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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

How hydrophobicity, side chains, and salt affect the dimensions of disordered proteins

Abstract Despite the generally accepted role of the hydrophobic effect as the driving force for folding, many intrinsically disordered proteins (IDPs), including those with hydrophobic content typical of foldable proteins, behave nearly as self‐avoiding random walks (SARWs) under physiological conditions. Here, we tested how temperature and ionic conditions influence the dimensions of the N‐terminal domain of pertactin (PNt), an IDP with an amino acid composition typical of folded proteins. While PNt contracts somewhat with temperature, it nevertheless remains expanded over 10–58°C, with a Flory exponent, ν , >0.50. Both low and high ionic strength also produce contraction in PNt, but this contraction is mitigated by reducing charge segregation. With 46% glycine and low hydrophobicity, the reduced form of snow flea anti‐freeze protein (red‐sfAFP) is unaffected by temperature and ionic strength and persists as a near‐SARW, ν ~ 0.54, arguing that the thermal contraction of PNt is due to stronger interactions between hydrophobic side chains. Additionally, red‐sfAFP is a proxy for the polypeptide backbone, which has been thought to collapse in water. Increasing the glycine segregation in red‐sfAFP had minimal effect on ν . Water remained a good solvent even with 21 consecutive glycine residues ( ν > 0.5), and red‐sfAFP variants lacked stable backbone hydrogen bonds according to hydrogen exchange. Similarly, changing glycine segregation has little impact on ν in other glycine‐rich proteins. These findings underscore the generality that many disordered states can be expanded and unstructured, and that the hydrophobic effect alone is insufficient to drive significant chain collapse for typical protein sequences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Role of surface wetting on tribological behavior for laser nanotextured steel using ionic liquid lubricants

Here, this research evaluates the effect of surface wettability on the tribological performance through ball-on-flat tribology testing. The substrate material, M2 tool steel, is laser processed and then functionalized with fluorocarbon and nitrile chemistry to achieve distinct oleophobicity and oleophilicity, respectively, but with a similar nanoscale surface texture. The baseline lubricant is poly-alpha-olefin (PAO) oil, and ionic liquids (ILs) are used as additives for this study. The interaction between the nanoscale textured steel surface and ionic liquid-based oils is investigated. A set of reciprocating wear tests are performed to investigate the tribological behavior of the tribo-system consisting of the surface-engineered, flat M2 tool steel specimen and a standard, surface-polished steel ball. Results show that the oleophobic flat surface results in a lower friction, while the oleophilic surface modification leads to a better wear protection to the flat surface. Ammonium-based IL provides the highest friction reduction, while the phosphonium-based ILs provide an improved wear protection.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Inhibition of asphaltene aggregation using deep eutectic solvents: COSMO-RS calculations and experimental validation

Asphaltene precipitation/deposition adversely affects various oil and gas processes, such as oil recovery, transportation, and petroleum processing. The resulting increase in viscosity of crude oil decreases distillate yields creating unstable phase separation. Deep eutectic solvents (DESs) have recently gained interest as inhibitors of asphaltene aggregation. The goal of the present study is to derive the mechanism of inhibition of petroleum asphaltene aggregation by a novel screening of DESs. An archipelago-based chemical structure of asphaltene was adopted for performing quantum chemical calculations. The structure was used in the conductor-like screening model for real solvents (COSMO-RS) model to screen potential DESs for asphaltene precipitation. It was found that DESs containing thymol were the most promising of the 153 DES combinations screened. The COSMO-RS predictions were validated experimentally using solubility data of asphaltene in DESs. Among the studied DESs, thymol-diphenyl ether provided the highest solubility for asphaltene, which was further validated using the experimental and the COSMO-RS predicted data. In addition, to characterize the structural interactions between asphaltene and DESs, Fourier transform infrared (FTIR) spectroscopy and nuclear magnetic resonance (NMR) measurements were performed. It was found that strong interaction between asphaltene and the DESs is responsible for the higher asphaltene dispersion. Finally, the present approach opens pathways to rationally design and understand the impact of structural variation of DESs based on their interactions with asphaltene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Influence of Charge Fraction on the Phase Behavior of Symmetric Single-Ion Conducting Diblock Copolymers

