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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Tuning the spin dynamics and magnetic phase transitions of the Cantor alloy via composition and sample processing protocols: A muon spin relaxation study

CrMnFeCoNi, also called the Cantor alloy, is a well-known high-entropy alloy whose magnetic properties have recently become a focus of attention. Here, we present a detailed muon spin relaxation study of the influence of chemical composition and sample processing protocols on the magnetic phase transitions and spin dynamics of several different Cantor alloy samples. Specific samples studied include a pristine equiatomic sample, samples with deficient and excess Mn content, and equiatomic samples magnetized in a field of 9 T or plastically deformed in pressures up to 0.5 GPa. The results confirm the sensitive dependence of the transition temperature on composition and demonstrate that post-synthesis pressure treatments cause the transition to become significantly less homogeneous throughout the sample volume. In addition, we observe critical spin dynamics in the vicinity of the transition in all samples, reminiscent of canonical spin glasses and magnetic materials with ideal continuous phase transitions. Application of an external magnetic field suppresses the critical dynamics in the Mn-deficient sample, while the equiatomic and Mn-rich samples show more robust critical dynamics. The spin-flip thermal activation energy in the paramagnetic phase increases with Mn content, ranging from 3.1⁢(3) × 10 -21 J for 0% Mn to 1.2⁢(2) × 10 -20 J for 30% Mn content. These results shed light on critical magnetic behavior in environments of extreme chemical disorder and demonstrate the tunability of spin dynamics in the Cantor alloy via chemical composition and sample processing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Wireless Frequency‐Multiplexed Acoustic Array‐Based Acoustofluidics

Abstract Acoustofluidics has shown great potential in enabling on‐chip technologies for driving liquid flows and manipulating particles and cells for engineering, chemical, and biomedical applications. To introduce on‐demand liquid sample processing and micro/nano‐object manipulation functions to wearable and embeddable electronics, wireless acoustofluidic chips are highly desired. This paper presents wireless acoustofluidic chips to generate acoustic waves carrying sufficient energy and achieve key acoustofluidic functions, including arranging particles and cells, generating fluid streaming, and enriching in‐droplet particles. To enable these functions, the wireless acoustofluidic chips leverage mechanisms, including inductive coupling‐based wireless power transfer (WPT), frequency multiplexing‐based control of multiple acoustic waves, and the resultant acoustic radiation and drag forces. For validation, the wirelessly generated acoustic waves are measured using laser vibrometry when different materials (e.g., bone, tissue, and hand) are inserted between the WPT transmitter and receiver. Moreover, the wireless acoustofluidic chips successfully arrange nanoparticles into different patterns, align cells into parallel pearl chains, generate streaming, and enrich in‐droplet microparticles. This research is anticipated to facilitate the development of embeddable wireless on‐chip flow generators, wearable sensors with liquid sample processing functions, and implantable devices with flow generation and acoustic stimulation abilities for engineering, veterinary, and biomedical applications.

Li, Jiali↗
DOE OSTI2025

PPI DataHub Project Data Package: S. elongatus PCC 7942 Limited Proteolysis and Thermal Proteome Profiling Structural Proteomics (JM-PB-DP3)

The purpose of this experiment was to investigate structural alterations in proteins involved in central carbon metabolism and photosynthetic electron transfer pathways in Synechococcus elongatus PCC 7942. Sample data was obtained from S. elongatus cell lysates using three complementary mass spectrometry (MS) techniques using limited proteolysis (LiP-MS), thermal proteome profiling (TPP-MS), and redox enrichment (Redox-MS) in evaluating alterations solvent accessibility and structural stability caused by light perturbation at the molecular level. Experimentally processed sample data for LiP and TPP proteomic datasets were derived from the same cell culture stock, prepared simultaneously in parallel, and acquired by mass spectrometry. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files, computed outputs, and supporting metadata materials. Experimental samples processed for LiP-MS label-free quantification (LFQ) or TPP-MS tandem mass tag (TMT) 10-plex were acquired using a Q-Exactive HF-X mass spectrometer and processed/compiled using either MSGF+ (v2024.03.26) or ​​​​PlexedPiper for proteome evaluation. Additional software supporting downstream proteomic analysis include FragPipe (v.4.0), MSFragger (v.22.1), and an adapted Microbial Isolate LiP Analysis Workflow (located at Zenodo). Processed proteomic data downloads include a sample naming key, normalized quantification results files, and processed protein annotated abundance files.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

MCPC Friction Stir Welding (FSW) Process Data

Processing parameters and machine log data for the MCPC LDRD Agile investment is collected material samples processed. This dataset captures the selected processing parameters, machine logs captured during material processing, and descriptions of how characterization samples were extracted from processed plates of material. The collect characterization data is captured in other datasets.

