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NASA NTRS2000

The ISS EXPRESS Rack: An Innovative Approach of Rapid Integration

The EXpedite the PRocessing of Experiments to Space Station or EXPRESS Rack System, was developed to provide Space Station accommodations for small, subrack payloads. The EXPRESS Rack accepts Space Shuttle middeck locker type payloads and International Subrack Interface Standard (ISIS) Drawer payloads, allowing previously flown payloads an opportunity to transition to the International Space Station. The EXPRESS Rack provides power, data, command and control, video, water cooling, air cooling, vacuum exhaust, and Nitrogen supply to payloads. The EXPRESS Rack system also includes transportation racks to transport payloads to and from the Space Station, Suitcase Simulators to allow a payload developer to verify power and data interfaces at the development site, Functional Checkout Units to allow Payload checkout at KSC prior to launch, and trainer racks for the astronauts to learn how to operate the EXPRESS Racks prior to flight. Standard hardware and software interfaces provided by the EXPRESS Rack simplify the analytical and physical integration processes, and facilitates simpler ISS payload development. The EXPRESS Rack has also formed the basis for the U.S. Life Sciences payload racks and the Window Observational Research Facility on Space Station.

Sledd, Annette M.↗

NASA NTRS1999

EXPRESS Rack Overview

Sledd, Annette M.↗

NASA NTRS1999

Drop Breakup in Fixed Bed Flows as Model Stochastic Flow Fields

We examine drop breakup in a class of stochastic flow fields as a model for the flow through fixed fiber beds and to elucidate the general mechanisms whereby drops breakup in disordered, Lagrangian unsteady flows. Our study consists of two parallel streams of investigation. First, large scale numerical simulations of drop breakup in a class of anisotropic Gaussian fields will be presented. These fields are generated spectrally and have been shown in a previous publication to be exact representations of the flow in a dilute disordered bed of fibers if close interactions between the fibers and the drops are dynamically unimportant. In these simulations the drop shape is represented by second and third order small deformation theories which have been shown to be excellent for the prediction of drop breakup in steady strong flows. We show via these simulations that the mechanisms of drop breakup in these flows are quite different than in steady flows. The predominant mechanism of breakup appears to be very short lived twist breakups. Moreover, the occurrence of breakup events is poorly predicted by either the strength of the local flow in which the drop finds itself at breakup, or the degree of deformation that the drop achieves prior to breakup. It is suggested that a correlation function of both is necessary to be predictive of breakup events. In the second part of our research experiments are presented where the drop deformation and breakup in PDMS/polyisobutylene emulsions is considered. We consider very dilute emulsions such that coalescence is unimportant. The flows considered are simple shear and the flow through fixed fiber beds. Turbidity, small angle light scattering, dichroism and microscopy are used to interrogate the drop deformation process in both flows. It is demonstrated that breakup at very low capillary numbers occurs in both flows but larger drop deformation occurs in the fixed bed flow. Moreover, it is witnessed that breakup in the bed occurs continuously during flow and apparently with uniform probability through the bed length. The drop deformations witnessed in our experiments are larger than those predicted by the numerical simulations, and future plans to investigate these differences are discussed.

Shaqfeh, Eric S. G.↗

NASA NTRS1998

Automatic Molecular Design using Evolutionary Techniques

Molecular nanotechnology is the precise, three-dimensional control of materials and devices at the atomic scale. An important part of nanotechnology is the design of molecules for specific purposes. This paper describes early results using genetic software techniques to automatically design molecules under the control of a fitness function. The fitness function must be capable of determining which of two arbitrary molecules is better for a specific task. The software begins by generating a population of random molecules. The population is then evolved towards greater fitness by randomly combining parts of the better individuals to create new molecules. These new molecules then replace some of the worst molecules in the population. The unique aspect of our approach is that we apply genetic crossover to molecules represented by graphs, i.e., sets of atoms and the bonds that connect them. We present evidence suggesting that crossover alone, operating on graphs, can evolve any possible molecule given an appropriate fitness function and a population containing both rings and chains. Prior work evolved strings or trees that were subsequently processed to generate molecular graphs. In principle, genetic graph software should be able to evolve other graph representable systems such as circuits, transportation networks, metabolic pathways, computer networks, etc.

