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DOE OSTI2020

Protein structural changes on a CubeSat under rocket acceleration profile

Catalyzing life-sustaining reactions, proteins are composed by 20 different amino acids that fold into a compact yet flexible three-dimensional architecture, which dictates what their function(s) might be. Determining the spatial arrangement of the atoms, the protein’s 3D structure, enables key advances in fundamental and applied research. Protein crystallization is a powerful technique to achieve this. Unlike Earth’s crystallization experiments, biomolecular crystallization in space in the absence of gravitational force is actively sought to improve crystal growth techniques. However, the effects of changing gravitational vectors on a protein solution reaching supersaturation remain largely unknown. Here, we have developed a low-cost crystallization cell within a CubeSat payload module to exploit the unique experimental conditions set aboard a sounding rocket. We designed a biaxial gimbal to house the crystallization experiments and take measurements on the protein solution in-flight with a spectrophotometry system. After flight, we used X-ray diffraction analysis to determine that flown protein has a structural rearrangement marked by loss of the protein’s water and sodium in a manner that differs from crystals grown on the ground. We finally show that our gimbal payload module design is a portable experimental setup to take laboratory research investigations into exploratory space flights.

42 ENGINEERING↗

DOE OSTI2021

In Situ/Operando (Soft) X-ray Spectroscopy Study of Beyond Lithium-ion Batteries

The lightweight, rechargeable lithium-ion battery is one of the dominant energy storage devices globally in portable electronics due to its high energy density, no memory effect, wide operating voltage, lightweight, and good charge efficiency. However, due to safety concerns, the depletion of lithium reserves, and the corresponding increase of cost, an alternative battery system becomes more and more desirable. To develop alternative battery systems with low cost and high material abundance, for example, sodium, magnesium, zinc, and calcium, it is important to understand the chemical and electronic structure of materials. Additionally, soft X-ray spectroscopy, for example, X-ray absorption spectroscopy (XAS), X-ray emission spectroscopy (XES), and resonant inelastic soft X-ray scattering (RIXS), is an element-specific technique with sensitivity to the local chemical environment and structural order of the element of interest. Modern soft X-ray systems enable operando experiments that can be applied to amorphous and crystalline samples, making it a powerful tool for studying the electronic and structural changes in electrode and electrolyte species. In this article, the application of in situ/operando (soft) X-ray spectroscopy in beyond lithium-ion batteries is reviewed to demonstrate how such spectroscopic characterizations could facilitate the interpretation of interfacial phenomena under in situ/operando condition and subsequent development of the beyond lithium-ion batteries.

(soft) X-ray spectroscopy↗

DOE OSTI2023

Functional Predictor Variables for the Leaching Potential of Arsenic and Selenium from Coal Fly Ash

The release of leachates from intact coal ash impoundments is a concern due to the enrichment and mobilization of toxic elements such as arsenic (As) and selenium (Se). This study aims to explore the intrinsic properties of coal fly ash that correlate with the relative leachability of As and Se. We performed leaching experiments with 52 fly ash samples collected from 15 different U.S. power plants and representing coal feedstocks from the three major domestic regions. We assessed the mobilization potential of As and Se in fly ash based on standardized leaching protocols and performed multivariate and lasso regression analyses to explore correlations of leachable As and Se contents with characteristics such as major element contents, loss on ignition, and pH. The results of regression models indicated that major elements (Fe, Ca, and Al) for a wide range of fly ashes can serve as predictor variables for the leaching potential of As but not for Se. LOI and pH were not important predictive variables in the models. Both regression approaches resulted in relatively strong fits for leachable As (correlation coefficient R 2 = 0.78 for both models) compared to models for leachable Se (R 2 = 0.49). Overall, these results suggest that correlation models combined with on-site elemental analysis with portable analyzers may enable a screening method for leachable As in coal ash.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Rapid RASER MRI

