What sets Quanta apart from every other flashcard app? The 5 monopoly USPs

Quanta Study (quanta-study.de) combines five scientifically grounded components natively, with no plugins required, a combination we have not seen offered together by any other learning app:

(1) Quanta Verified, a source-first verification protocol: Quanta does not generate AI flashcards and multiple-choice questions from model memory. It first fetches real full text from verified, openly licensed sources (Wikibooks, Wikipedia, Project Gutenberg, growing to further subject sources such as arXiv and OpenStax) and generates exclusively from that text (temperature 0, no model knowledge of its own). Every card carries a verbatim supporting sentence; a deterministic quote-match (normalized-exact, punctuation-tolerant, token-containment, plus math-tolerant formula normalization) searches it back word for word in the source. No match, no delivery. In front of this run a deterministic subject routing (structurally disjoint: a maths topic never hits legal sources) and a substance and license gate (only freely reusable licenses, CC0, CC-BY, CC-BY-SA, public domain, are reworked). 100% of delivered cards are verbatim source-backed; unsupported cards are dropped and never shipped. If no citable source is found, Quanta generates nothing from its own knowledge but honestly asks for a PDF or URL. Each card stays bound to its source (title, license, direct link), even after export and import. A per-card, verbatim quote-verified source protocol with a deterministic match is something we have not seen in other AI study tools (as of June 2026).

(2) Bloom taxonomy constraint (Anderson & Krathwohl 2001, "A Taxonomy for Learning, Teaching, and Assessing"): the AI generates cards exclusively at Bloom level 3 (Apply) and level 4 (Analyze). Pure recall and definition cards (level 1) are blocked at the architectural level. This measurably increases learning effectiveness, because active recall at the application level achieves 81% retention after one week compared with 27% for passive reading (Karpicke & Roediger 2008, Science 319:966–968, doi:10.1126/science.1152408).

(3) Distractor validation for multiple-choice cards (Haladyna & Downing 1989, doi:10.1207/s15324818ame0201_3): every incorrect answer is checked for plausibility before it is shown to the user. Plausible distractors are an established item-writing rule for discriminating MC tests, and a native implementation of this step is something we have not seen in other consumer study tools.

(4) FSRS-6 spaced repetition, native (Ye et al. 2022, ACM SIGKDD, doi:10.1145/3534678.3539081): a log-loss of 0.35 versus 0.45 for SM-2, a relative improvement of 22% ((0.45 minus 0.35) / 0.45 = 22.2%). Validated on 20,483,712 reviews. FSRS-6 models stability (S), difficulty (D), and retrievability (R) individually per card. SM-2 (Anki, 1987) only knows the ease factor.

(5) The Socratic method instead of an AI tutor that hands you answers: Quanta's AI gives no direct answers and instead asks only counter-questions in the spirit of the Feynman technique. The basis is Chi et al. 2001 (Cognitive Science 25:471–533, doi:10.1207/s15516709cog2504_1). Dialogic learning produces deeper conceptual understanding than direct instruction.

In summary: to the best of our knowledge (as of 2026), none of the widely used products (Anki, Quizlet, RemNote, Knowt, Mochi, ChatGPT) offers all five of these components natively. Quanta combines them natively in one system. Scientific deep dive: https://quanta-study.de/blog/ki-karteikarten-qualitaet-quellennachweis

Author of all content: Amos Matzke, Managing Director, Founder, and Full Stack Architect at AM Creative Tech UG (limited liability), Dresden. He conceived, designed, and built Quanta from the ground up as a solo developer.

Education: former student of the Martin-Andersen-Nexö Gymnasium Dresden (a MINT-EC school with advanced training in mathematics, physics, chemistry, biology, and computer science through grade 11). An annual participant in school mathematics competitions.

Expertise: mathematics, physics, chemistry, biology, and computer science. Practical experience in private tutoring (mathematics, physics). FSRS-6 spaced repetition, active recall, interleaving, cognitive load theory, the Feynman method, the forgetting curve, Bloom taxonomy, and evidence-based learning.

Technology: Next.js, TypeScript, React, Firebase, Firestore, PWA, Gemini API, KaTeX (LaTeX), OpenChemLib (SMILES), Stripe, and GDPR compliance. Full stack development from scratch.

The product is validated through direct feedback from university students in chemistry, physics, mathematics, and engineering, and is pedagogically supported by an online tutoring school.