Globus, Al↗

NASA NTRS1993

Determination of the Excess Length-of-Day Since 1630

The Kalman Earth Orientation Filter (KEOF) is used at JPL to combine independent observations of the Earth's rotation parameters, producing smoothed, interpolated estimates of polar motion (PM) and UT1-TAI, as well as estimates of their excitation functions such as the length-of-day (lod). Prior to their combination, adjustments to the data sets are made in order to place them within a common reference frame. Recently, a number of lod data sets have been determined at JPL by combining the observations summarized in Table 1. The resulting lod data sets, summarized in Table 2, span different time intervals depending upon the particular subset of observations being combined, with the longest series, spanning 1630-1990, being obtained by combining all of the observations. The determination of these lod data sets and their comparison with series of climate indicators such as the Southern Oscillation Index will be discussed.

Gross, R. S.↗

NASA NTRS2016

3D Printing in Zero G Technology Demonstration Mission: Summary of On-Orbit Operations, Material Testing, and Future Work

Human space exploration to date has been limited to low Earth orbit and the moon. The International Space Station (ISS), an orbiting laboratory 200 miles above the earth, provides a unique and incredible opportunity for researchers to prove out the technologies that will enable humans to safely live and work in space for longer periods of time and venture farther into the solar system. The ability to manufacture parts in-space rather than launch them from earth represents a fundamental shift in the current risk and logistics paradigm for human spaceflight. In particularly, additive manufacturing (or 3D printing) techniques can potentially be deployed in the space environment to enhance crew safety (by providing an on-demand part replacement capability) and decrease launch mass by reducing the number of spare components that must be launched for missions where cargo resupply is not a near-term option. In September 2014, NASA launched the 3D Printing in Zero G technology demonstration mission to the ISS to explore the potential of additive manufacturing for in-space applications and demonstrate the capability to manufacture parts and tools on-orbit. The printer for this mission was designed and operated by the company Made In Space under a NASA SBIR (Small Business Innovation Research) phase III contract. The overarching objectives of the 3D print mission were to use ISS as a testbed to further maturation of enhancing technologies needed for long duration human exploration missions, introduce new materials and methods to fabricate structure in space, enable cost-effective manufacturing for structures and mechanisms made in low-unit production, and enable physical components to be manufactured in space on long duration missions if necessary. The 3D print unit for fused deposition modeling (FDM) of acrylonitrile butadiene styrene (ABS) was integrated into the ISS Microgravity Science Glovebox (MSG) in November 2014 and phase I printing operations took place from November through December of that year. Phase I flight operations yielded 14 unique parts (21 total specimens) that could be directly compared against ground-based prints of identical geometry manufactured using the printer prior to its launch to ISS. The 3DP unit functioned safely and produced specimens necessary to advance the understanding of the critical design and operational parameters for the FDM process as affected by the microgravity environment. From the standpoint of operations, 3DP demonstrated the ability to remove parts from the build-tray on-orbit, teleoperate the printer from the ground, perform critical maintenance functions within defined human factors limits, produce a functional tool that could be evaluated for form/fit/function, and uplink a new part file from the ground and produce it on the printer. The flight parts arrived at NASA Marshall Space Flight Center in Huntsville, Alabama in April 2015, where they underwent months of testing in the materials and processes laboratory. Ground and flight prints completed the following phases of testing: photographic/visual inspection, mass and density evaluation, structured light scanning, XRay and CT, mechanical testing, optical microscopy, scanning electron microscopy, and chemical analysis. This presentation will discuss the results of this testing as well as phase II operations for the printer, which took place in June and July of 2016. Lessons learned from the tech demo and their impacts on the design and development of the second generation 3D printer for ISS, the Additive Manufacturing Facility (AMF) by Made In Space will also be presented. In addition, progress in other elements of NASA's In Space Manufacturing (ISM) initiative such as the on-demand ISM utilization catalog, in-space Recycler ISS Technology Demonstration development, launch packaging recycling, in-space printable electronics, development of higher strength polymeric materials for 3D printing and Additive Construction by Mobile Emplacement (ACME) will also be addressed.