316 Stainless Steel↗
DOE OSTI2024

Coupling Microdroplet-Based Sample Preparation, Multiplexed Isobaric Labeling, and Nanoflow Peptide Fractionation for Deep Proteome Profiling of the Tissue Microenvironment

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity in a cell-type-specific manner to better understand and predict the function of complex biological systems such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverage due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (microdroplet processing in one pot for trace samples), multiplexed isobaric labeling, and a nanoflow peptide fractionation approach. The integrated workflow allowed us to maximize proteome coverage of laser-isolated tissue samples containing nanogram levels of proteins. We demonstrated that the deep spatial proteomics platform can quantify more than 5000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 μm2) and differentiate unique protein abundance patterns in pancreas. Furthermore, the use of the microPOTS chip eliminated the requirement for advanced microfabrication capabilities and specialized nanoliter liquid handling equipment, making it more accessible to proteomic laboratories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Bayesian Framework for Bioburden Density Estimation in Planetary Protection

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A comparative analysis of residual stresses from friction stir processing of aluminum cast 380 and wrought 7075 alloy sheets: experimental characterization and modeling

Residual stresses are often overlooked in friction stir processing (FSP), but their significant impact on fatigue performance necessitates their consideration in optimizing processing parameters. The first step in this effort is understanding how process conditions influence residual stress distributions, especially across different alloys. This study focuses on determining and explaining the through-thickness residual stress variations and the effect of process temperature on the residual stress magnitude in wrought AA7075 and cast AA380.0 alloys. Additionally, for AA380.0, the impact of a second FSP pass was investigated. To achieve this, hole-drilling electronic speckle pattern interferometry (ESPI) and the thermal pseudo-mechanical (TPM) model within finite element analysis were employed to study the 3D distributions of in-plane residual stresses in processed samples under various conditions. A key finding was the varying impact of process temperatures on residual stress magnitudes. Higher process temperatures reduced stresses in AA380.0 but increased them in AA7075. Additionally, the through-thickness stress distributions differed between the two alloys. Further analysis revealed that yield stresses are crucial in explaining these phenomena and the effects of additional FSP passes. Further, this fundamental understanding will be vital in guiding the efforts to mitigate residual stresses and assess their impact on the performance of FSP aluminum alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of a high-throughput method for processing sponge-stick samples to detect viable Bacillus anthracis spores

Since the national validation of the sponge-stick based method for detection of Bacillus anthracis spores in environmental samples, there have not been focused efforts to address the low throughput nature of the method, which processes only one sample at one time. Sample processing remains a serious bottleneck for rapidly analyzing large numbers of samples expected from a biological warfare attack. Therefore, we developed a high-throughput method to simultaneously process multiple sponge-stick samples to be better prepared for rapid response and recovery after wide area anthrax incidents. In this method, sponges are placed in 50 mL tubes containing 25 mL extraction buffer and shaken to release spores, after which the suspension is recovered for analysis. Here, we determined that an additional extraction step, conducted in the same tubes with 10 mL buffer, further increased spore recovery from sponge-stick by approximately 10 %. We determined that orbital shaking and multi-tube vortexing were both more effective than reciprocating shaking for recovering spores. We conducted simultaneous processing of up to 12 sponge-stick samples and demonstrated comparable spore recovery efficiencies to the traditional low-throughput stomacher-based method (approximately 60 % recovery at 10 2 -spore level and 75 % recovery at 10 4 -spore level for both methods in three replicate experiments, P > 0.05 for two-tailed t-tests for each experiment and spore level). We also demonstrated that our high-throughput method could be integrated with Rapid Viability-Polymerase Chain Reaction (RV-PCR) analysis and could detect levels as low as 40 spores per sponge even when challenged by a PCR particulate contaminant.

