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DOE OSTI2025

Digital light processing of porous LLZTO scaffolds for Li-garnet solid-state batteries

Li 7 La 3 Zr 2 O 12 (LLZO)-based solid-state electrolytes (SEs) are promising materials for next-generation solid-state batteries. In this work, digital light processing (DLP), an emerging additive manufacturing technology, is employed to produce porous Ta-doped LLZO (LLZTO) scaffolds. The self-standing scaffolds are 100 μm thick and have 40% porosity. The scaffolds demonstrate symmetric cell cycling stability exceeding 1,500 h at 0.1 mA/cm2 current density, with a capacity of 0.1 mAh/cm 2 (1 h for each half cycle). At higher current densities, reversible soft shorts frequently happen, while immediate hard shorts are prevented due to Li dendrite growth being hindered by the tortuous pore network. In addition to the cycling stability, the phase stability of LLZTO is investigated during the post-printing thermal process for printing resin removal. We discovered that the LLZTO partially decomposes into Li 2 Zr 2 O 7 and other impurity phases from 400°C to 800°C, but the pure LLZTO phase is restored upon the completion of resin removal beyond 800°C.

Li-metal anode↗

NASA NTRS1975

Formulation of the information capacity of the optical-mechanical line-scan imaging process

An expression for the information capacity of the optical-mechanical line-scan imaging process is derived which includes the effects of blurring of spatial, photosensor noise, aliasing, and quantization. Both the information capacity for a fixed data density and the information efficiency (the ratio of information capacity to data density) exhibit a distinct single maximum when displayed as a function of sampling rate, and the location of this maximum was determined by the system frequency-response shape, signal-to-noise ratio, and quantization interval.

Huck, F. O.↗

NASA NTRS1999

Thermophysical Properties of Zirconium at High Temperature

Six thermophysical properties of both the solid and liquid zirconium measured using the high-temperature electrostatic levitator at JPL are presented. These properties are: density, thermal expansion coeffiecient, constant pressure heat capacity, hemispherical total emissivity, surface tension and viscosity.

thermophysical↗

DOE OSTI2024

Designing electrolytes with high solubility of sulfides/disulfides for high-energy-density and low-cost K-Na/S batteries

Alkaline metal sulfur (AMS) batteries offer a promising solution for grid-level energy storage due to their low cost and long cycle life. However, the formation of solid compounds such as M 2 S 2 and M 2 S (M = Na, K) during cycling limits their performance. Here we unveil intermediate-temperature K-Na/S batteries utilizing advanced electrolytes that dissolve all polysulfides and sulfides (K 2 S x , x = 1–8), significantly enhancing reaction kinetics, specific capacity, and energy density. These batteries achieve near-theoretical capacity (1655 mAh g -1 sulfur) at 75 °C with a 1 M sulfur concentration. At a 4 M sulfur concentration, they deliver 830 mAh g -1 at 2 mA cm -2 , retaining 71% capacity after 1000 cycles. This new K-Na/S battery with specific energy of 150-250 Wh kg -1 only employs earth-abundant elements, making it attractive for long-duration energy storage.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Complex-Concentrated Anion Doping Enables Ultra-Stable Lattice Oxygen and Structural Integrity in Lithium-Rich Layered Oxide Cathodes

Lithium- and manganese-rich layered oxides (LMR) stand out as next-generation lithium-ion cathode chemistries, which harness both transition-metal and lattice-oxygen redox processes to deliver exceptional capacity and energy density. However, their full potential is hindered by intrinsic oxygen instability and structural degradation, resulting in pronounced voltage fade and capacity decay. Here, we present a complex-concentrated anion-doping paradigm in which multiple anions, F, Br, and S, are incorporated into the oxygen sublattice to enhance oxygen-redox and structural stability. X-ray absorption spectroscopy and aberration-corrected scanning transmission electron microscopy confirm ultra-stable local oxygen coordination environments during long-term cycling, with detrimental phase transformations and oxygen-loss-induced cavitation dramatically inhibited. Notably, we show that the characteristic LiTM6 transition metal (TM) honeycomb ordering is preserved even after electrochemical cycling. Concurrently, this strategy yields an unprecedented volume change of only 0.63% upon charging to 4.8 V vs. Li+/Li, achieving the first zero-strain LMR cathode. The resulting LMR cathode delivers ultralow voltage fade (1 mV per cycle during the first 100 cycles and becomes negligible in subsequent cycles) and outstanding energy retention (93% after 200 cycles) in a pouch cell configuration. Our complex-concentrated anion-doping concept establishes a broadly applicable strategy for resolving chemo-mechanical failure mechanisms in ceramic intercalation electrodes for next-generation energy storage.