A series of symmetric poly[(oligo(ethylene glycol) methyl ether methacrylate-co-oligo(ethylene glycol) propyl sodium sulfonate methacrylate)]-block-polystyrene (PsOEGMA-PS) diblock copolymers were synthesized as a model system to probe the effect of charge fraction on the phase behavior of charged-neutral single-ion conducting diblock copolymers. Small-angle X-ray scattering (SAXS) experiments showed that increasing the charge fraction does not alter the ordered phase morphology (lamellar) but increases the order–disorder transition temperature (T ODT ) significantly. Additionally, the effective Flory–Huggins interaction parameter (χ eff ) was found to increase linearly with the charge fraction, similar to the case of conventional salt-doped diblock copolymers. This indicates that the effect of counterion solvation, attributed to the significant mismatch between the dielectric constant of each block, provides the dominant effect in tuning the phase behavior of this charged diblock copolymer. Lastly, we therefore infer that electrostatic cohesion (local charge ordering induced by Coulombic interactions), which is predicted to suppress microphase separation and lead to asymmetric phase diagrams, only plays a minor role in this model system.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Molecular-Scale Characterization of Photoinduced Charge Separation in Mixed-Dimensional InSe–Organic van der Waals Heterostructures

Layered indium selenide (InSe) is an emerging two-dimensional semiconductor that has shown significant promise for high-performance transistors and photodetectors. The range of optoelectronic applications for InSe can potentially be broadened by forming mixed-dimensional van der Waals heterostructures with zero-dimensional molecular systems that are widely employed in organic electronics and photovoltaics. Here, we report the spatially resolved investigation of photoinduced charge separation between InSe and two molecules (C 70 and C 8 -BTBT) using scanning tunneling microscopy combined with laser illumination. We experimentally and computationally show that InSe forms type-II and type-I heterojunctions with C 70 and C 8 -BTBT, respectively, due to an interplay of charge transfer and dielectric screening at the interface. Laser-excited scanning tunneling spectroscopy reveals a ~0.25 eV decrease in the energy of the lowest unoccupied molecular orbital of C 70 with optical illumination. Furthermore, photoluminescence spectroscopy and Kelvin probe force microscopy indicate that electron transfer from InSe to C 70 in the type-II heterojunction induces a photovoltage that quantitatively matches the observed downshift in the tunneling spectra. In contrast, no significant changes are observed upon optical illumination in the type-I heterojunction formed between InSe and C 8 -BTBT. Density functional theory calculations further show that, despite the weak coupling between the molecular species and InSe, the band alignment of these mixed-dimensional heterostructures strongly differs from the one suggested by the ionization potential and electronic affinities of the isolated components. Self-energy-corrected density functional theory indicates that these effects are the result of the combination of charge redistribution at the interface and heterogeneous dielectric screening of the electron–electron interactions in the heterostructure. In addition to providing specific insight for mixed-dimensional InSe–organic van der Waals heterostructures, this work establishes a general experimental methodology for studying localized charge transfer at the molecular scale that is applicable to other photoactive nanoscale systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Tunable chiral and nematic states in the triple-Q antiferromagnet Co 1/3 TaS 2