Anthrax↗
DOE OSTI2024

A Review of Online Monitoring within Used Nuclear Fuel Recycling Processes

The processing of used nuclear fuels and related materials is often complex and variable. The ability to quickly optimize conditions to the material being processed can aid in increasing efficiency and safety, but requires very quick determination of the conditions present in the feedstock, the process, and the product. Furthermore, accurate quantification of materials such as enriched uranium and plutonium aids in maintaining material accountancy and avoiding nuclear proliferation risks. Traditional analytical methods require process samples to be collected and analyzed in a laboratory, which often takes days to weeks. Online monitoring is suitable for collecting this information nearly instantaneously, enabling much faster optimization of the process or detection of material diversion. Online monitoring is also beneficial as it is typically based on robust and nondestructive analytical methods, so no material is removed as samples. This review examines online monitoring relevant to used nuclear fuel processing for the determination of both chemical and physical parameters. The chemical parameters include quantities such as concentration, isotopic composition, and speciation. These values are often well suited to spectroscopic or spectrometric measurements as they are fast, nondestructive, and easily implemented in an online manner. Physical quantities are often more varied and include temperature, pressure, tank fill levels, and others. Due to the specificity of these quantities, specialized instrumentation is often used. However, this instrumentation is often amendable to online monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Integrative Multi-PTM Proteomics Reveals Dynamic Global, Redox, Phosphorylation, and Acetylation Regulation in Cytokine-treated Pancreatic Beta Cells

Studying regulation of protein function at a systems level necessitates an understanding of the interplay among diverse post-translational modifications (PTMs). A variety of proteomics sample processing workflows are currently used to study specific PTMs but rarely characterize multiple types of PTMs from the same sample inputs. Method incompatibilities and laborious sample preparation steps complicate large-scale physiological investigations and can lead to variations in results. The single-pot, solid-phase-enhanced sample preparation (SP3) method for sample cleanup is compatible with different lysis buffers and amenable to automation, making it attractive for high-throughput multi-PTM profiling. Herein, we describe an integrative SP3 workflow for multiplexed quantification of protein abundance, cysteine thiol oxidation, phosphorylation, and acetylation. The broad applicability of this approach is demonstrated using cell and tissue samples, and its utility for studying interacting regulatory networks is highlighted in a time-course experiment of cytokine-treated ß-cells. We observed a swift response in global regulation of protein abundances consistent with rapid activation of JAK-STAT and NF-?B signaling pathways. Regulators of these pathways as well as proteins involved in their target processes displayed multi-PTM dynamics indicative of a complex cellular response stages: acute, adaptation, and chronic (prolonged stress). PARP14, a negative regulator of JAK-STAT, had multiple co-localized PTMs that may be involved in intraprotein regulatory crosstalk. Our workflow provides a high-throughput platform that can profile multi-PTMomes from the same sample set, which is valuable in unraveling the functional roles of PTMs and their co-regulation.

proteomics, PTM, automation, SP3, cysteine thiol o↗
DOE OSTI2024

Tuning austenite stability through prior microstructure control in a low-alloy Q&P steel

Quenching and partitioning (Q&P) processing is a widely accepted heat treatment methodology for creating high strength steels consisting of ferrite, martensite, and austenite, while maintaining relatively low manufacturing costs. Though the research on effects of prior microstructure is limited, an understanding of the heat treatment response of different starting microstructures is critical to processing and creating steels with complex microstructures that contain retained austenite and may afford opportunities to further optimize properties. This study investigates the influence of starting microstructure (ferrite/pearlite versus martensite) and prior levels of cold work (38 verses 58 %) on the microstructural development and mechanical properties of a 0.2 C-2.0 Mn-1.5 Si (wt.%) steel exposed to Q&P processing. Samples with a starting martensitic microstructure resulted in higher retained austenite fractions and a more homogeneous microstructure after Q&P processing compared to a starting microstructure of ferrite-pearlite. Starting martensitic microstructures also displayed higher work hardening rates and higher uniform elongations. Larger cold reductions saw accelerated dissolution kinetics and austenite formation during intercritical annealing, resulting in more similar final microstructures from the ferrite-pearlite and martensitic starting microstructures. Finally, the results presented here indicate that varying prior processing can be a route to manipulate and control austenite stability in a Q&P processed steel.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Diffusion model approach to simulating electron-proton scattering events

