge noise mechanism

An experimental investigation has been conducted to understand the physical mechanism of noise generation from a turbulent wall jet discharging over a flat plate and interacting with its sharp trailing edge. An aspect ratio 10 rectangular nozzle was used to provide the wall jet. Measurements made consist of farfield noise, surface pressure fluctuations, turbulent velocity fluctuations, and two-point space-time cross-correlations among these quantities. Results are presented which suggest strongly that the generation mechanism is the interaction of the convecting large scale quasi-orderly disturbance in the upper free shear layer of the wall jet with the trailing edge. The interaction also excites large scale strong vortical motion in the trailing edge wake. The dominant part of the sound field is highly coherent and in phase opposition across the trailing edge.

Yu, J. C.↗
NASA NTRS1981

Recent progress in exobiology and planetary biology

Recent work in the fields of exobiology, the study of the possible characteristics of extraterrestrial life, and planetary biology, the study of life forms as a function of planetary conditions, is reviewed. Searches conducted for life on Mars by the Viking Landers and on Titan by Voyager 1 are considered, and the origin of life on earth is considered in relation to the question of the inorganic trace elements in living systems that are required for life. The question of the origin of terrestrial life from spores carried through the interstellar medium is examined, and the unlikelihood of the survival of such spores except within meteorites or dust particles is pointed out. Studies of organic molecules present in the interstellar medium are indicated as evidence that the conditions necessary for the formation of life can exist in various locations throughout the universe. Investigations of the molecular evolution of life on earth and of life under extreme conditions of heat, cold, drought and ultraviolet radiation, and of the organic compounds found in meteorites and comets are also discussed. The importance of a mechanism of heredity, such as terrestrial DNA, to the evolution of terrestrial and possible extraterrestrial life is pointed out.

Jukes, T. H.↗
NASA NTRS2003

Mechanical injury and repair of cells

OBJECTIVE: To concisely review the field of cell plasma membrane disruption (torn cell surface) and repair. MAIN POINTS: Plasma membrane disruption is a common form of cell injury under physiologic conditions, after trauma, in certain muscular dystrophies, and during certain forms of clinical intervention. Rapid repair of a disruption is essential to cell survival and involves a complex and active cell response that includes membrane fusion and cytoskeletal activation. Tissues, such as cardiac and skeletal muscle, adapt to a disruption injury by hypertrophying. Cells adapt by increasing the efficiency of their resealing response. CONCLUSION: Plasma membrane disruption is an important cellular event in both health and disease. The disruption repair mechanism is now well understood at the cellular level, but much remains to be learned at the molecular level. Cell and tissue level adaptational responses to the disruption either prevent its further occurrence or facilitate future repairs. Therapeutically useful drugs might result if, using this accumulating knowledge, chemical agents can be developed that can enhance repair or adaptive responses.

Review, Tutorial↗
DOE OSTI2025

Geometry-aware framework for deep energy method: An application to structural mechanics with hyperelastic materials

Here, in this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries. As the weak form of the physical system equation (or the energy-based approach) has demonstrated clear advantages compared to the strong form for solving solid mechanics problems, GADEM employs the weak form and aims to infer the solution on multiple shapes of geometries. Integrating a geometry-aware framework into an energy-based method results in an effective physics-informed deep learning model in terms of accuracy and computational cost. Different ways to represent the geometric information and to encode the geometric latent vectors are investigated in this work. We introduce a loss function of GADEM which is minimized based on the potential energy of all considered geometries. An adaptive learning method is also employed for the sampling of collocation points to enhance the performance of GADEM. We present some applications of GADEM to solve solid mechanics problems, including a loading simulation of a toy tire involving contact mechanics and large deformation hyperelasticity. The numerical results of this work demonstrate the remarkable capability of GADEM to infer the solution on various and new shapes of geometries using only one trained model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Selective mass scaling for single-layer thick shell elements in DYNA3D

Hexahedral elements can be adapted to model thin and moderately thick structures by neglecting the coupling of through-thickness stress, resulting in a fully three-dimensional, but simplified, state of stress. These specialized elements, often referred to as “thick” or “solid” shells, are generally employed to model thin-walled structures using continuum mechanics-based material models. In explicit dynamics simulations, where computational speed is important, these elements are integrated with a single quadrature point and a set of anti-hourglassing (stabilizing) forces. Thick shells, by definition, have a thickness dimension smaller than their in-plane dimensions, and this small thickness often determines the stable time step size in simulations, despite the mechanics being approximated. To alleviate this limitation while retaining the relevant dynamics of thin-walled structures, selective mass scaling (SMS), or selective mass “augmentation,” has been proposed in the literature. In this technical report, we explore the application of SMS to single-layer thick shells in the simulation software DYNA3D.

42 ENGINEERING↗
NASA NTRS1995

Interfacial Effects on the Thermal and Mechanical Properties of Graphite/Copper Composites

Graphite surfaces are not wet by pure copper. This lack of wetting has been responsible for a debonding phenomenon that has been found in continuous graphite fiber reinforced copper matrix composites subjected to elevated temperatures. By suitably alloying copper, its ability to wet graphite surfaces can be enhanced. Information obtained during sessile drop testing has led to the development of a copper-chromium alloy that suitably wets graphite. Unidirectionally reinforced graphite/copper composites have been fabricated using a pressure infiltration casting procedure. P100 pitch-based fibers have been used to reinforce copper and copper-chromium alloys. X-ray radiography and optical microscopy have been used to assess the fiber distribution in the cast composites. Scanning electron microscopy and Auger electron spectroscopy analyses were conducted to study the distribution and continuity of the chromium carbide reaction phase that forms at the fiber/matrix interface in the alloyed matrix composites. The effects of the chromium in the copper matrix on the mechanical and thermal properties of P100Gr/Cu composites have been evaluated through tensile testing, three-point bend testing, thermal cycling and thermal conductivity calculations. The addition of chromium has resulted in an increased shear modulus and essentially zero thermal expansion in the P100Gr/Cu-xCr composites through enhanced fiber/matrix bonding. The composites have longitudinal tensile strengths in excess of 700 MPa with elastic moduli of 393 GPa. After 100 hr at 760 deg C 84 percent of the as-cast strength is retained in the alloyed matrix composites. The elastic moduli are unchanged by the thermal exposure. It has been found that problems with spreading of the fiber tows strongly affect the long transverse tensile properties and the short transverse thermal conductivity of the P100Gr/Cu-xCr composites. The long transverse tensile strength is limited by rows of touching fibers which are paths of easy crack propagation under low tensile loads. The short transverse thermal conductivity is dictated by the fiber/matrix interface. Conduction across this interface has been estimated to be two orders of magnitude lower than that across the composite. This is due to the mechanical, and not chemical, nature of Gr/Cu bond.

Devincent, Sandra Marie↗