Generate a single crystal structure for a given composition using OMatG.

Generate completely novel crystal structures using OMatG. The model samples atomic species, positions, and lattice vectors from scratch to create new materials.

Predict crystal structures for given chemical compositions using OMatG. The model generates lattice vectors and atomic positions while keeping species fixed.

OMatG is a generative model for crystal structure prediction (CSP) and de novo generation of inorganic materials.

Determining whether low-energy P1 structures hide higher-symmetry configurations and if more sampling could find them. The team ran three experiments to see why many of the lowest-energy structures end up in P1 (triclinic) symmetry and whether better structures exist. They found that the main problem is not hidden symmetry in P1, but too little sampling: only about 15 trials per formula leaves much of the energy landscape unexplored. Overall, increasing trials and sampling breadth can reveal better, more stable phases.

Gold memberships are back on Ouro. This is just the starting point, and the perks will grow over time.

WTI crude is set for a modest grind higher, with prices forecast to reach $61.23/bbl by 2026-04-12 (up 3.1% from $59.39 on 2026-01-18) as the market shifts from a fading Iran war-premium spike to a tighter—but not crisis-level—fundamental balance. Rather than a new bull trend, this move reflects a gradual rebuilding of a moderate geopolitical risk premium and steady underlying demand tightening, which together anchor WTI in the low-$60s over the next three months.

Gold futures are poised for a controlled grind higher rather than a breakout, with prices expected to rise about 2.0% from 4,604.3 (18 Jan 2026) to 4,698.7 by 12 Apr 2026 as higher-for-longer US real yields cap upside but fail to trigger a deeper correction. With most hawkish Fed repricing already absorbed and gold holding near record levels, the balance of risks tilts modestly bullish, underpinned by sticky central‑bank and strategic demand amid structurally elevated geopolitical and fiat‑credibility concerns.

Forecasts for Crude Oil Price (WTI) with 12-period horizon (weekly)

Forecasts for Gold Futures with 12-period horizon (weekly)

Silver futures are positioned for a regime‑shift rally from 84.61 to 186.78 by 2026‑04‑12 (+120.8% in ~12 weeks), with a sustained, high‑volatility uptrend punctuated by sharp 15–25% pullbacks rather than a smooth melt‑up. The upside is driven by markets re‑pricing persistent policy and resource‑nationalism risk—after already realizing downside from delayed tariffs—on top of accelerating structural demand from the energy transition and advanced technologies that tightens supply chains and forces a higher clearing price.

Forecasts for Silver Futures with 12-period horizon (weekly)

Supercell 4x4x4 of Fe3Ni9B4 (Space group: P1, 64 symmetry operations)

YouTube clip from https://youtu.be/Iw81rptxkc?si=4OylYw59-1luNTG (28:00 - 29:00)

Convert between image formats (PNG, JPG, WEBP)

while maintaining its current format

Extract audio track from MP4 video to MP3 or WAV format

Compress an MP4 video using FFmpeg with quality settings

Download a specific time range from a YouTube video as an MP4 clip

File operation and conversion endpoints

Supercell 3x3x3 of Fe6BiSe3 (Space group: P4mm, 216 symmetry operations)

Phase diagram of Fe6BiSe3; eabovehull: 0.186839 eV/atom; predicted_stable: False

Phonon band structure (supercell [3, 3, 3], Δ=0.01 Å); imaginary modes detected; min freq = -0.99 THz

Phase diagram of Zr8Fe2Bi; eabovehull: 0.081061 eV/atom; predicted_stable: False

Supercell 3x3x3 of Zr8Fe2Bi (Space group: P422, 216 symmetry operations)

Phase diagram of Nb9Co19Bi; eabovehull: 0.194784 eV/atom; predicted_stable: False

Funny, the ones that are most stable have Bi as far as possible from Co/Fe. Not great for SOC!

Phase diagram of Nb4Co14Bi; eabovehull: 0.277027 eV/atom; predicted_stable: False

Supercell 2x2x2 of Nb4Co14Bi (Space group: P4/m, 64 symmetry operations)

Phonon band structure (supercell [3, 3, 3], Δ=0.01 Å); imaginary modes detected; min freq = -7.37 THz

high above the hull

Phase diagram of Nb5Co25Bi2; eabovehull: 0.178932 eV/atom; predicted_stable: False

Phonon band structure (supercell [3, 3, 3], Δ=0.01 Å); imaginary modes detected; min freq = -8.58 THz

Phase diagram of Nb3Co6Bi; eabovehull: 0.190533 eV/atom; predicted_stable: False

74meV above the hull

Rare-earth-free permanent magnet candidate system. WIP.