Generative artificial intelligence is a fast-growing area of research offering various avenues for exploration in high-energy nuclear physics. In this work, we explore the use of generative models for simulating electron-proton collisions relevant to experiments like the Continuous Electron Beam Accelerator Facility and the future Electron-Ion Collider (EIC). These experiments play a critical role in advancing our understanding of nucleons and nuclei in terms of quark and gluon degrees of freedom. The use of generative models for simulating collider events faces several challenges such as the sparsity of the data, the presence of global or eventwide constraints, and steeply falling particle distributions. In this work, we focus on the implementation of diffusion models for the simulation of electron-proton scattering events at EIC energies. Our results demonstrate that diffusion models can reproduce relevant observables such as momentum distributions and correlations of particles, momentum sum rules, and the leading electron kinematics, all of which are of particular interest in electron-proton collisions. Although the sampling process is relatively slow compared to other machine-learning architectures, we find diffusion models can generate high-quality samples. We foresee various applications of our work including inference for nuclear structure, interpretable generative machine learning, and searches of physics beyond the Standard Model. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Densification, microstructure, and mechanical properties of Mo–30W alloys fabricated from conditioned powders

Refractory alloys, such as molybdenum-based systems, are attracting growing interest for applications in extreme environments, such as in the nuclear and aerospace industries. Recent advances in sintering technologies, coupled with mechanical alloying, have enabled the tailored design of these alloys by leveraging powder characteristics to control final microstructures and mechanical properties. In this study, Mo-30W alloys were fabricated using electric field-assisted sintering (EFAS) from ball-milled powders with and without hydrogen treatment to investigate the influence of surface oxides on material properties and sintering behavior. The results revealed that samples processed from as-ball-milled powder contained a high density of oxides within the microstructure, whereas oxide presence was significantly reduced in samples fabricated from hydrogen-treated powders. Interestingly, the two powder types led to opposite trends in grain size distribution: samples from untreated powders exhibited grain refinement from sample periphery to the center, while samples from hydrogen-treated powders showed grain coarsening toward the center. This behavior is attributed to temperature gradients present during sintering due to electrical percolation pathway differences during Joule heating. The powder surface oxides may have influenced the temperature distribution and grain evolution. Microhardness profiles measured along both axial and thickness directions were consistent with the grain size distribution. Furthermore, oxide films on powder surfaces have delayed densification by hindering particle necking and atomic diffusion during sintering.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Effects of magnetic field assisted heat treatment on the microstructure and mechanical properties of Fe-0.63 %C alloy

This study investigates the influence of an applied magnetic field on the microstructural evolution and mechanical properties of hypoeutectoid steels subjected to heat treatment. Tensile tests and microstructural analysis were performed on samples processed under varying magnetic field strengths (0 T, 5 T, and 9 T) and different austenitization incubation times. The results indicate that the application of a magnetic field alters the fraction of proeutectoid ferrite phase without changing the cooling rates and heat treatment process. Additionally, pearlite microstructural features such as lamellar spacing and misorientation angles exhibit variations under different field strengths. While the pearlite nodule diameter remains largely unaffected, an increase in percentage elongation and strength is observed in the 5 T treated sample, attributed to changes in microstructural features with the magnetic field. Additionally, the percentage elongation is reduced in the samples heat treated with reduced austenitization incubation times. The study further demonstrates that low-angle misorientations increased in the samples taken parallel to the magnetic field direction, influencing the mechanical response. These findings suggest that applying a magnetic field during heat treatment provides an additional driving force for phase transformations, offering a manufacturing process for tailoring microstructures and optimizing mechanical properties. Moreover, integrating magnetic fields in heat treatment processes has potential benefits in energy efficiency.

High magnetic field↗
DOE OSTI2025

Impact of Storage Conditions on the Quality and Viability of Switchgrass as a Bioenergy Crop