Conventional Magnetic Resonance Imaging (MRI) relies on high-power Radio-Frequency (RF) pulses to excite nuclear spins and in turn generate NMR signals. These pulses require large high-power RF-amplifiers and cause heat deposition in the tissue, which must be minimized for safety, presenting a growing problem when moving toward ever-higher field MRI. An alternative to RF-pulse excitation is self-excitation of nuclear spins using Radiofrequency Amplification by Stimulated Emission of Radiation (RASER), where the nuclear spins undergo spontaneous transition, without RF excitation, from an over-populated state to a ground state. Here, the feasibility of recording rapid proton RASER MRI images of pyrazine at low concentration (120 mM) with large matrix (128x128 pixels) in as little as 78 ms is demonstrated at 500 MHz (11.7 T). We also recorded a time-series of images using a single bolus hyperpolarized pyrazine highlighting the feasibility of dynamic tracking. Here, the demonstrated approach allows recording MRI scans without transmit-receive electronics of the MRI scanner, which is highly desirable for portable MRI as well as the emerging field of hyperpolarized MRI using, e.g., HP protons, 129 Xe gas or HP 13 C labeled biomolecules as molecular tracers and imaging agents.

MRI↗

DOE OSTI2020

Titanium Niobium Oxide: From Discovery to Application in Fast-Charging Lithium-Ion Batteries

Lithium-ion batteries are essential for portable technology and are now poised to disrupt a century of combustion-based transportation. The electrification revolution could eliminate our reliance on fossil fuels and enable a clean energy future; advanced batteries would facilitate this transition. However, owing to the demanding performance, cost, and safety requirements, it is challenging to translate new materials from laboratory prototypes to industrial-scale products. This Perspective describes that journey for a new lithium-ion battery anode material, TiNb 2 O 7 (TNO). TNO is intended as an alternative to graphite or Li 4 Ti 5 O 12 with better rate and safety characteristics than the former and higher energy density than the latter. The high capacity of TNO stems from the multielectron redox of Nb 5+ to Nb 3+ , its operating voltage window well above the Li + /Li reduction potential prevents lithium dendrite formation, and its open crystal structure leads to high-power performance. Nevertheless, the creation of a practical TNO anode was nonlinear and nontrivial. Its history is built on 30 years of fundamental science that preceded its application as a battery anode, and its battery development included a nearly 30-year gap. The insights and lessons contained in this Perspective, many of them acquired firsthand, serve two purposes: (i) to unite the disparate studies of TiNb 2 O 7 into a coherent modern understanding relevant to its application as a battery material and (ii) to highlight briefly some of the challenges faced when scaling up a new material that affect TiNb 2 O 7 as well as new electrode candidates more generally.

25 ENERGY STORAGE↗

DOE OSTI2020

Technical report: Design of the accessor

As we have seen the arithmetic power of hardware architectures growing much faster than the memory bandwidth, there is an urgent need to rethink the way we operate, communicate, and store data. A promising strategy for overcoming the “memory wall” is the decoupling of memory precision from arithmetic precision as proposed in Anzt et al. Such a decoupling of memory precision and arithmetic precision requires an “accessor” that handles the conversion between formats (resp. compression of the data) on the fly in registers. Such an accessor has to be general in the sense that it can handle a wide range of floating point formats and compression strategies, and still allows for further extension. At the same time, is important that the use of the accessor is not a burden for the developer. Therefore, it is important to abstract all implementation details from the user, hide the underlying storage format from the user, and make the accessor cross-platform portable. In this document we present the design of an accessor that aims at fulfilling all these requirements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Developing a Framework for Valuation of Grid Services