Li-ion batteries↗

DOE OSTI2025

Stable Cycling of Sodium All‐Solid‐State Batteries with High‐Capacity Cathode Presodiation

Sodium all-solid-state batteries (NaSSBs) with an alloy-type anode (e.g., Sn and Sb) offer superior capacity and energy density compared to hard carbon anode. However, the irreversible loss of Na + at the alloy anode during the initial cycle results in diminished capacity and stability, impairing full-cell performance. Here, this study presents an easy-to-implement cathode presodiation strategy by employing a Na-rich material to address these challenges. Leveraging the high theoretical capacity and suitable voltage window, Na 2 S is chosen as the Na donor, which is activated by creating a mixed electron-ion conducting network, delivering a high capacity of 511.7 mAh g −1 . By adding a small amount (i.e., 3 wt.%) of Na 2 S to the cathode composite, a NaCrO 2 || Sn full cell demonstrated capacity improvement from 90.8 to 118.2 mAh g −1 (based on cathode mass). The capacity-balanced full cell can thus cycle to more than 300 times with >90% capacity retention. This work provides a practical solution to enhance the full-cell performance and advance the transformation from half-cell to full-cell applications of NaSSBs.

25 - ENERGY STORAGE↗

NASA NTRS1974

Heat-physical properties of lunar surface material returned to earth by the Luna 16 automatic station

Density, specific heat capacity, and coefficient of thermal conductivity were studied on a sample of lunar surface material returned by the Luna 16 automatic station. The study was carried out in a helium-filled chamber. The density of the surface material when freely heaped was 1.2 g/cu cm, and when shaken down -- 1.7 g/cu cm. The specific heat capacity was 0.177 + or - 0.010 cal x g/1 x deg/1. The coefficient of thermal conductivity in the material was 4.8 x 10/6 + or - 1.2 x 10/6 cal x cm/1 x sec/1 x deg/1.

Avduyevskiy, V. S.↗

NASA NTRS2006

Current ISS Exercise Countermeasures: Where are we now?

Current International Space Station (ISS) crew schedules include 1.5 h/d for completion of resistive exercise and 1 h/d of aerobic exercise , 6 d/wk. While ISS post flight decrements in muscle strength, bone m ineral density, and aerobic capacity improved in some crewmembers, de conditioning was still evident even with this volume of exercise. Res ults from early ISS expeditions show maximum loss in bone mineral density of the lumbar spine and pelvis in excess of 1.5% per month, with all crewmembers demonstrating significant bone loss in one or more re gions. Similarly, post flight muscle strength losses in the hamstring and quadriceps muscle groups exceeded 30% in the immediate post miss ion period in some crewmembers. Measures of aerobic capacity early in the mission show average decrements of 15%, but with onboard aerobic exercise capability, the crew has been able to "train up" over the co urse of the mission. These findings are highly variable among crewmem bers and appear to be correlated with availability and reliability of the inflight resistive exercise device (RED), cycle ergometer, and t readmill. This suite of hardware was installed on ISS with limited op erational evaluation in groundbased test beds. As a result, onorbit hardware constraints have resulted in inadequate physical stimulus, d econditioning, and increased risk for compromised performance during intra and extravehicular activities. These issues indicate that the c urrent ISS Countermeasures System reliability or validity are not ade quate for extendedduration exploration missions. Learning Objective: A better understanding of the status of ISS exercise countermeasures , their ability to protect physiologic systems, and recommendations for exploration exercise countermeasures.