Complex spin configurations in magnetic materials, ranging from collinear single-Q to non-coplanar multi-Q states, exhibit rich symmetry and chiral properties. However, their detailed characterization is often hindered by the limited spatial resolution of neutron diffraction techniques. Here we employ magnetic circular dichroism and magnetic linear dichroism to investigate the triangular lattice antiferromagnet Co 1/3 TaS 2 , revealing three-state (Z 3 ) nematicity and also spin chirality across its multi-Q magnetic phases. At intermediate temperatures, the presence of linear dichroism identifies nematicity arising from a single-Q stripe phase, while at high magnetic fields and low temperatures, a phase characterized solely by circular dichroism emerges, signifying a purely chiral non-coplanar triple-Q state. Notably, at low temperatures and small fields, we discover a unique phase where both chirality and nematicity coexist. A theoretical analysis based on a continuous multi-Q manifold captures the emergence of these distinct magnetic phases, as a result of the interplay between four-spin interactions and weak magnetic anisotropy. Additionally, both circular and linear dichroism microscopy spatially resolves the chiral and nematic domains. Our findings establish Co 1/3 TaS 2 as a rare platform hosting diverse multi-Q states with distinct combinations of spin chirality and nematicity while demonstrating the effectiveness of polarized optical techniques in characterizing complex magnetic textures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Versatile multi-energy hard x-ray camera to study confined and unconfined fast electron dynamics and anisotropies (Invited)

A powerful and flexible hard x-ray (HXR) camera has been recently installed and tested on the WEST tokamak (CEA, France) in collaboration with the Princeton Plasma Physics Laboratory. The diagnostic is a pinhole camera fielded with a 2D pixel detector equipped with a 1 mm thick CdTe sensor. The novelty of this diagnostic technique is the detector’s capability of adjusting the threshold energy at the pixel level. This innovation provides great flexibility in the energy configuration, allowing simultaneous space, energy, and time resolved x-ray measurements. The novel camera has been used to measure the core radiation from non-Maxwellian (fast) electrons accelerated by Lower Hybrid (LH) waves and also the beam–target emission of tungsten in the divertor region produced by fast electron losses interacting with the target. In addition, anisotropic hard x-ray emission has been detected for the first time at the WEST core and edge plasma, with opposite toroidal intensity trends. Finally, experimental vertical and toroidal HXR profiles have been successfully reproduced with the LH code LUKE.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Toward improved property prediction of 2D materials using many-body quantum Monte Carlo methods

The field of 2D materials has grown dramatically in the past two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic, clean energy, and quantum computing applications. These 2D structures, which are often exfoliated from layered van der Waals materials, possess highly inhomogeneous electron densities and can possess short- and long-range electron correlations. The complexities of 2D materials make them challenging to study with standard mean-field electronic structure methods such as density functional theory (DFT), which relies on approximations for the unknown exchange-correlation functional. To overcome the limitations of DFT, highly accurate many-body electronic structure approaches such as diffusion Monte Carlo (DMC) can be utilized. In the past decade, DMC has been used to calculate accurate magnetic, electronic, excitonic, and topological properties in addition to accurately capturing interlayer interactions and cohesion and adsorption energetics of 2D materials. Here, this approach has been applied to 2D systems of wide interest, including graphene, phosphorene, MoS 2 , CrI 3 , VSe 2 , GaSe, GeSe, borophene, and several others. In this review article, we highlight some successful recent applications of DMC to 2D systems for improved property predictions beyond standard DFT.

2D materials↗
DOE OSTI2021

KPC-2 β-lactamase enables carbapenem antibiotic resistance through fast deacylation of the covalent intermediate

Serine active-site β-lactamases hydrolyze β-lactam antibiotics through the formation of a covalent acyl-enzyme intermediate followed by deacylation via an activated water molecule. Carbapenem antibiotics are poorly hydrolyzed by most β-lactamases owing to slow hydrolysis of the acyl-enzyme intermediate. However, the emergence of the KPC-2 carbapenemase has resulted in widespread resistance to these drugs, suggesting it operates more efficiently. Here, we investigated the unusual features of KPC-2 that enable this resistance. We show that KPC-2 has a 20,000-fold increased deacylation rate compared with the common TEM-1 β-lactamase. Furthermore, kinetic analysis of active site alanine mutants indicates that carbapenem hydrolysis is a concerted effort involving multiple residues. Substitution of Asn170 greatly decreases the deacylation rate, but this residue is conserved in both KPC-2 and non-carbapenemase β-lactamases, suggesting it promotes carbapenem hydrolysis only in the context of KPC-2. X-ray structure determination of the N170A enzyme in complex with hydrolyzed imipenem suggests Asn170 may prevent the inactivation of the deacylating water by the 6α-hydroxyethyl substituent of carbapenems. In addition, the Thr235 residue, which interacts with the C3 carboxylate of carbapenems, also contributes strongly to the deacylation reaction. In contrast, mutation of the Arg220 and Thr237 residues decreases the acylation rate and, paradoxically, improves binding affinity for carbapenems. Thus, the role of these residues may be ground state destabilization of the enzyme-substrate complex or, alternatively, to ensure proper alignment of the substrate with key catalytic residues to facilitate acylation. These findings suggest modifications of the carbapenem scaffold to avoid hydrolysis by KPC-2 β-lactamase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Frontiers and opportunities in bioenergy crop microbiome research networks