Rare-earth-free permanent magnet candidate system. WIP

Rare-earth-free permanent magnet candidate system. WIP Mostly giving up on this system. It doesn't seem like it has what we're looking for given the few I've tested and the stability of the symmetries

Rare-earth-free permanent magnet candidate system. WIP

I've got a small sample of experimental MAE values to compare against our calculator. While nowhere near sufficient, it should give us a bit of grounding against real world data and how trustworthy ou

A post that gathers casual, anecdotal ideas and some research about curing autoimmune conditions, with a focus on rheumatoid arthritis (RA). It describes personal motives to help a friend and to search for non-traditional approaches found on the internet. The content mixes diet ideas (Paleo, AIP, Clean Keto, Mediterranean pattern), gut health concepts like leaky gut and microbiome, and a range of potential strategies such as omega-3s, green tea, vitamin D and vitamin E, prebiotics, and probiotics. It also mentions gentler options like vagus nerve stimulation through breathing or humming, as well as supplements like berberine, and notes that results can be mixed. The piece emphasizes that much of this is not medical advice and should be read as personal exploration of what might help alongside conventional treatment. It links to several papers and online posts for further reading.

Interstitial Doping is a tool that helps place extra atoms inside crystal structures. It uses a physics-informed approach to find likely interstitial sites with Voronoi tessellation, and then ranks these sites by how well they fit the dopant atom and how favorable the surrounding chemistry is. The method works in periodic crystals by expanding the cell into a small supercell, performing the analysis, and then mapping the results back to the original structure. It characterizes each potential site by void size, coordination, geometry, and nearby atoms, and it scores them to guide dopant placement. Dopants are added one by one while maintaining minimum distances to hosts and to other dopants. This is designed for fast, high‑throughput screening and does not perform energy calculations or structural relaxations; users should relax all structures with DFT afterward.

Analysis of gold futures with a 52-period forecast (Weekly).

Analysis of crude oil price (wti) with a 52-period forecast (Weekly).

Forecasts for Crude Oil Price (WTI) with 52-period horizon (weekly)

Forecasts for Gold Futures with 52-period horizon (weekly)

Stop scraping the "paint" (HTML) and start intercepting the "data packages" (API responses). This guide introduces the Network Interception strategy using Python and Playwright. Learn how to bypass BeautifulSoup entirely, listen to background network traffic, and capture raw, structured JSON data directly from the server—even for complex infinite-scroll sites.

Neodymium iron boron represents one of the most influential material systems in modern permanent magnet technology. As a rare earth–based intermetallic compound, its exceptional magnetic performance is primarily attributed to the Nd₂Fe₁₄B phase, which combines high saturation magnetization with strong magnetocrystalline anisotropy. These intrinsic properties enable the generation of powerful and stable magnetic fields within compact volumes, redefining performance limits in electromechanical and energy-related applications. From a materials science perspective, neodymium iron boron systems rely on precise control of chemical composition and microstructure. The interaction between neodymium-rich grain boundary phases and iron-dominated magnetic grains is critical to achieving high coercivity and resistance to demagnetization. Boron plays a stabilizing role in the crystal lattice, enhancing structural integrity and enabling the formation of the desired magnetic phase during alloy solidification and heat treatment. Industrial production of neodymium iron boron materials is based on advanced powder metallurgy and thermal processing. High-purity raw materials are alloyed under inert or vacuum conditions, followed by rapid solidification and fine milling to achieve uniform particle size distribution. During compaction, external magnetic fields align crystallographic easy axes, creating anisotropic structures that maximize remanence. Subsequent sintering and heat treatment refine grain boundaries and optimize magnetic performance. Microstructural engineering has become a central focus in the continued evolution of neodymium iron boron technology. Techniques such as grain boundary diffusion using heavy rare earth elements are employed to enhance intrinsic coercivity and thermal stability while reducing overall rare earth content. These innovations address both performance demands and supply chain constraints, supporting more sustainable manufacturing practices. Neodymium iron boron materials are widely deployed in electric vehicle traction motors, wind turbine generators, industrial automation systems, robotics, medical devices, and high-efficiency consumer electronics. Their ability to deliver high magnetic energy density enables system miniaturization, improved energy efficiency, and advanced functional integration. As global demand for electrification and renewable energy accelerates, neodymium iron boron remains a foundational material system. Ongoing advances in materials science, process optimization, and recycling technologies continue to reinforce its strategic importance in enabling next-generation industrial and energy infrastructures.