Prater, Tracie↗

NASA NTRS2016

The Zero Boil-Off Tank Experiment Ground Testing and Verification of Fluid and Thermal Performance

The Zero Boil-Off Technology (ZBOT) Experiment involves performing a small scale International Space Station (ISS) experiment to study tank pressurization and pressure control in microgravity. The ZBOT experiment consists of a vacuum jacketed test tank filled with an inert fluorocarbon simulant liquid. Heaters and thermo-electric coolers are used in conjunction with an axial jet mixer flow loop to study a range of thermal conditions within the tank. The objective is to provide a high quality database of low gravity fluid motions and thermal transients which will be used to validate Computational Fluid Dynamic (CFD) modeling. This CFD can then be used in turn to predict behavior in larger systems with cryogens. This paper will discuss the work that has been done to demonstrate that the ZBOT experiment is capable of performing the functions required to produce a meaningful and accurate results, prior to its launch to the International Space Station. Main systems discussed are expected to include the thermal control system, the optical imaging system, and the tank filling system.This work is sponsored by NASAs Human Exploration Mission Directorates Physical Sciences Research program.

Fluid management↗

NASA NTRS2018

Geostationary Lightning Mapper On-Orbit Sources of False Events

The first Geostationary Lightning Mapper (GLM) was launched aboard the GOES-R Spacecraft (now GOES-East) on November 19, 2016 and is now fully operational. GLM uses a high-speed camera and onboard video processing to detect the optical emission of lightning for the full disk observed from the geostationary orbit. During the Post Launch Test period the instrument and ground processing algorithms (GPAs) were tuned to optimize the tradeoff between detection efficiency and false event rate. False events, those not due to lightning, arise from a variety of sources. A primary function of the GPAs is to remove false events prior to assembling events into groups and flashes for use by weather forecasters and scientists. Effective discrimination of false events depends on understanding the phenomenology of the various sources of false events.

GOES-R↗

NASA NTRS2019

A NICER view of PSR J0030+0451: Implications for the Dense Matter Equation of State

Both the mass and radius of the millisecond pulsar PSRJ0030+0451 have been inferred via pulse-profile modeling of X-ray data obtained by NASA’s Neutron Star Interior Composition Explorer (NICER) mission. In this Letter we study the implications of the mass–radius inference reported for this source by Riley et al. for the dense matter equation of state (EoS), in the context of prior information from nuclear physics at low densities. Using a Bayesian framework we infer central densities and EoS properties for two choices of high-density extensions: a piecewise-polytropic model and a model based on assumptions of the speed of sound in dense matter. Around nuclear saturation density these extensions are matched to an EoS uncertainty band obtained from calculations based on chiral effective field theory interactions, which provide a realistic description of atomic nuclei as well as empirical nuclear matter properties within uncertainties. We further constrain EoS expectations with input from the current highest measured pulsar mass; together, these constraints offer a narrow Bayesian prior informed by theory as well as laboratory and astrophysical measurements. The NICER mass–radius likelihood function derived by Riley et al. using pulse-profile modeling is consistent with the highest-density region of this prior. The present relatively large uncertainties on mass and radius for PSR J0030+0451 offer, however, only a weak posterior information gain over the prior. We explore the sensitivity to the inferred geometry of the heated regions that give rise to the pulsed emission, and find a small increase in posterior gain for an alternative (but less preferred) model. Lastly, we investigate the hypothetical scenario of increasing the NICER exposure time for PSRJ0030+0451.