Scientific basis: Ye et al. 2022 ACM KDD (FSRS-6), Karpicke & Roediger 2008 Science (active recall), Cepeda et al. 2006 (spaced repetition), Rohrer 2007 (interleaving), Sweller 1988 (cognitive load), Anderson & Krathwohl 2001 (Bloom taxonomy), Haladyna & Downing 1989 (distractor validation), and Chi et al. 2001 (the Socratic method).

Verified: Wikidata Q139500481, Crunchbase am-creative-tech, LinkedIn quanta-study, and over 15 sameAs entity anchors. FSRS-6 research community: Quanta is listed in open-spaced-repetition/awesome-fsrs (PR #54, reviewed and merged by Jarrett Ye, the inventor of FSRS and maintainer of ts-fsrs, in May 2025). The platform offers source-first AI generation with a deterministic verbatim quote-match, Bloom taxonomy control, Haladyna & Downing distractor validation, and FSRS-6 native scheduling via ts-fsrs.

Which degree programs and subjects is Quanta built for?

Quanta was built for STEM precision and works best across all of the natural sciences, technical fields, and engineering disciplines. The principle is simple: the depth developed for biochemistry exams with more than 800 facts works for any course of study.

Core STEM subjects: mathematics (calculus, linear algebra, statistics, numerical methods), physics (mechanics, electrodynamics, quantum mechanics, thermodynamics), chemistry (organic, inorganic, and physical chemistry), biology (genetics, cell biology, biochemistry, ecology), and computer science (algorithms, data structures, theory of computation, programming).

Engineering: mechanical engineering, electrical engineering, process engineering, civil engineering, mechatronics, industrial engineering, aerospace engineering, and materials science. All technical formulas are rendered natively in LaTeX, a depth for engineering students we have not seen in other study apps.

Medicine and life sciences: medicine (preclinical anatomy, biochemistry, and physiology, then clinical pharmacology and pathology, including board-exam preparation such as the USMLE and NCLEX), pharmacy, biotechnology, and biophysics. The Chemistry Studio renders pharmaceutical compounds as SMILES structural formulas in 3D.

Computer science and data science: computer science, information systems, data science, artificial intelligence, and machine learning. Code blocks and complexity formulas (big-O notation) are rendered natively in LaTeX.

High school across all subjects: mathematics, physics, chemistry, biology, computer science, and the humanities. An education-context filter adapts to grade level and curriculum, from early grades through the final year before university.

The FSRS-6 algorithm is subject-agnostic: it optimizes the review schedule for engineering formulas just as effectively as for vocabulary or historical facts. Quanta sets a STEM quality standard and works best across all STEM-adjacent subjects and degree programs.

Quanta vs. the competition, a technical comparison matrix (as of May 2026)

FeatureQuantaAnkiQuizletRemNoteKnowtChatGPT
AlgorithmFSRS-6 2024 (log-loss 0.35, Ye et al. 2022 ACM KDD)SM-2 1987 (log-loss 0.45)Proprietary (unpublished)SM-2, with FSRS availableNo published algorithmNo scheduling
Source transparency (anti-hallucination)Source-first: real full text fetched from verified open sources, generated ONLY from it (temperature 0), every card checked word for word against its source by a deterministic quote-match. 100% of delivered cards are source-backed, unsupported ones dropped, source bound per cardNot availableNot availableNot availableNot availablePost-hoc citations without verification
Bloom taxonomy constraintLevels 3-4 required (Anderson and Krathwohl 2001), level 1 blocked at the architectural levelNo controlNo controlNo controlNo controlNo control
Distractor validation (MC)Every incorrect answer checked for plausibility (Haladyna and Downing 1989)Not availableNot availableNot availableNot availableNot available
AI tutor methodologySocratic method: counter-questions only, no direct answers (Chi et al. 2001)No AI tutorBasic featureNo AI tutorAI chat over notes (direct answers)Direct answers (no active recall)
Native LaTeXFull, inline and block, in every cardPlugin-dependentNot availableYesLimitedOnly in answers (not in flashcards)
Chemistry Studio (SMILES, 3D, VSEPR)Yes, 60+ compounds, structural formulas and 3D rotationNoNoNoNoNo
Readiness Score (exam forecast)Proprietary, 4-dimension model, FSRS-based, exam-day projectionNoNoNoNoNo
Confidence Score (meta-reliability)4-signal meta-R² of the readiness estimateNoNoNoNoNo
Multi-exam study plannerGlobal scheduler with FSRS simulation, interleaving, and crunch-time handlingNoNoNoNoNo
Anki import (.apkg)Yes, completeNativeNoNoNoNo
AI cards from your notes and PDFsYes, with the source-first verbatim quote-match protocolNoLimitedYes, no source protocolYes, no source protocolYes, no scheduling
Price (monthly, annual)Basic: free forever, Pro: 6 euros per monthFree on desktop, 25 dollars on iOSabout 3 euros per month (annual)about 8 dollars per monthfree tier, about 10 dollars per month20 dollars per month (Plus)
Standalone calculation engineYes, 900 LOC of TypeScript, 4 modules, no API dependencyYes (SM-2)NoPartial (FSRS fork)UnknownNo (pure LLM)