Hayes, J. C.↗

DOE OSTI2024

Superionic conducting vacancy-rich β-Li 3 N electrolyte for stable cycling of all-solid-state lithium metal batteries

The advancement of all-solid-state lithium metal batteries requires breakthroughs in solid-state electrolytes (SSEs) for the suppression of lithium dendrite growth at high current densities and high capacities (>3 mAh cm -2 ) and innovation of SSEs in terms of crystal structure, ionic conductivity and rigidness. Here we report a superionic conducting, highly lithium-compatible and air-stable vacancy-rich β-Li 3 N SSE. This vacancy-rich β-Li 3 N SSE shows a high ionic conductivity of 2.14 × 10 -3 S cm -1 at 25 °C and surpasses almost all the reported nitride-based SSEs. A Li- and N-vacancy-mediated fast lithium-ion migration mechanism is unravelled regarding vacancy-triggered reduced activation energy and increased mobile lithium-ion population. All-solid-state lithium symmetric cells using vacancy-rich β-Li 3 N achieve breakthroughs in high critical current densities up to 45 mA cm -2 and high capacities up to 7.5 mAh cm -2 , and ultra-stable lithium stripping and plating processes over 2,000 cycles. The high lithium compatibility mechanism of vacancy-rich β-Li 3 N is unveiled as intrinsic stability to lithium metal. In addition, β-Li 3 N possesses excellent air stability through the formation of protection surfaces. All-solid-state lithium metal batteries using the vacancy-rich β-Li 3 N as SSE interlayers and lithium cobalt oxide (LCO) and Ni-rich LiNi 0.83 Co 0.11 Mn 0.06 O 2 (NCM83) cathodes exhibit excellent battery performance. Extremely stable cycling performance is demonstrated with high capacity retentions of 82.05% with 95.2 mAh g -1 over 5,000 cycles at 1.0 C for LCO and 92.5% with 153.6 mAh g -1 over 3,500 cycles at 1.0 C for NCM83. Utilizing the vacancy-rich β-Li 3 N SSE and NCM83 cathodes, the all-solid-state lithium metal batteries successfully accomplished mild rapid charge and discharge rates up to 5.0 C, retaining 60.47% of the capacity. Notably, these batteries exhibited a high areal capacity, registering approximately 5.0 mAh cm -2 for the compact pellet-type cells and around 2.2 mAh cm -2 for the all-solid-state lithium metal pouch cells.

25 ENERGY STORAGE↗

DOE OSTI2023

Interface Design for High‐Performance All‐Solid‐State Lithium Batteries

All‐solid‐state batteries suffer from high interface resistance and lithium dendrite growth leading to low Li plating/stripping Coulombic efficiency (CE) of <90% and low critical current density at high capacity. Here, in this work, both challenges are simultaneously addressed and the Li plating/stripping CE is significantly increased to 99.6% at 0.2 mA cm −2 /0.2 mAh cm −2 , and critical current density (CCD) of > 3.0 mA cm −2 /3.0 mAh cm −2 by inserting a mixed ionic‐electronic conductive (MIEC) and lithiophobic LiF‐C‐Li 3 N‐Bi nanocomposite interlayer between Li 6 PS 5 Cl electrolyte and Li anode. The highly lithiophobic LiF‐C‐Li 3 N‐Bi interlayer with high ionic conductivity (10 −5 S cm −1 ) and low electronic conductivity (3.4×10 −7 S cm −1 ) enables Li to plate on the current collector (CC) surface rather than on Li 6 PS 5 Cl surface avoiding Li 6 PS 5 Cl electrolyte reduction. During initial Li plating on CC, Li penetrates into porous LiF‐C‐Li 3 N‐Bi interlayer and lithiates Bi nanoparticles into Li 3 Bi. The lithiophilic Li 3 Bi and Li 3 N nanoparticles in LiF‐C‐Li 3 N‐Li 3 Bi sub‐interlayer will move to CC along with plated Li, forming LiF‐C/Li 3 N‐Li 3 Bi lithiophobic/lithiophilic sublayer during the following Li stripping. This interlayer enables Co 0.1 Fe 0.9 S 2 /Li 6 PS 5 Cl/Li cell with an areal capacity of 1.4 mAh cm −2 to achieve a cycle life of >850 cycles at 150 mA g −1 . The lithiophobic/lithiophilic interlayer enables solid‐state metal batteries to simultaneously achieve high energy and long cycle life.