Researchers from across the four U.S. Department of Energy Bioenergy Research Centers engaged in a microbiome workshop that focused on identifying challenges and collaboration opportunities to better understand bioenergy-relevant plant–microbe interactions. The virtual workshop included hands-on educational sessions and a keynote address on current best practices in microbiome science and community microbiome standards, as well as breakout sessions aimed at identifying microbiome-related data and measurements that should be prioritized, opportunities for and barriers to integrating plant metabolites to microbiome research, and strategies for more effectively integrating microbiome data and processes into existing models. Based on participant discussion, key findings of the workshop were the need to prioritize scaling data sharing across BRCs and the broader research community and securing collaborative infrastructure in the areas of microbiome-ecosystem modeling and molecular plant-microbe interactions. This workshop review highlights additional main findings from this event, to encourage cross-site and more holistic meta-analyses while promoting wide scientific community engagement across plant microbiome sciences.

09 BIOMASS FUELS↗
DOE OSTI2024

Measurements of jet cross-section ratios in 13 TeV proton-proton collisions with ATLAS

Measurements of jet cross-section ratios between inclusive bins of jet multiplicity are performed in 140 fb -1 of proton-proton collisions with √s = 13 TeV center-of-mass energy, recorded with the ATLAS detector at CERN’s Large Hadron Collider. These ratios are constructed from double-differential cross-section measurements that are made in bins of jet multiplicity and other observables that are sensitive the energy scale and angular distribution of radiation due to the strong interaction in the final state. Additionally, the scalar sum of the two leading jets’ transverse momenta is measured triple differentially, in bins of the third jet’s transverse momentum and of jet multiplicity. These measurements are unfolded to account for acceptance and detector-related effects. The measured distributions are used to construct ratios of the inclusive jet-multiplicity bins, which have been shown to be sensitive to the strong coupling Formula Presented while being less sensitive than other observables to systematic uncertainties and parton distribution functions. The measured distributions are compared with state-of-the-art QCD calculations, including next-to-next-to-leading-order predictions for two- and three-jet events. These predictions are generally found to model the data well and perform best in bins with a modest requirement on the third jet’s transverse momentum. Significant differences between data and Monte Carlo predictions are observed in events with large rapidity gaps and invariant masses of the leading jet pair. Studies leading to reduced jet energy scale uncertainties significantly improve the precision of this work and are documented herein.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Understanding the selectivity of nonsteroidal anti-inflammatory drugs for cyclooxygenases using quantum crystallography and electrostatic interaction energy

Quantum crystallography methods have been employed to investigate complex formation between nonsteroidal anti-inflammatory drugs (NSAIDs) and cyclooxygenase (COX) enzymes, with particular focus on the COX-1 and COX-2 isoforms. This study analyzed the electrostatic interaction energies of selected NSAIDs (flurbiprofen, ibuprofen, meloxicam and celecoxib) with the active sites of COX-1 and COX-2, revealing significant differences in binding profiles. Flurbiprofen exhibited the strongest interactions with both COX-1 and COX-2, indicating its potent binding affinity. Celecoxib and meloxicam showed a preference for COX-2, consistent with their known selectivity for this isoform, while ibuprofen showed comparable interaction energies with both isoforms, reflecting its nonselective inhibition pattern. Key amino-acid residues, including Arg120, Arg/His513 and Tyr355, were identified as critical determinants of NSAID selectivity and binding affinity. The findings highlight the complex interplay between interaction energy and selectivity, suggesting that while electrostatic interactions play a fundamental role, additional factors such as enzyme dynamics and the hydrophobic effect also contribute to the therapeutic efficacy and safety profiles of NSAIDs. These insights provide valuable guidance for the rational design of NSAIDs with enhanced therapeutic benefits and minimized adverse effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Parallel Algorithms for Efficient Computation of High-Order Line Graphs of Hypergraphs