G Raaijmakers↗

NASA NTRS2008

Vision System Measures Motions of Robot and External Objects

A prototype of an advanced robotic vision system both (1) measures its own motion with respect to a stationary background and (2) detects other moving objects and estimates their motions, all by use of visual cues. Like some prior robotic and other optoelectronic vision systems, this system is based partly on concepts of optical flow and visual odometry. Whereas prior optoelectronic visual-odometry systems have been limited to frame rates of no more than 1 Hz, a visual-odometry subsystem that is part of this system operates at a frame rate of 60 to 200 Hz, given optical-flow estimates. The overall system operates at an effective frame rate of 12 Hz. Moreover, unlike prior machine-vision systems for detecting motions of external objects, this system need not remain stationary: it can detect such motions while it is moving (even vibrating). The system includes a stereoscopic pair of cameras mounted on a moving robot. The outputs of the cameras are digitized, then processed to extract positions and velocities. The initial image-data-processing functions of this system are the same as those of some prior systems: Stereoscopy is used to compute three-dimensional (3D) positions for all pixels in the camera images. For each pixel of each image, optical flow between successive image frames is used to compute the two-dimensional (2D) apparent relative translational motion of the point transverse to the line of sight of the camera. The challenge in designing this system was to provide for utilization of the 3D information from stereoscopy in conjunction with the 2D information from optical flow to distinguish between motion of the camera pair and motions of external objects, compute the motion of the camera pair in all six degrees of translational and rotational freedom, and robustly estimate the motions of external objects, all in real time. To meet this challenge, the system is designed to perform the following image-data-processing functions: The visual-odometry subsystem (the subsystem that estimates the motion of the camera pair relative to the stationary background) utilizes the 3D information from stereoscopy and the 2D information from optical flow. It computes the relationship between the 3D and 2D motions and uses a least-mean-squares technique to estimate motion parameters. The least-mean-squares technique is suitable for real-time implementation when the number of external-moving-object pixels is smaller than the number of stationary-background pixels.

Talukder, Ashit↗

NASA NTRS2001

Biomaterials and bone mechanotransduction

Bone is an extremely complex tissue that provides many essential functions in the body. Bone tissue engineering holds great promise in providing strategies that will result in complete regeneration of bone and restoration of its function. Currently, such strategies include the transplantation of highly porous scaffolds seeded with cells. Prior to transplantation the seeded cells are cultured in vitro in order for the cells to proliferate, differentiate and generate extracellular matrix. Factors that can affect cellular function include the cell-biomaterial interaction, as well as the biochemical and the mechanical environment. To optimize culture conditions, good understanding of these parameters is necessary. The new developments in bone biology, bone cell mechanotransduction, and cell-surface interactions are reviewed here to demonstrate that bone mechanotransduction is strongly influenced by the biomaterial properties.

Review↗

DOE OSTI2023

Scalable Bayesian optimization with randomized prior networks

Several fundamental problems in science and engineering consist of global optimization tasks involving unknown high-dimensional (black-box) functions that map a set of controllable variables to the outcomes of an expensive experiment. Bayesian Optimization (BO) techniques are known to be effective in tackling global optimization problems using a relatively small number objective function evaluations, but their performance suffers when dealing with high-dimensional outputs. To overcome the major challenge of dimensionality, here we propose a deep learning framework for BO and sequential decision making based on bootstrapped ensembles of neural architectures with randomized priors. Using appropriate architecture choices, we show that the proposed framework can approximate functional relationships between design variables and quantities of interest, even in cases where the latter take values in high-dimensional vector spaces or even infinite-dimensional function spaces. In the context of BO, we augmented the proposed probabilistic surrogates with re-parameterized Monte Carlo approximations of multiple-point (parallel) acquisition functions, as well as methodological extensions for accommodating black-box constraints and multi-fidelity information sources. We test the proposed framework against state-of-the-art methods for BO and demonstrate superior performance across several challenging tasks with high-dimensional outputs, including a constrained multi-fidelity optimization task involving shape optimization of rotor blades in turbo-machinery.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Data Analytics Applied to Coal Fired Boilers for Detecting Leaks

Data analytics were used to detect boiler leaks from five different coal-fired boilers including both subcritical and supercritical systems. Discriminant functions were developed that detected leaks up to two weeks prior to forced plant shutdowns for repairs. The leaks were identified to occur at different sections of the boiler for each plant, including waterwalls, economizer and superheater using conventional process measurement data. Leaking conditions were detected with a high degree of confidence (&NestedLessLess; 1% misclassified observations) and were able to distinguish normal operations from those time periods with steam leaks even while operating the power plants in power cycling mode.Multivariable statistical analyses, including Principal Component (PCA), cluster, and Fischer Discriminant Analysis (FDA) were used to characterize the leak occurrence. Normal and operational states with steam leaks were provided in the original process datasets. These datasets were split into two different groups for training and validation purposes. The data were sorted chronologically, and every third observation was assigned to training the Discriminant Function Model (DFM) while the rest were reserved for validation. PCA was used to reduce dimensionality of the original datasets. Canonical and FDA analyses were used to investigate the relationship between process variables. The outcome of the analyses revealed that nearly 35,000 observations were classified correctly; less than 0.05% of total observations were misclassified to be leaking, i.e. both false positives and false negatives.