Nd Fe B magnets for sale represent a highly specialized segment of the permanent magnet market, supplying critical components to industries that demand high magnetic performance, compact design, and long-term reliability. Neodymium iron boron magnets are recognized as the strongest commercially available permanent magnets, with their performance derived from the Nd₂Fe₁₄B crystal phase, which exhibits high saturation magnetization and strong magnetocrystalline anisotropy. From a technical perspective, Nd Fe B magnets offered on the market differ significantly in magnetic grade, microstructural design, and operating characteristics. Key parameters such as remanence, intrinsic coercivity, and maximum energy product define magnetic output and resistance to demagnetization. These properties are directly influenced by alloy composition, grain orientation, and heat treatment processes implemented during manufacturing. As a result, magnets intended for high-temperature or high-load environments typically command higher value due to increased material and process complexity. Manufacturing quality is a decisive factor when evaluating Nd Fe B magnets for sale. Most high-performance products are produced through advanced powder metallurgy, involving vacuum melting, fine powder milling, magnetic field alignment, sintering, and precision heat treatment. Tight control over each stage is essential to ensure consistent magnetic performance, dimensional accuracy, and structural integrity, particularly for applications with strict engineering tolerances. Surface engineering is another critical consideration in commercial Nd Fe B magnet offerings. Due to their high neodymium content, these magnets are inherently sensitive to corrosion. Protective coatings such as nickel, zinc, epoxy, or multilayer composite systems are commonly applied to enhance environmental resistance and extend service life in industrial operating conditions. The global market for Nd Fe B magnets for sale is driven by strong demand from electric vehicles, renewable energy systems, industrial automation, robotics, and consumer electronics. Buyers increasingly prioritize not only magnetic strength, but also supply stability, quality consistency, and compliance with environmental and technical standards. This has accelerated the adoption of material-efficient technologies, including grain boundary diffusion and rare-earth optimization strategies, to balance performance with cost and sustainability. In this context, Nd Fe B magnets for sale should be evaluated as engineered materials rather than commodity components. A thorough understanding of material properties, manufacturing processes, and application requirements is essential for selecting magnets that deliver reliable performance and long-term value across advanced electromechanical systems.

Neodymium iron boron magnets are the most advanced and widely used class of rare earth permanent magnets, distinguished by their exceptional magnetic strength and high energy density. Their performance is fundamentally derived from the Nd₂Fe₁₄B intermetallic phase, whose crystal structure exhibits strong magnetocrystalline anisotropy and high saturation magnetization. These intrinsic characteristics enable powerful and stable magnetic fields within compact material volumes. The manufacturing of neodymium iron boron magnets relies on precision-controlled powder metallurgy and thermal processing technologies. High-purity neodymium, iron, and boron are alloyed under inert or vacuum environments to prevent oxidation and compositional deviation. The alloy is then rapidly solidified and milled into fine powders with controlled particle size distribution. During compaction, an external magnetic field aligns the magnetic easy axes, producing an anisotropic microstructure that maximizes remanence. Subsequent vacuum sintering and heat treatment optimize grain boundary phases, resulting in high intrinsic coercivity and long-term magnetic stability. Microstructural engineering is a critical factor in determining the functional performance of neodymium iron boron magnets. Grain size refinement, phase uniformity, and grain boundary chemistry directly influence resistance to demagnetization and thermal degradation. Advanced approaches, such as grain boundary diffusion using heavy rare earth elements, are widely adopted to enhance high-temperature coercivity while reducing overall rare earth consumption, balancing performance requirements with material efficiency. Due to their high neodymium content, neodymium iron boron magnets are inherently susceptible to corrosion and oxidation, which can compromise magnetic integrity over time. To address this limitation, surface engineering is an essential component of product design. Protective coatings including nickel, zinc, epoxy, and multilayer composite systems are applied to improve environmental durability and ensure reliable operation in demanding industrial conditions. Neodymium iron boron magnets are extensively utilized in electric vehicles, wind turbine generators, industrial automation equipment, robotics, medical devices, and precision electronics. Their ability to deliver high magnetic performance in compact and lightweight designs enables increased power density, improved energy efficiency, and advanced system integration. Through continuous advances in materials science, manufacturing technology, and sustainable resource management, neodymium iron boron magnets remain a foundational material supporting the evolution of modern energy, transportation, and automation systems.