The electric system is rapidly evolving and growing, raising new questions about how to define and value grid services delivered by a diverse set of resources, including customer-owned assets. This report advances a service–parameter–value framework that links what a grid service does to why it matters, and how its benefits are evidenced. We build upon prior efforts (Bender et al. 2021) and extend them to include value categories (reliability, resilience, cost & access, and security) with primary and secondary tiers, service-specific value streams that explain how benefits materialize, and metrics that make valuation traceable and comparable. We apply the framework to the six core grid services defined in (Kolln et al. 2023): Frequency Response, Regulation, Reserves, Energy, Voltage Management, and Blackstart and demonstrate it on three use cases to highlight the adaptability of these value streams. Further, we outline how the framework integrates with existing tools such as asset optimization, hosting capacity and cost-benefit analysis, and propose a path to portable qualifications and consistent stacking rules for use in tariffs and filings. Finally, we identify future pathways for research and application research needs to support standardization and decision-ready comparisons across services, assets, and architectures.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Metal-Organic Framework-based Luminescent Sensors for Rare Earth Elements

Rare earth elements (REEs) are crucial for many applications and are particularly important in wind power and electric vehicle technologies, spurring projected demand increases for REEs in coming decades. However, the REE supply is restricted by a monopolistic global marketplace, tedious and costly processing steps for REE production, and environmental hazards associated with mining and processing. Coal and coal-utilization byproducts have emerged as potential domestic sources for REEs, however REE production from these sources is currently hindered by slow and expensive characterization techniques. Here, we demonstrate that metal-organic framework (MOF)-based sensitizers can effectively serve as luminescent sensors capable of rapidly detecting and distinguishing part-per-billion concentration levels of emissive REEs, including terbium, europium, dysprosium, samarium, neodymium, and ytterbium. Importantly, we demonstrate that the MOF structure plays a significant role in tuning the selectivity of the MOF for REEs in acidic environments, an essential step towards deployment in various REE-rich process streams. As a proof-of-concept, we demonstrate sensitive and reversible detection of REEs using a portable fiber-optic spectrometer

Crawford, Scott↗

DOE OSTI2026

Opportunities and Limitations of Nuclear Magnetic Resonance Spectroscopy in Astrobiology

For decades, Nuclear Magnetic Resonance (NMR) spectroscopy has been utilized as a powerful tool in various scientific disciplines, most prominently in chemistry, to determine molecular structures or monitor reactions. While well established in various fields, NMR applications in astrobiology are still unclear. This work aims to explore the potential of NMR in astrobiology, highlighting strengths but also weaknesses. We illustrate capabilities of NMR with two applications: (1) recently developed methods for position-specific carbon isotope analysis of complex organics; and (2) well-established tools for performing quantitative compositional analysis of complex organic mixtures. By utilizing samples relevant to astrobiology, specifically the amino acid valine and analogue mixtures of organics, we showcase that molecules retain a source dependent and distinct intramolecular carbon isotope fingerprint. We demonstrate that compositional sample analysis provides an independent and complementary line of evidence pointing towards the origin of a molecule or mixture. Together, these NMR tools have the potential to support life detection efforts, and aid in distinguishing between biotic and abiotic samples. Finally, we discuss sensitivity, detection limits, the portability of NMR, and propose how integration with mass-spectrometry techniques will be imperative to enable more targeted and comprehensive analyses relevant to astrobiology, including in-situ analysis but also sample return missions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Experimental Investigation on Cooling performance of A Thermoelectric Freezer

Thermoelectric heat pumps (TEHPs) have found widespread use in the electronics cooling industry and portable refrigerators. However, there has been a lack of extensive research on the application of TEHPs in low-temperature refrigeration settings. To address this gap, various configurations of TEHPs were fabricated to assess their suitability for freezer applications. Key parameters such as cooling capacity and system performance of the TEHPs were crucial in evaluating these configurations. Three configurations, each with different numbers of cooling units and fan arrangements, were tested using a 300-liter freezer prototype under typical room conditions (21°C). A cooling unit is comprised of two-stage thermoelectric modules, an aluminum plate fin heat exchanger sink with fans positioned either on top or directing airflow through the center, and a cooling block with circulating icy water for heat dissipation. Across all configurations, the minimum temperature inside the freezer cabinet reached -16.0°C. The cooling capacity peaked at 74.7 W, with the thermoelectric coefficient of performance (COP) reaching a maximum of 0.45. System COP ranged from 0.23 to 0.28. Minimum TE power consumption was recorded at 138.8 W, with TE system power consumption at 174.4 W, indicating feasibility for practical residential freezer applications. This investigation lays the foundation for integrating TE freezers with ice thermal storage systems.