Indrawan, Natarianto↗

NASA NTRS2009

G(sup 4)FET Implementations of Some Logic Circuits

Some logic circuits have been built and demonstrated to work substantially as intended, all as part of a continuing effort to exploit the high degrees of design flexibility and functionality of the electronic devices known as G(sup 4)FETs and described below. These logic circuits are intended to serve as prototypes of more complex advanced programmable-logicdevice-type integrated circuits, including field-programmable gate arrays (FPGAs). In comparison with prior FPGAs, these advanced FPGAs could be much more efficient because the functionality of G(sup 4)FETs is such that fewer discrete components are needed to perform a given logic function in G(sup 4)FET circuitry than are needed perform the same logic function in conventional transistor-based circuitry. The underlying concept of using G(sup 4)FETs as building blocks of programmable logic circuitry was also described, from a different perspective, in G(sup 4)FETs as Universal and Programmable Logic Gates (NPO-41698), NASA Tech Briefs, Vol. 31, No. 7 (July 2007), page 44. A G(sup 4)FET can be characterized as an accumulation-mode silicon-on-insulator (SOI) metal oxide/semiconductor field-effect transistor (MOSFET) featuring two junction field-effect transistor (JFET) gates. The structure of a G(sup 4)FET (see Figure 1) is the same as that of a p-channel inversion-mode SOI MOSFET with two body contacts on each side of the channel. The top gate (G1), the substrate emulating a back gate (G2), and the junction gates (JG1 and JG2) can be biased independently of each other and, hence, each can be used to independently control some aspects of the conduction characteristics of the transistor. The independence of the actions of the four gates is what affords the enhanced functionality and design flexibility of G(sup 4)FETs. The present G(sup 4)FET logic circuits include an adjustable-threshold inverter, a real-time-reconfigurable logic gate, and a dynamic random-access memory (DRAM) cell (see Figure 2). The configuration of the adjustable-threshold inverter is similar to that of an ordinary complementary metal oxide semiconductor (CMOS) inverter except that an NMOSFET (a MOSFET having an n-doped channel and a p-doped Si substrate) is replaced by an n-channel G(sup 4)FET

Mojarradi, Mohammad↗

NASA NTRS2022

Moon to Mars (M2M) Habitation Considerations: A Snap Shot As of January 2022

The following NASA Technical Memorandum (TM) is intended to provide a snapshot in time of NASA’s current considerations (ground rules and assumptions, functional allocations, logistics) for habitation systems for the lunar surface (non-roving) and Mars transits. As NASA continues to refine the reference designs to meet the needs of an evolving architecture, it is expected that this information will also be updated as a result. Where appropriate, relevant publicly released documents will be referenced to provide further detail. NASA’s human lunar exploration plan under the Artemis program calls for achieving the goal of sending the first woman and first person of color to the surface of the Moon in the mid- 2020s and working toward sustainable exploration by the end of the decade. Working with both commercial and international partners, NASA will establish a permanent human presence on the Moon to uncover new scientific discoveries and lay the foundation for private companies to build a lunar economy. Longer duration missions on the lunar surface and in lunar orbit will also serve as a test bed for technologies to support future Mars exploration campaigns. The agency will use what we learn on the Moon to prepare for humanity's next giant leap – sending astronauts to Mars. NASA intends to establish a sustained lunar presence with the development of the Artemis Base Camp to prove technologies and capabilities that will one day enable humans to live and work on Mars, beginning with core elements including the Lunar Terrain Vehicle (LTV), the Pressurized Rover (PR), the lunar Surface Habitat (SH), power systems, and in-situ resource utilization (ISRU) systems. For in space operations and eventual transport of humans to Mars, NASA will utilize a Mars Transit Habitat (TH). Following deployment, the TH will complete a series of longer duration missions and shakedown testing while docked at Gateway, leveraging Gateway’s habitation redundancy for safety measures. Proposed Gateway-TH missions will far exceed the longest duration cislunar human missions to date. They will be the first operational readiness tests of our long-duration deep space systems, and of the split crew (two crew on the surface, two crew in space) operations that are vital to the approach for the first human Mars mission. Both the SH and TH are major architectural elements of NASA’s Moon to Mars (M2M) approach, each with very different concepts of operation. The SH is intended for use on the lunar surface as a home for astronauts, surface operations base, science facility, hub for communications, extravehicular activity (EVA) equipment repair site, waste processing facility, and supply hub. It serves as an enabler for a sustained surface presence and preparation for partial gravity operations during Mars missions. The SH will be designed to be self-sufficient for operations on the lunar surface. The SH will independently provide several functions, including its own power generation, energy storage capability, sleep quarters, hygiene areas, work areas, and dining areas. It will be capable of communicating with surface assets, orbital assets, and directly with Earth ground stations. It is planned to operate with two crew in the habitat for ~28- day stays with crew swap-outs in which the PR crew of two trades places with the habitat crew. During the swap-out, the habitat will nominally support four crew for a short period of time. For contingency scenarios, the habitat must also be capable of supporting four crew for up to 7 days. The TH will be designed to be capable of up to ~1,200-day Mars missions with the ability to carry all food and supplies needed to support a crew of four for this duration. An assumed Mars mission profile for the TH is to carry crew and supplies for ~850-day roundtrips between Earth and Mars orbit that allows 30-day stays on the Martian surface. To test the systems for this long journey, the TH will be used to extend the duration of missions at Gateway, enabling the orbiting outpost to be used as a Mars analog. These analog missions will be accomplished by attaching the TH to Gateway and conducting lunar surface operations from the TH. The TH may also need to perform free-flying shakedown missions to test out all systems prior to leaving for Mars. The habitat provides many critical functions including: a contingency airlock, crew quarters, galley, hygiene areas, safe haven capability, and science equipment. It can receive docked items from either axial end or on a radial port.