25 ENERGY STORAGE↗

DOE OSTI2025

A novel approach for large-scale wind energy potential assessment

Increasing wind energy generation is central to grid decarbonization, yet methods to estimate wind energy potential are not standardized, leading to inconsistencies and even skewed results. This study aims to improve the fidelity of wind energy potential estimates through an approach that integrates geospatial analysis and machine learning (i.e., Gaussian process regression). We demonstrate this approach to assess the spatial distribution of wind energy capacity potential in the Contiguous United States (CONUS). We find that the capacity-based power density ranges from 1.70 MW/km2 (25th percentile) to 3.88 MW/km2 (75th percentile) for existing wind farms in the CONUS. The value is lower in agricultural areas (2.73 ± 0.02 MW/km2, mean ± 95 % confidence interval) and higher in other land cover types (3.30 ± 0.03 MW/km2). Notably, advancements in turbine manufacturing could reduce power density in areas with lower wind speeds by adopting low specific-power turbines, but improve power density in areas with higher wind speeds (>8.35 m/s at 120m above the ground), highlighting opportunities for repowering existing wind farms. Wind energy potential is shaped by wind resource quality and is regionally characterized by land cover and physical conditions, revealing significant capacity potential in the Great Plains and Upper Texas. The results indicate that areas previously identified as hot spots using existing approaches (e.g., the west of the Rocky Mountains) may have a limited capacity potential due to low wind resource quality. Improvements in methodology and capacity potential estimates in this study could serve as a new basis for future energy systems analysis and planning.

Dai, Tao↗

DOE OSTI2024

Macroscopic Traffic Modeling Using Probe Vehicle Data: A Machine Learning Approach

Abstract The macroscopic fundamental diagram (MFD) captures an orderly relationship among traffic flow, density, and speed at the network level. It is a simple yet powerful tool for modeling traffic dynamics in large urban networks with broad application in traffic control and management. However, empirically derived MFDs in urban regions require high-resolution traffic data from the network. Having the network flow and vehicular density estimated at the (granular) census tract level using vehicle probe data, we apply machine learning methods to predict the MFDs across U.S. urban areas and capture the impacts of location-specific input features on the network flow–density relationships at a large scale. The results show that, among the four tested machine learning approaches (Random Forest, XGBoost, Support Vector Machine, and Neural Network), XGBoost delivers the best performance in predicting network traffic flow based on vehicular density and location attributes. Using interaction Shapley Additive explanation (SHAP) values and partial correlation analysis, we examine the factors influencing MFD shapes across different locations. Our empirical findings reveal that across U.S. urban areas, network topology, transportation infrastructure, and land use are primary factors shaping MFD curves, while demand and trip-related factors play a lesser role. Specifically, higher ranking roads, centrality, and development levels correlate positively with network capacity and critical density, whereas negative associations are observed for network connectivity, mixed-use development, and road roughness levels.