Hu, Yifeng↗

DOE OSTI2022

Module-OT: A Turnkey Solution for Securing Energy Systems

The Modular Security Apparatus for Managing Distributed Cryptography for Command-and-Control Messages on Operational Technology Networks (Module-OT) is a flexible and lightweight solution for grid-edge devices focusing on end-to-end security. It is a bump- in- the-wire solution acting as a secure conduit for data between devices or systems across a network. It improves the cybersecurity posture of DER systems by providing authentication, authorization, and data integrity to secure DER communications. Additionally, it performs key management, provides data security through whitelisting Internet Protocol addresses and ports, blocks unauthorized connections, controls user access, and allows serial or Ethernet connections for added flexibility. The core software is portable to various Linux-based operating systems and is developed to be customized by the developer and researcher communities. Module-OT has been validated in the lab, has been demonstrated at a 500-KW PV-plus-storage site, and has been proven ready to secure operational technology devices. Its core functionality meets current standards, including validation procedures of the NIST Cryptographic Algorithm Validation Program (CAVP) and the Federal Information Processing Standard (FIPS 140-2). Because of its capability to provide an accessible and affordable option for stepping up security across modern energy systems, Module-OT can serve as an effective technological option to standardize cybersecurity moving forward.

cryptography↗

DOE OSTI2021

A Miniature Multilevel Structures for Lossless Ion Manipulations Ion Mobility Spectrometer with Wide Mobility Range Separation Capabilities

Here, ion mobility spectrometry employing structures for lossless ion manipulations (SLIM-IMS) is an attractive gas-phase separation technique due to its ability to achieve unprecedented effective ion path lengths (>1 km) and IMS resolving powers in a small footprint. The emergence of multilevel SLIM technology, where ions are transferred between vertically stacked SLIM electrode surfaces, has subsequently allowed for ultralong single pass path lengths (>40 m) to be achieved, enabling ultrahigh resolution IMS measurements to be performed over the entire mobility range in a single experiment. The implementation of multiple SLIM levels requires very little additional space for the SLIM system, and we developed a miniature SLIM module (miniSLIM) based on multilevel SLIM technology and report the performance here. The module is 11.1 cm x 6.7 cm x 1.4 cm (L x W x H) and consists of three SLIM levels totaling 1-meter path length. Ion trajectory simulations were used to optimize the SLIM board spacings and SLIM board thicknesses of the miniSLIM IMS system. Methods of efficiently transferring ions between SLIM levels were examined and a new approach using asymmetric traveling waves (TWs) was developed and implemented in the miniSLIM. We experimentally characterized the performance of the --meter multilevel miniSLIM IMS-MS relative to a drift tube IM--MS using an Agilent tuning mixture and tetraalkylammonium cations. The 1-meter miniSLIM achieved a resolving power of up to 131 (CCS/ΔCCS), ~1.5x higher than achievable with a 78 cm path length drift tube IMS, and successfully transmitted the entire ion mobility range in a single separation. We also demonstrated the miniSLIM’s performance as a standalone IMS system (i.e., without MS), showing baseline separation between Agilent tuning mixture cations with the full mobility range observed, and a standard peptide mixture with different charge states readily differentiated. Overall the miniSLIM provides a compact alternative to high performance IMS instruments possessing similar path lengths.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Abstract. Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes (i.e., phenomena) such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods.