With growing energy demands and climate concerns, advancements in bioenergy have become imperative. Biofuels promote energy independence, reduce fossil fuel reliance, and cut greenhouse gas emissions. Switchgrass (Panicum virgatumis) is an ideal bioenergy crop due to its ability to thrive on marginal lands unsuitable for food crops and its drought tolerance, rendering it a low-maintenance, high-yield option. In the bioenergy industry, energy crops are typically stored to facilitate supply chain management and ensure a continuous supply despite seasonal availability. However, the effective utilization of bioenergy crops is typically contingent upon addressing the challenges associated with biomass storage. These challenges include high moisture content that promotes biological degradation of the biomass leading to increased risk of pathogenic microbes, and chemical degradation that increases the ratio of inconvertible, inorganic materials. These issues lead to a reduction of feedstock value, diminishing the biomass-to-biofuel conversion efficacy, making switchgrass and other bioenergy crops less effective as fuel sources. This project aims to improve the storage of purpose-grown energy crops. Aerobic storage trials were conducted under varying moisture contents to stimulate real-world environmental exposure. Switchgrass samples were rewetted to 30% or 35% and stored in a bioreactor for approximately one month, or until cellular respiration ceased. Degradation indicators, such as dry matter loss, temperature changes, and cellular respiration, were measured throughout this process. Samples for compositional analysis, 16S, and ITS were taken at three different time points: before, during, and after storage, to monitor changes in biomass, microbial communities, and metabolites over time. Preliminary data indicate that dry matter loss is proportional to cellular respiration, with higher moisture content (35%) leading to higher temperatures and elevated dry matter loss. Compositional analysis and microbial community analysis are in progress. This research will provide a comprehensive understanding of storage, helping to identify stability factors in energy crops and improve best management practices for biomass producers.

09 - BIOMASS FUELS↗
DOE OSTI2025

An Evaluation of Actinide Reactivity with CO 2 , O 2 , and O 2 /He Gases using Inductively Coupled Plasma Tandem Mass Spectrometry: Application to Simultaneous Measurement of 241 Am/ 241 Pu Ratios in Unseparated Complex Matrices

Accurate actinide measurements are critical within the field of nuclear science. Traditional methods for actinide quantification require time-consuming sample processing prior to analysis. There is a need for rapid analytical techniques that still maintain a high degree of accuracy. In this work, actinide reactivity was assessed for multiple oxygen-containing reaction gases using quadrupole inductively coupled plasma tandem mass spectrometry (Q-ICP-MS/MS) to evaluate actinide analysis in complex sample matrices without analyte-matrix separation. A novel method was developed to measure 241 Am/ 241 Pu in complex sample matrices using O 2 /He reaction gas with no matrix removal or analyte pre-concentration. This inline method reduces matrix-derived polyatomic interferences that complicate traditional ICP-MS analyses by mass-shifting to 241 Am 16 O + and 241 Pu 16 O 2 + , allowing Am and Pu to be mass separated for simultaneous analysis. While mass shifting is efficient, a small portion of Am + (<1.3%) and Pu + (<1.4%) react to from AmO 2 + and PuO + , respectively. Therefore, a mass balance approach was used, in combination with reactivity determined from 242 Pu and 243 Am standard solutions, to correct for residual 241 PuO + and 241 AmO 2 + . The method was validated by measuring 241 Am/ 241 Pu in Pu isotope standards CRM-136 and CRM-137 (separated in March/April 1970 and February 2022, respectively) in both neat solutions and complex matrices containing diluted soil (NIST SRM 2711a, >1000 µg·g -1 ). Method detection limits of 15.9 and 9.6 fg·g -1 were determined for 241 Am and 241 Pu, respectively, and 241 Am/ 241 Pu ratios were measured with accuracies within <3.5%. In conclusion, this work presents the first direct analysis of 241 Am/ 241 Pu in unseparated complex matrices, advancing capabilities for rapid actinide measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Spatial Proteomics towards cellular Resolution

Introduction: Spatial biology is an emerging interdisciplinary field facilitating biological discoveries through the use of spatial omics technologies. Recent advancements in spatial transcriptomics, spatial genomics (e.g. genetic mutations and epigenetic marks), multiplexed immunofluorescence, and spatial metabolomics/lipidomics have enabled high-resolution spatial profiling of gene expression, genetic variation, protein expression, and metabolites/lipids profiles in tissue. These developments contribute to a deeper understanding of the spatial organization within tissue microenvironments at the molecular level. Areas covered: This report provides an overview of the untargeted, bottom-up mass spectrometry (MS)-based spatial proteomics workflow. It highlights recent progress in tissue dissection, sample processing, bioinformatics, and liquid chromatography (LC)-MS technologies that are advancing spatial proteomics toward cellular resolution. Expert opinion: The field of untargeted MS-based spatial proteomics is rapidly evolving and holds great promise. To fully realize the potential of spatial proteomics, it is critical to advance data analysis and develop automated and intelligent tissue dissection at the cellular or subcellular level, along with high-throughput LC-MS analyses of thousands of samples. In conclusion, achieving these goals will necessitate significant advancements in tissue dissection technologies, LC-MS instrumentation, and computational tools.

59 BASIC BIOLOGICAL SCIENCES↗