Bonded NdFeB materials are a distinct category of rare earth permanent magnets engineered by combining neodymium iron boron magnetic powders with polymer binders. Unlike sintered NdFeB magnets, bonded NdFeB are manufactured through low-temperature forming processes, enabling superior dimensional control, complex geometries, and efficient mass production while delivering stable and predictable magnetic performance. The manufacturing process of bonded NdFeB begins with the preparation of NdFeB powders, which may be produced by rapid solidification or hydrogen decrepitation techniques. These powders are uniformly mixed with thermoplastic or thermosetting binders and formed using compression molding, injection molding, or extrusion. Depending on whether a magnetic field is applied during forming, bonded NdFeB materials can be isotropic or anisotropic, with anisotropic variants offering enhanced magnetic output through controlled particle orientation. From a materials engineering perspective, bonded NdFeB materials exhibit excellent homogeneity and mechanical robustness. The polymer matrix provides inherent resistance to corrosion and mechanical chipping, reducing the need for additional surface treatments. Their lower density compared with sintered magnets contributes to lightweight component design, while tight tolerances and near-net-shape manufacturing reduce secondary machining and assembly complexity. Although bonded NdFeB materials have lower maximum energy products than sintered NdFeB magnets, they offer superior design flexibility and functional integration. They perform reliably under moderate operating temperatures and dynamic conditions, including vibration and mechanical stress. These characteristics make them particularly suitable for applications where precision, repeatability, and complex magnetic circuit design are more critical than absolute magnetic strength. Bonded NdFeB materials are widely used in automotive sensors, small electric motors, electronic devices, office automation equipment, and precision actuators. Their ability to integrate magnetic functionality directly into molded components supports system miniaturization, cost optimization, and high-volume manufacturing efficiency. By balancing magnetic performance with advanced processing flexibility, bonded NdFeB materials occupy a strategic position within the permanent magnet industry, enabling innovative product designs and scalable manufacturing solutions across diverse industrial sectors.

NdFeB magnets, formally known as neodymium iron boron permanent magnets, represent the most powerful class of commercially available permanent magnetic materials. Their exceptional performance is rooted in the Nd₂Fe₁₄B intermetallic compound, whose crystal structure exhibits strong magnetocrystalline anisotropy and high saturation magnetization. These intrinsic properties enable NdFeB magnets to generate intense magnetic fields within compact volumes, supporting advanced engineering designs across multiple industries. The manufacturing of NdFeB magnets is based on sophisticated powder metallurgy and thermal processing techniques. High-purity neodymium, iron, and boron are alloyed under inert or vacuum conditions to prevent oxidation. The alloy is then rapidly solidified and milled into fine powders with controlled particle size distribution. During compaction, an external magnetic field aligns the magnetic easy axes, creating an anisotropic microstructure that maximizes remanence. Subsequent vacuum sintering and heat treatment enhance densification and optimize grain boundary phases, resulting in high intrinsic coercivity and long-term magnetic stability. Microstructural engineering is a critical determinant of NdFeB magnet performance. Grain size control, phase uniformity, and grain boundary chemistry directly influence resistance to demagnetization and thermal degradation. Advanced technologies such as grain boundary diffusion using heavy rare-earth elements are widely applied to improve high-temperature coercivity while minimizing rare-earth consumption, balancing performance demands with material efficiency. Despite their superior magnetic strength, NdFeB magnets are inherently susceptible to corrosion and oxidation due to their high neodymium content. To ensure reliable operation, surface engineering is essential. Protective coatings including nickel, zinc, epoxy, and multilayer composite systems are commonly applied to enhance environmental durability without compromising magnetic properties. NdFeB magnets are extensively used in electric vehicles, wind turbine generators, high-efficiency motors, robotics, medical devices, and precision electronics. Their ability to deliver high magnetic performance in compact and lightweight designs enables increased power density, improved energy efficiency, and advanced system integration. Through continuous innovation in materials science, manufacturing processes, and sustainability practices, NdFeB magnets remain a foundational technology driving the evolution of modern electromechanical and energy conversion systems.