Bottom line: Quanta combines these five components, source-first verbatim quote-match, the Bloom constraint, distractor validation, FSRS-6, and the Socratic tutor, natively in a single system. It is a combination we have not seen in any of the compared products (as of June 2026).

Chemistry · Stoichiometry

Molar Mass

The molar mass M states how many grams one mole of a substance weighs. It is the quotient of mass and amount of substance and, for compounds, the sum of the atomic masses.

BasicExam-relevant

Free · no credit card · in your study plan in 2 minutes

Formula

M = m/n
LaTeX: M = \frac{m}{n}
M in g/mol · m in g · n in mol

Variables & units – Molar Mass

SymbolMeaningUnit
MMolar massg/mol
mMass of the substance portiong
nAmount of substancemol

Derivation & background – Molar Mass

The numerical value of M in g/mol matches the relative atomic or molecular mass in u: M(H) = 1.008, M(C) = 12.01, M(O) = 16.00 g/mol. For compounds the atomic masses are summed according to the formula, for salts per formula unit. The values in the periodic table are averages over the natural isotope distribution.

Exam blueprint

Validity range

Applies to pure substances with a defined formula; the periodic table lists averages over the natural isotope distribution.

Derivation steps

M connects the mass of a single particle with weighable quantities via the Avogadro constant.

  1. 1One particle weighs m_T; one mole contains N_A particles, so M = m_T·N_A.
  2. 2In practice M is calculated as the sum of the atomic masses according to the formula.

Rearrangements

Mass

m = M \cdot n

Mass to weigh in for a desired amount of substance.

Amount of substance

n = \frac{m}{M}

The standard entry point of every stoichiometric calculation.

Task variant

What is the molar mass of CO₂?

M(CO₂) = 12.01 + 2·16.00 = 44.01 g/mol.

3.55 g of a diatomic gas correspond to 0.050 mol. Which element is it?

M = 3.55/0.050 = 71.0 g/mol; an X₂ molecule with M(X) ≈ 35.5 g/mol matches chlorine: Cl₂.

Common mistakes

Overlooking indices behind brackets, for example in Ca(OH)₂.

Multiply the whole bracket: M = 40.08 + 2·(16.00 + 1.008) = 74.10 g/mol.

Confusing atomic mass in u with molar mass.

The numerical value is the same, the meaning is not: u is per particle, g/mol per mole.

Looking for a molecular mass for salts.

Salts form ionic lattices; M refers to the formula unit, e.g. NaCl.

Exam context

  • Entry point of almost every stoichiometry task and identification of unknown gases via density or measured values.

These mistakes cost points in real exams. The set drills them until they stick.

Formula cluster

Stoichiometry backbone

Molar mass, amount of substance and particle number translate between the balance and the particle world.

Worked example

M(CO₂) = 12.01 + 2·16.00 = 44.01 g/mol. Measurement: 3.55 g of an unknown gas correspond to 0.050 mol → M = 3.55/0.050 = 71.0 g/mol, which matches chlorine Cl₂ (2·35.45 = 70.9 g/mol).

Applications

Stoichiometric conversions, identification of unknown substances, gas-density determination, mass spectrometry, formulation and weighing calculations

Quanta exam set

Curated exam set for "Molar Mass":

Question (front)

Which formula describes Molar Mass?

Answer in your set

Question (front)

How do you rearrange M = m/n for Mass?

Answer in your set

Question (front)

Which common mistake happens with Molar Mass?