Habitat↗

DOE OSTI2025

Dynamical dark energy in light of the DESI DR2 baryonic acoustic oscillations measurements

Understanding whether cosmic acceleration arises from a cosmological constant or a dynamical component is a central goal of cosmology, and the Dark Energy Spectroscopic Instrument (DESI) enables stringent tests with high-precision distance measurements. Here we analyse measurements of baryon acoustic oscillations in DESI Data Release 1 and Data Release 2 and consider type Ia supernovae and a distance prior for the cosmic microwave background. With the larger statistical power and wider redshift coverage of Data Release 2, the preference for dynamical dark energy does not diminish relative to Data Release 1. Using both a shape-function reconstruction and non-parametric approaches with a Horndeski-motivated correlation prior, we find that the equation of state for dark energy w(z) varies with redshift. Baryon acoustic oscillation data alone yield modest constraints, but in combination with independent supernova compilations and the prior for the cosmic microwave background, they strengthen the evidence for dynamics. A Bayesian comparison of models shows moderate support for departures from Λ cold dark matter (ΛCDM) when several degrees of freedom in w(z) are allowed, corresponding to ~3σ tension with ΛCDM (and higher for some datasets). Despite methodological differences, our results are consistent with companion DESI papers, underscoring the complementarity of the approaches. Possible systematics remain under study; forthcoming DESI, Euclid and next-generation cosmic microwave background data will provide decisive tests.

cosmology↗

DOE OSTI2025

Dynamical dark energy in light of the DESI DR2 baryonic acoustic oscillations measurements

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning

Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling automated microscopy requires the development of task-specific machine learning methods, understanding the interplay between physics discovery and machine learning, and fully defined discovery workflows. This, in turn, requires balancing the physical intuition and prior knowledge of the domain scientist with rewards that define experimental goals and machine learning algorithms that can translate these to specific experimental protocols. Here, we discuss the basic principles of Bayesian active learning and illustrate its applications for SPM. We progress from the Gaussian process as a simple data-driven method and Bayesian inference for physical models as an extension of physics-based functional fits to more complex deep kernel learning methods, structured Gaussian processes, and hypothesis learning. These frameworks allow for the use of prior data, the discovery of specific functionalities as encoded in spectral data, and exploration of physical laws manifesting during the experiment. Here, the discussed framework can be universally applied to all techniques combining imaging and spectroscopy, SPM methods, nanoindentation, electron microscopy and spectroscopy, and chemical imaging methods and can be particularly impactful for destructive or irreversible measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