Calculate Magnetic Anisotropy Energy (MAE) using DFT

🚀 The 7-Day Price Volatility Dataset: Market Dynamics Tracker 🔍 Dataset Description & Fields This dataset is designed to capture short-term market liquidity and volatility by comparing the initial price of an item to its price exactly one week later. It is a powerful tool for analyzing pricing strategies, predicting short-term market trends, and identifying products with significant price instability. Interpretation: A positive percentage (e.g., ) indicates the item has experienced appreciation (price increase) over the week, potentially signaling rising demand or reduced supply. A negative percentage (e.g., ) indicates depreciation (price decrease), possibly due to overstocking, new competition, or sales events. A value close to signifies strong price stability. 💡 Advanced Analytical Uses The simple structure of this data facilitates a wide range of analytical tasks: Market Timing: Determine the optimal days or conditions under which prices are most likely to drop (or surge) over a 7-day window. Product Segmentation: Group products by their volatility index to understand which market segments are most sensitive to change. Pricing Strategy Audit: Assess the effectiveness of promotional campaigns by observing the seven-day rebound or stabilization after an initial price change. Risk Assessment: Use the change percentage as a risk indicator for inventory management or investment decisions. First time time it was scraped at 02-12-2025 and next time at 09-12-2025.

🚀 The 7-Day Price Volatility Dataset: Market Dynamics Tracker 🔍 Dataset Description & Fields This dataset is designed to capture short-term market liquidity and volatility by comparing the initial price of an item to its price exactly one week later. It is a powerful tool for analyzing pricing strategies, predicting short-term market trends, and identifying products with significant price instability. Interpretation: A positive percentage (e.g., ) indicates the item has experienced appreciation (price increase) over the week, potentially signaling rising demand or reduced supply. A negative percentage (e.g., ) indicates depreciation (price decrease), possibly due to overstocking, new competition, or sales events. A value close to signifies strong price stability. 💡 Advanced Analytical Uses The simple structure of this data facilitates a wide range of analytical tasks: Market Timing: Determine the optimal days or conditions under which prices are most likely to drop (or surge) over a 7-day window. Product Segmentation: Group products by their volatility index to understand which market segments are most sensitive to change. Pricing Strategy Audit: Assess the effectiveness of promotional campaigns by observing the seven-day rebound or stabilization after an initial price change. Risk Assessment: Use the change percentage as a risk indicator for inventory management or investment decisions. First time time it was scraped at 01-12-2025 and next time at 08-12-2025.

Forecasts for Bitcoin Price with 52-period horizon (weekly)

Forecasts for Crude Oil Price (WTI) with 52-period horizon (weekly)

Forecasts for Copper Price with 12-period horizon (monthly)

Forecasts for Silver Futures with 12-period horizon (monthly)

Forecasts for Gold Futures with 12-period horizon (monthly)

Observed and forecasted housing market data for December 2025 (monthly).

HubSpot Zimbabwe Partner Companies Dataset (Scraped & Structured) This dataset contains clean, structured information scraped from public HubSpot Partner listings for companies operating within Zimbabwe. It is designed to support research, analytics, automation workflows, market mapping, and CRM enrichment. 📌 Dataset Includes Company identifiers (ID, slug, name) Partner tier & partner type Website URLs Public descriptions Logo URLs Ratings & review counts Budget ranges (when available) Locations & regions Languages supported Catalog services offered Industries served Credential and accreditation IDs 🧩 Useful For Market analysis & segmentation Lead scoring and enrichment Competitive mapping Workflow automation & RPA pipelines Data-driven decision-making Building internal tools or dashboards ⚠️ Responsible Use Notice This dataset contains publicly available business information only. It must not be used for: Unsolicited spam campaigns Misrepresentation or harmful automation Violating HubSpot's terms of service or any platform's policies Use this dataset ethically and in compliance with all applicable laws.

HubSpot Zambia Partner Companies Dataset (Scraped & Structured) This dataset contains clean, structured information scraped from public HubSpot Partner listings for companies operating within Zambia. It is designed to support research, analytics, automation workflows, market mapping, and CRM enrichment. 📌 Dataset Includes Company identifiers (ID, slug, name) Partner tier & partner type Website URLs Public descriptions Logo URLs Ratings & review counts Budget ranges (when available) Locations & regions Languages supported Catalog services offered Industries served Credential and accreditation IDs 🧩 Useful For Market analysis & segmentation Lead scoring and enrichment Competitive mapping Workflow automation & RPA pipelines Data-driven decision-making Building internal tools or dashboards ⚠️ Responsible Use Notice This dataset contains publicly available business information only. It must not be used for: Unsolicited spam campaigns Misrepresentation or harmful automation Violating HubSpot's terms of service or any platform's policies Use this dataset ethically and in compliance with all applicable laws.

