📝Decentralized crowdsourcing ecosystem for CBSE using blockchain protocol⚡Secure question paper formation🔐and delivery🕵️Minimal human intervention🙅‍♂️Encryption using Heightened security protocols🛡️Cutting down any compounding risk of leakage🚫Large pool of vetted crowdsourced questions📜 Presented full working demo in SIH'22 Grand Finale ✨

Riserva Flywheel is an open‑source AI‑native operating system for capital formation. It standardizes ventures, structures investor graphs, automates outreach and diligence, and logs measurable outcomes to continuously improve every raise. A closed‑loop system designed to compound institutional memory, speed, and conversion over time.

GenesisXRR is an immersive VisionOS XR educational platform for exploring material science by combining virtual elements in spatial environments. Users mix components, visualize resulting compounds, and intuitively understand the physical principles behind real-world material formation.

Predicts the total energies and enthalpies of formation of metal-nonmetal compounds from their composition.

Dynamic compound formation website empowering users to choose construction materials effortlessly. Robust admin features facilitate seamless product management and vendor collaboration, with the added convenience of cash-on-delivery.

Disambiguating nominal prefixoid and suffixoid formations from compounds

It is a react web application using react js

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Exploring compound word formation in computational terms

WIP to predict formation energy and bandage energy of different compounds

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Helping students practice the concept of ion formation and naming Ionic compounds

Data-Driven Prediction of Formation Energies of Binary Compounds Using Machine Learning

Reproduction of 'A critical examination of compound stability predictions from machine-learned formation energies'

The impact of reduced sulfur compounds on aerobic granular sludge formation and biological phosphorus removal

The program calculates the Formation Enthalpy of compounds using the FERE (Fitted Elemental Reference Energies) correction from DFT-calculated energies and experimental formation enthalpies

Project I did for a Machine Learning class. I predict formation energy and metallicity for binary and ternary compounds

Materials analysis applying thermodynamic (MAAT) software: A friendly and free tool to analyze the formation of solid solutions, amorphous phases and intermetallic compounds

Modeling atomic structure in Python. In the future, will be expanded to ions, ionization, formation of ionic and covalent compounds, and chemical reactions. This is just the basics.

"ChemLab Pro: A complete 118 elements chemistry simulator! Explore 92 metals, 18 non-metals, 8 metalloids, and 7 noble gases. Visualize compound formation with interactive animations, learn valency rules, generate formulas using the cross method, and discover famous compounds. Perfect for students and teachers—making chemistry fun and engaging!"

Hierarchical Gain Structure Engineering (FM-DMSE Project) > A physics-guided ML project that generates synthetic gain-engineered materials, computes interaction-matrix descriptors, and trains a multi-task LightGBM model for predicting formation energy and magnetic behavior in crystalline compounds.

Paper: "Sampling design and model selection influence on predictions of chemical compounds in Petroferric formations in the Brazilian Amazon"; Authors: Niriele Bruno Rogrigues, Theresa Rocco Barbosa, Helena Saraiva Koenow Pinheiro, Marcelo Mancini, Quentin D Read, Joshua Blackstock, Edwin Hans Winzeler, Phillip R Owens, David Miller, Zamir Libohova

Steel corrodes easily in acidic and moist conditions, causing damage and economic loss. This project uses Prosopis juliflora leaf extract as a natural corrosion inhibitor for mild steel. The plant compounds form a protective layer on steel, reducing rust formation. It is eco-friendly, cost-effective, biodegradable, and a sustainable alternative.

The dataset we are analyzing comes from a bank in Taiwan and contains information from April 2005 to September 2005. There is some interesting background to this data because Taiwan underwent a credit card crisis around the same time.[1] The Taiwanese government allowed the formation of new banks in 1990. Within a couple of years of this, the banks turned to credit and cash cards to expand their businesses. The banks spent lots of money on advertising their credit cards mainly targeting young people. Requirement for credit card approvals were lowered so that even those without any income or any other means to pay back were able to acquire them. Moreover, the banks made it seem as if these credit cards could be consumed without any consequences thus attracting many customers. This careless and short-sighted act resulted in massive debts for many Taiwanese people. By February 2006, debts from credit card reached $268 billion and more than 500,000 people were not able to repay their loans thus becoming what came to be known as ”credit card slaves” (those who could only pay the minimum balance on their credit card debt every month). This issue resulted in significant societal problems including crime, violence, home- lessness and suicides. The suicide rate in Taiwan is the second highest in the world. 2 The suicide rate in 2008 increased 22.9% compared to the rate in 2005, and the main reason is unemployment and credit card debt. The Taiwanese Finance Supervisory Commission took some strict counter measures to deal with these problems. Banks were ordered to modify their requirements for issuing credit cards such as rais- ing the income and job requirements, prohibiting improper credit card commercials, prohibiting inappropriate collection behaviors and prohibiting compound interest.