Jin, Ling↗

DOE OSTI2025

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

DOE OSTI2025

Disordered Rocksalts as High‐Energy and Earth‐Abundant Li‐Ion Cathodes

To address the growing demand for energy and support the shift toward transportation electrification and intermittent renewable energy, there is an urgent need for low‐cost, energy‐dense electrical storage. Research on Li‐ion electrode materials has predominantly focused on ordered materials with well‐defined lithium diffusion channels, limiting cathode design to resource‐constrained Ni‐ and Co‐based oxides and lower‐energy polyanion compounds. Recently, disordered rocksalts with lithium excess (DRX) have demonstrated high capacity and energy density when lithium excess and/or local ordering allow statistical percolation of lithium sites through the structure. This cation disorder can be induced by high temperature synthesis or mechanochemical synthesis methods for a broad range of compositions. DRX oxides and oxyfluorides containing Earth‐abundant transition metals have been prepared using various synthesis routes, including solid‐state, molten‐salt, and sol‐gel reactions. This review outlines DRX design principles and explains the effect of synthesis conditions on cation disorder and short‐range cation ordering (SRO), which determines the cycling stability and rate capability. In addition, strategies to enhance Li transport and capacity retention with Mn‐rich DRX possessing partial spinel‐like ordering are discussed. Finally, the review considers the optimization of carbon and electrolyte in DRX materials and addresses key challenges and opportunities for commercializing DRX cathodes.

Li-ion batteries↗

DOE OSTI2024

Ab-initio molecular dynamics study of eutectic chloride salt: MgCl2–NaCl–KCl

Ionic liquid materials are viable candidates as a heat transfer fluid (HTF) in a wide range of applications, notably within concentrated solar power (CSP) technology and molten salt reactors (MSRs). For next-generation CSP and MSR technologies that strive for higher power generation efficiency, a HTF with wide liquid phase range and energy storage capabilities is crucial. Studies have shown that eutectic chloride salts exhibit thermal stability at high temperatures, high heat storage capacity, and are less expensive than nitrate and carbonate salts. However, the experimental data needed to fully evaluate the potential of eutectic chloride salts as a HTF contender are scarce and entail large uncertainties. Considering the high cost and potential hazards associated with the experimental methods used to determine the properties of ionic liquids, molecular modeling can be used as a viable alternative resource. In this study, the eutectic ternary chloride salt MgCl 2 –NaCl–KCl is modeled using ab-initio molecular dynamics simulations (AIMDs) in the liquid phase. Using the simulated data, the thermophysical and transport properties of eutectic chloride salt can be calculated: density, viscosity, heat capacity, diffusion coefficient, and ionic conductivity. For an initial model validation, experimental pair-distribution function data were obtained from X-ray total scattering techniques and compared to the theoretical pair-distribution function. Additionally, theoretical viscosity values are compared to experimental viscosity values for a similar system. The results provide a starting foundation for a MgCl 2 –NaCl–KCl model that can be extended to predict other fundamental properties.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2025

Tuning Cation (Dis)Order in Cr‐Based Li‐Excess Oxide Cathode Materials to Improve Li+ Transport Properties

Abstract Li‐excess disordered rocksalts (DRXs) hold promise as next‐generation cathodes for Li‐ion batteries due to their high capacity and energy density, along with the potential to eliminate the need for Co and Ni. However, due to their low Li + diffusivity, DRXs need to be pulverized into nanoparticles to achieve high performance. Herein, a new strategy for overcoming this limitation is demonstrated, involving the design of as‐synthesized partially disordered oxides with a structure that lies between ordered layered and fully disordered, exhibiting a varying degree of local (dis)order. This unique structure activates new Li + diffusion channels, improving percolation and transport properties. This strategy allows a large content of Li + to be accessed in material with large, micron‐sized particles through highly reversible Cr 3+/6+ and O redox, yielding a first discharge capacity of 286 mAh g −1 (881 Wh kg −1 ). The Li + percolation network is further improved by substituting Ti with a mixture of multiple metals, which appears to locally decrease the migration barrier through lattice distortion. Proper tuning of the chemical composition, especially the content of metals with empty d orbitals, is established as a crucial factor for controlling the degree of disorder and mitigating voltage fade and hysteresis growth upon cycling.