This paper considers structures of systems beyond dyadic (pairwise) interactions and investigates mathematical modeling of multi-way interactions and connections as hypergraphs, where captured relationships among system entities are set-valued. To date, in most situations, entities in a hypergraph are considered connected as long as there is at least one common ``neighbor''. However, minimal commonality sometimes discards the ``strength'' of connections and interactions among groups. To this end, considering the ``width'' of a connection, referred to as the \emph{$s$-overlap} of neighbors, provides more meaningful insights into how closely the communities or entities interact with each other. In addition, $s$-overlap computation is the fundamental kernel to construct the line graph of a hypergraph, a low-order approximation of the hypergraph which can carry significant information about the original hypergraph. Subsequent stages of a data analytics pipeline then can apply highly-tuned graph algorithms on the line graph to reveal important features. Given a hypergraph, computing the $s$-overlaps by exhaustively considering all pairwise entities can be computationally prohibitive. To tackle this challenge, we develop efficient algorithms to compute $s$-overlaps and the corresponding line graph of a hypergraph. We propose several heuristics to avoid execution of redundant work and improve performance of the $s$-overlap computation. Our parallel algorithm, combined with these heuristics, is orders of magnitude (more than $10\times$) faster than the naive algorithm in all cases and the SpGEMM algorithm with filtration in most cases (especially with large $s$ value).

hypergraph algorithms, graph algorithms, parallel ↗
DOE OSTI2022

Heavy Duty Commercial Vehicle Platooning Energy Benefits for Conventional and Electrified Powertrains

Heavy duty vehicle platooning under highway operating conditions, has been projected to provide significant fuel economy gains based on aerodynamic drag improvements of the platooning vehicles. Realizing these benefits under real-world operating conditions presents several challenges. This paper (the first as part of series) provides a framework to quantify the fuel economy benefits of both conventional and electrified powertrains operating across the U.S. Interstate highway system. In addition to the powertrain, key interactions that are explored include the vehicle separation distance, baseline vehicle aerodynamic properties, vehicle weight, number of vehicles in the platoon, excursions from road speed limits, and particular traffic interactions. While the approach makes use of a limited fidelity vehicle model for longitudinal dynamics, the narrative provides application decision personnel with a mechanism and well-defined set of fuel economy impact factors to consider as part of their architecture selection process.

Sujan, Vivek↗
DOE OSTI2023

Cryo-EM structure of the human Sirtuin 6–nucleosome complex

Sirtuin 6 (SIRT6) is a multifaceted protein deacetylase/deacylase and a major target for small-molecule modulators of longevity and cancer. In the context of chromatin, SIRT6 removes acetyl groups from histone H3 in nucleosomes, but the molecular basis for its nucleosomal substrate preference is unknown. Our cryo–electron microscopy structure of human SIRT6 in complex with the nucleosome shows that the catalytic domain of SIRT6 pries DNA from the nucleosomal entry-exit site and exposes the histone H3 N-terminal helix, while the SIRT6 zinc-binding domain binds to the histone acidic patch using an arginine anchor. In addition, SIRT6 forms an inhibitory interaction with the C-terminal tail of histone H2A. The structure provides insights into how SIRT6 can deacetylate both H3 K9 and H3 K56.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Towards Three-Dimensional Neutron Imaging with Light-field Technology