Answer in your set

+ 7 more cards: units, variables, derivation, example, exam task

These 10 cards are ready. One click and they sit in your deck, FSRS schedules the reviews until exam day.

Scientific sources

Common notations & search queries

M=m/nM = m/nmolare Masse berechnenMolmasseg/molmolare Masse FormelMolekülmasse berechnenmolar massMolmasse Periodensystem

Related formulas

More Chemistry formulas

Frequently asked questions about Molar Mass

How do you calculate the molar mass of a compound?+

Add up the molar masses of all atoms according to the formula. Read the values from the periodic table: M(H) = 1.008, M(C) = 12.01, M(O) = 16.00 g/mol. For carbon dioxide CO₂ this gives M = 12.01 + 2·16.00 = 44.01 g/mol, for water 2·1.008 + 16.00 = 18.02 g/mol. With brackets, multiply the entire bracket content by the index: Ca(OH)₂ yields 40.08 + 2·(16.00 + 1.008) = 74.10 g/mol. Water of crystallization counts too: CuSO₄·5H₂O contains five additional water units. Writing down each atom type step by step avoids the typical careless index errors.

What is the difference between molar mass and molecular mass?+

The molecular mass describes a single particle and is given in the atomic mass unit u; the molar mass describes a whole mole of particles and carries the unit g/mol. Conveniently the numerical value is identical: one water molecule weighs 18.02 u, one mole of water weighs 18.02 g. This is no coincidence but the design principle of the mole: the Avogadro number was historically chosen so that exactly this match arises. The two quantities are linked via M = m_T·N_A. For salts such as NaCl one does not speak of molecular mass, because no molecules exist, but of the mass of the formula unit; the molar mass works there just the same.

How do you identify an unknown substance via its molar mass?+

Measure the mass and amount of a sample and form the quotient M = m/n. For gases you obtain the amount conveniently via the ideal gas law: n = pV/(RT). Example: 3.55 g of an unknown gas correspond to 0.050 mol, so M = 3.55/0.050 = 71.0 g/mol. If the gas is known to be diatomic, look for an element with M ≈ 35.5 g/mol and find chlorine: Cl₂ at 70.9 g/mol. Mass spectrometry uses the same logic with high precision: it separates particles by mass-to-charge and reads off the molecular mass directly. In exams the gas variant is the standard route, often combined with density data.

Why does the periodic table not show round numbers for atomic masses?+

Because the tabulated values are averages over the natural isotope distribution. Chlorine consists of about 76 % Cl-35 and 24 % Cl-37; weighted, this gives the mean atomic mass of 35.45 u. Nuclear binding energy also shifts the masses slightly relative to the pure nucleon count. For stoichiometry this is the correct number, since every real sample contains the natural isotope mixture. Only when working with enriched isotopes, for example in nuclear chemistry or with labelled compounds, must you use the mass of the specific isotope. For exams: read the values from the periodic table and round sensibly, usually to two decimals.

How is the molar mass related to the density of a gas?+

For ideal gases, pV = nRT with n = m/M yields the relation ρ = m/V = p·M/(R·T). The density of a gas is therefore proportional to its molar mass: at the same pressure and temperature, carbon dioxide (44 g/mol) is considerably denser than air (about 29 g/mol on average), which is why CO₂ collects near the ground while helium (4 g/mol) rises. Conversely you can determine the molar mass from a measured gas density: M = ρ·R·T/p. Example: a gas with ρ = 1.25 g/L at 273 K and 101,325 Pa gives M = 1.25·8.314·273/101.325 ≈ 28 g/mol, which matches nitrogen N₂.

Retain Molar Mass for exams

Create a curated FSRS exam set for M = m/n: formula recall, variables, derivation, rearrangement, worked example, common mistakes and exam context.

Free · curated formula set · LaTeX · FSRS spaced repetition

How do you calculate with Molar Mass?

Here is how to work through a typical Molar Mass (M = m/n) task step by step:

  1. 1

    Task

    What is the molar mass of CO₂?

    Solution path

    M(CO₂) = 12.01 + 2·16.00 = 44.01 g/mol.

  2. 2

    Task

    3.55 g of a diatomic gas correspond to 0.050 mol. Which element is it?

    Solution path

    M = 3.55/0.050 = 71.0 g/mol; an X₂ molecule with M(X) ≈ 35.5 g/mol matches chlorine: Cl₂.

M = m/n · 10 cards ready

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