HubSpot South Africa Partner Companies Dataset (Scraped & Structured) This dataset contains clean, structured information scraped from public HubSpot Partner listings for companies operating within South Africa. It is designed to support research, analytics, automation workflows, market mapping, and CRM enrichment. 📌 Dataset Includes Company identifiers (ID, slug, name) Partner tier & partner type Website URLs Public descriptions Logo URLs Ratings & review counts Budget ranges (when available) Locations & regions Languages supported Catalog services offered Industries served Credential and accreditation IDs 🧩 Useful For Market analysis & segmentation Lead scoring and enrichment Competitive mapping Workflow automation & RPA pipelines Data-driven decision-making Building internal tools or dashboards ⚠️ Responsible Use Notice This dataset contains publicly available business information only. It must not be used for: Unsolicited spam campaigns Misrepresentation or harmful automation Violating HubSpot's terms of service or any platform's policies Use this dataset ethically and in compliance with all applicable laws.

HubSpot Kosovo Partner Companies Dataset (Scraped & Structured) This dataset contains clean, structured information scraped from public HubSpot Partner listings for companies operating within Kosovo. It is designed to support research, analytics, automation workflows, market mapping, and CRM enrichment. 📌 Dataset Includes Company identifiers (ID, slug, name) Partner tier & partner type Website URLs Public descriptions Logo URLs Ratings & review counts Budget ranges (when available) Locations & regions Languages supported Catalog services offered Industries served Credential and accreditation IDs 🧩 Useful For Market analysis & segmentation Lead scoring and enrichment Competitive mapping Workflow automation & RPA pipelines Data-driven decision-making Building internal tools or dashboards ⚠️ Responsible Use Notice This dataset contains publicly available business information only. It must not be used for: Unsolicited spam campaigns Misrepresentation or harmful automation Violating HubSpot's terms of service or any platform's policies Use this dataset ethically and in compliance with all applicable laws.

HubSpot Vietnam Partner Companies Dataset (Scraped & Structured) This dataset contains clean, structured information scraped from public HubSpot Partner listings for companies operating within Vietnam. It is designed to support research, analytics, automation workflows, market mapping, and CRM enrichment. 📌 Dataset Includes Company identifiers (ID, slug, name) Partner tier & partner type Website URLs Public descriptions Logo URLs Ratings & review counts Budget ranges (when available) Locations & regions Languages supported Catalog services offered Industries served Credential and accreditation IDs 🧩 Useful For Market analysis & segmentation Lead scoring and enrichment Competitive mapping Workflow automation & RPA pipelines Data-driven decision-making Building internal tools or dashboards ⚠️ Responsible Use Notice This dataset contains publicly available business information only. It must not be used for: Unsolicited spam campaigns Misrepresentation or harmful automation Violating HubSpot's terms of service or any platform's policies Use this dataset ethically and in compliance with all applicable laws.

HubSpot Venezuela Partner Companies Dataset (Scraped & Structured) This dataset contains clean, structured information scraped from public HubSpot Partner listings for companies operating within Venezuela. It is designed to support research, analytics, automation workflows, market mapping, and CRM enrichment. 📌 Dataset Includes Company identifiers (ID, slug, name) Partner tier & partner type Website URLs Public descriptions Logo URLs Ratings & review counts Budget ranges (when available) Locations & regions Languages supported Catalog services offered Industries served Credential and accreditation IDs 🧩 Useful For Market analysis & segmentation Lead scoring and enrichment Competitive mapping Workflow automation & RPA pipelines Data-driven decision-making Building internal tools or dashboards ⚠️ Responsible Use Notice This dataset contains publicly available business information only. It must not be used for: Unsolicited spam campaigns Misrepresentation or harmful automation Violating HubSpot's terms of service or any platform's policies Use this dataset ethically and in compliance with all applicable laws.

API for first-principles calculations and properties

Interactive browser visualizations for materials science, by @janosh

Random bulk crystal generation with PyXtal and Orb v3