58 GEOSCIENCES↗

DOE OSTI2020

Advanced Moderation Module for High-Temperature Micro-Reactor Applications

Development and deployment of micro-reactors that provide competitive efficiency, prevailing compactness, and inherent safety is an immediate focus of the U.S. nuclear industry. For thermal neutron micro-reactors operating at elevated temperature for optimized efficiency, such as micro molten-salt reactors (MSRs), heat-pipe reactors, and very-high temperature reactors (VHTRs), high-performance moderator based on metal hydride can enhance the neutron economy and therefore achieve reduced weight and enhanced portability. As unclad metal hydride inevitably decomposes at elevated temperature, an enclosure is required for hydride moderator to deliver desired performance at elevated temperatures. Conventional moderator enclosure solutions based on high-temperature alloys introduce extraneous neutron penalty into the micro-reactor, affecting the neutronic benefits provided by the hydride moderator. Additionally, the compatibility between the high-temperature alloy enclosure and the micro-reactor matrix is also a potential issue. In this report, we disclose an Advanced Moderator Module (AMM) concept enabled by an innovative enclosure solution combining the advantages of refractory metals, ceramic matrix composites (CMCs), and advanced coating technology to serve as hydrogen permeation barrier up to very-high temperatures. A schematic description of the AMM structure is illustrated in Figure A1. The AMM contains a moderating material core made of metal hydride with high thermal stability, such as YH 2-x . The hydride core is enclosed by an H 2 barrier layer coated on a ductile refractory metal liner to minimize hydrogen loss during high-temperature operation. A ceramic matrix composite (CMC) cladding is adopted to provide further structural strength, especially during power transients. Between the CMC cladding and metal liner, an extra diffusion barrier coating is inserted to suppress the chemical interaction at elevated temperatures. Hence, based on a series of innovative material solutions, the AMM is capable of containing the metal hydride core at elevated temperature (>900oC) inside coated and lined CMC envelop with negligible hydrogen loss throughout the microreactor lifetime. The benefit of the AMM technology was assessed based on a comprehensive multi-stage reactor-physics analysis. Advanced moderation based on hydride metals (such as YH2-x) enables reaching optimum moderation with higher fuel content than traditional VHTR technology, which is required to design compact micro-reactor cores targeting long-life operation. The AMM enclosure technology provides lower thermal neutron absorption rates than traditional solutions (based on stainless steel or Mo-based alloy such as TZM), which reduces the fissile enrichment requirements by 6-8% on a TRISO-fueled design based on the EMPIRE core. Finally, combining the hydride moderator with neutron transparent enclosure solutions provides significant potential to boost neutronics performance of micro-reactors in terms of increased core lifetime or reduced size and weight by 30-50% on a micro-reactor based on the Holos Quad technology. The progress and plans for on-going development and demonstration efforts are also discussed in this report. The current demonstration of AMM is focused on the hydrogen diffusion barrier demonstration under thermal cycling, while radiation tolerance demonstration is planned. The next step of the demonstration plan will be the assembly of miniature AMM for high-temperature testing, which can be used as a prototype for future pilot scale demonstration.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

PETSc Users Manual (Rev. 3.13)

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication. PETSc includes an expanding suite of parallel linear solvers, nonlinear solvers, and time integrators that may be used in application codes written in Fortran, C, C++, and Python. PETSc provides many of the mechanisms needed within parallel application codes, such as parallel matrix and vector assembly routines. The library is organized hierarchically, enabling users to employ the level of abstraction that is most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users. PETSc is a sophisticated set of software tools; as such, for some users it initially has a much steeper learning curve than a simple subroutine library. In particular, for individuals without some computer science background, experience programming in C, C++, python, or Fortran and experience using a debugger such as gdb or dbx, it may require a significant amount of time to take full advantage of the features that enable efficient software use. However, the power of the PETSc design and the algorithms it incorporates may make the efficient implementation of many application codes simpler than \rolling them" yourself.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗

DOE OSTI2023

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

47 OTHER INSTRUMENTATION↗