Moździerz, Maciej↗

NASA NTRSDate not supplied

Influence of Thermophysical Property Variability on Thermal Predictions of Ti-6Al-4V

The additive manufacturing (AM) industry has experienced rapid growth in recent decades as industrial interest in the process has grown. Because of this, there are many groups interested in simulations of the AM process. However, the influence of thermophysical property variability on the melt pool geometry during processing of various AM alloys is unclear. The goal of my work at NASA Langley Research Center (LaRC) was to characterize this influence on Ti-6Al-4V during AM processing alongside developing a tool to enable equivalent studies on other AM materials. To facilitate this process, a database tool was developed to contain and organize thermophysical data previously reported by primary sources. The specific thermophysical properties of interest for this study were density, specific heat capacity, and conductivity. Thermal diffusivity was calculated using the other three properties. This data was then fit with a Gaussian distribution and then randomly sampled from using Monte Carlo random value sampling. Using the Rosenthal equation, this sample data was used to simulate the temperature field during additive manufacturing and extract the melt pool geometry. Specifically, the melt pool’s length, width, and depth. This process was repeated an arbitrary number of times, with the default being 1000. Once this information was obtained, histograms were made showing the distributions of the sizes of the melt pool’s length, width, and depth. Representative statistical metrics of the distributions were calculated (mean, standard deviation, and coefficient of variance). This work found that at the simulated processing values, the melt pool’s width and depth had a 5.7% variation while the length had a 3.2% variation. Additionally, a tool was constructed to graph a thermal color map representation of the melt pool for specific, arbitrary values of density, specific heat, and conductivity. This tool allowed for more efficient plotting of individual queries of the thermophysical properties. The results that were observed in the research were that values reported in literature vary and this variance can have a significant impact on the simulation. Predictions of the melt pool’s dimensions show that length has a standard deviation of approximately 6 μm, width has a standard deviation of approximately 5 μm, and depth can vary by approximately 3 μm. Considering the mean sizes of length, width, and depth are 185 μm, 88 μm, and 44 μm respectively, such a deviation is significant. This shows that depth, for example, could be more than 10% larger or smaller than expected. This demonstrates that variability in the reported thermophysical properties are not negligible and should be expected to have an influence on the results of the laser powder bed fusion additive manufacturing process. When simulating this process in the future, measures should be taken to account for this discrepancy and the uncertainty involved

Justin Martin↗

DOE OSTI2026

The Influence of Mesoscale Particle Structure on the Electrode Degradation and Resultant Electrochemistry of Lithium Ion Cells With Nickel Rich Lithium Nickel Manganese Cobalt Oxide Positive Electrodes

Nickel-rich lithium nickel manganese cobalt oxide, NMC (LiNi x Mn y Co z O 2 ), materials are desirable positive electrodes in lithium ion batteries, providing high capacity and energy density. The mesoscale structure of NMC materials is commonly a polycrystalline aggregate, providing opportunity for short lithium ion transport distance of the small primary particles, yet facile material handling due to the larger secondary particles. On (de)lithiation the NMC unit cell changes volume, where the anisotropic strain can result in secondary particle fracture. This secondary particle fracture process during cycling has been associated with several degradation modes of NMC materials in LIBs. In this work, a milling process was determined whereby the secondary particles could be pre-fractured with retention of the parent primary particle crystallographic structure, crystallite size, and morphology, providing the ability to unambiguously determine the influence of NMC secondary particle size and mesostructure on resultant functional behavior. The bulk and interfacial properties and electrochemistry of as-received commercially obtained polycrystal NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 , PC NMC) and its milled MPC NMC counterpart were compared. The smaller secondary particle size, higher surface area MPC NMC was found to result in 1) greater cathode tortuosity, 2) reduced surface Ni on the cycled MPC cathodes consistent with surface reconstruction, and 3) increased Ni deposition on the anodes from cathode-anode crosstalk. These factors manifested in unfavorable electrochemical behavior of MPC with lower functional capacity at both 1C and C/10 rates and higher impedance over extended moderate voltage (dis)charge cycling.

36 MATERIALS SCIENCE↗