A broad range of applications in nuclear safeguards and security can benefit from compact, fast neutron imagers with large angular acceptance. However, accurate 3D multi-vertex reconstruction in a monolithic detector remains a significant barrier to realization. Current approaches, such as the centroiding approach and the use of shadow masks, have not yet resulted in a successful demonstration in a light-starved environment. This project explored the use of cutting-edge technology—a light field camera—which inherently preserves both the spatial and directional information of incident light. Such technology can, in principle, resolve multi-vertex events and offer accurate position reconstruction in 3D with relatively simple readout electronics. Since the project's inception in May 2023, we have built an experimental setup to calibrate and characterize a commercial light-field camera (Lytro Illum). We assessed its 3D event reconstruction capability in a relatively low-light intensity environment by analyzing the cross-correlation of a series of 2D images of a characterized tunable light source taken at various distances. A sub-cm resolution, lower than typical neutron interaction separations in a compact scintillator volume, was observed with the LED light source, suggesting the promising capability of its nominal optics design to provide the adequate resolution required for a compact monolithic neutron directional detector. However, using a light-field-based readout for a neutron camera requires incorporating an ultra-low-noise light sensor, which is beyond the scope of this project. We also initiated the development of a 3D light-field-based reconstruction algorithm tailored to sparse scenes, as expected from particle interactions in a scintillator medium. Additionally, we demonstrated the capability of the algorithm to replicate the ground truth. Finally, we began the development of a neutron directional detector simulation to determine the performance criteria for light-field-based reconstruction that allows for good neutron directional reconstruction. This Feasibility Study has led to a successful follow-up project under the DNN R&D innovation portfolio starting May 2024.

42 ENGINEERING↗
DOE OSTI2025

Cost and Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural Gas to Electricity

This report presents an independent assessment of the cost and performance of select fossil energy power systems—pulverized coal (PC) and natural gas combined cycle (NGCC) plants—using a systematic, transparent, technical, and economic approach. This is Volume 1 of the baseline series: Bituminous Coal and Natural Gas to Electricity. The cost and performance of fossil fuel‐based generation technologies represented in this report are important inputs to assessments and determinations of technology combinations to be utilized to meet the projected demands of future power markets. From a research and development perspective, this report is used to assess goals and metrics and to provide a consistent basis for comparing developing technologies. The main report consists of fifteen power plant configurations, six PC cases (with and without carbon capture) nine NGCC cases (with and without carbon capture) and few additional cases of higher capture rate, for both PC and NGCC plants in the appendix. In addition to the report, an interactive tool was developed that allows users to manipulate six key study parameters simultaneously for each case and visualize the impact on three metrics: 1) levelized cost of electricity (LCOE), 2) cost of CO 2 capture (CCC), and 3) cost of CO 2 avoided (CCA). Following is the link to the interactive tool: https://netl.doe.gov/NETLVol1BaselineTool

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Zentropy Theory for Transformative Functionalities of Magnetic and Superconducting Materials

The proposed research developed the zentropy theory through applications to complex magnetic materials and superconductors under the hypothesis that the emergent properties of complex magnetic materials and superconductors can be predicted by statistical mechanics of ergodic microstates with their partition functions computed from DFT-predicted free energies. The key objective is to develop approaches to systematically determine the types and number of microstates and the supercell size in DFT-based calculations through convergency of macroscopic functionalities, with the incorporation of our mixed-space approach accounting for the interactions between periodic supercells. In addition to use scientific intuitions to guide the design of important microstates, the key innovation of the proposed research is to integrate the domain knowledge and the material-property-descriptor database (MPDD) with 4 million microstates, which is supported by our deep neural network machine learning models (SIPFENN: structure-informed prediction of formation energy using neural networks) and integrated with our high throughput DFT Tool Kit (DFTTK). For complex magnetic materials, one of the objectives is to develop approaches to calculate short-range ordering from the statistical distribution of each microstate. For superconductors, the divergency of quasiparticle effective mass at a quantum critical point will be investigated, and the superconducting and non-superconducting microstates will be delineated through analysis of electronic band structure, density of states, charge density, and Fermi surface.

36 MATERIALS SCIENCE↗