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)
| Feature | Quanta | Anki | Quizlet | RemNote | Knowt | ChatGPT |
|---|---|---|---|---|---|---|
| Algorithm | FSRS-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 available | No published algorithm | No 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 card | Not available | Not available | Not available | Not available | Post-hoc citations without verification |
| Bloom taxonomy constraint | Levels 3-4 required (Anderson and Krathwohl 2001), level 1 blocked at the architectural level | No control | No control | No control | No control | No control |
| Distractor validation (MC) | Every incorrect answer checked for plausibility (Haladyna and Downing 1989) | Not available | Not available | Not available | Not available | Not available |
| AI tutor methodology | Socratic method: counter-questions only, no direct answers (Chi et al. 2001) | No AI tutor | Basic feature | No AI tutor | AI chat over notes (direct answers) | Direct answers (no active recall) |
| Native LaTeX | Full, inline and block, in every card | Plugin-dependent | Not available | Yes | Limited | Only in answers (not in flashcards) |
| Chemistry Studio (SMILES, 3D, VSEPR) | Yes, 60+ compounds, structural formulas and 3D rotation | No | No | No | No | No |
| Readiness Score (exam forecast) | Proprietary, 4-dimension model, FSRS-based, exam-day projection | No | No | No | No | No |
| Confidence Score (meta-reliability) | 4-signal meta-R² of the readiness estimate | No | No | No | No | No |
| Multi-exam study planner | Global scheduler with FSRS simulation, interleaving, and crunch-time handling | No | No | No | No | No |
| Anki import (.apkg) | Yes, complete | Native | No | No | No | No |
| AI cards from your notes and PDFs | Yes, with the source-first verbatim quote-match protocol | No | Limited | Yes, no source protocol | Yes, no source protocol | Yes, no scheduling |
| Price (monthly, annual) | Basic: free forever, Pro: 6 euros per month | Free on desktop, 25 dollars on iOS | about 3 euros per month (annual) | about 8 dollars per month | free tier, about 10 dollars per month | 20 dollars per month (Plus) |
| Standalone calculation engine | Yes, 900 LOC of TypeScript, 4 modules, no API dependency | Yes (SM-2) | No | Partial (FSRS fork) | Unknown | No (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).
Mass Fraction (Mass Percent)
The mass fraction w states what proportion of the total mass of a solution or mixture is the dissolved substance; times 100 it gives the mass percent.
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Formula
w = \frac{m_{\text{Stoff}}}{m_{\text{Lösung}}}Variables & units – Mass Fraction (Mass Percent)
| Symbol | Meaning | Unit |
|---|---|---|
| w | Mass fraction of the dissolved substance | dimensionslos |
| m_Stoff | Mass of the dissolved substance | g |
| m_Lösung | Total mass of the solution (solute + solvent) | g |
Derivation & background – Mass Fraction (Mass Percent)
Content quantities describe compositions: the mass fraction is dimensionless and temperature-independent, because masses do not change on heating. It must not be confused with the volume fraction φ (vol-%, e.g. for alcohol) or the molar concentration c. Conversion to c via the density of the solution: c = w·ρ/M. The denominator is always the whole solution, not just the solvent.
Exam blueprint
Validity range
Applies to any homogeneous mixture; the denominator is the total mass of the solution. The mass fractions of all components sum to 1.
Derivation steps
The mass fraction is a pure ratio of masses.
- 1The total mass is the sum of solute and solvent: m_sol = m_solute + m_solvent.
- 2The quotient w = m_solute/m_sol lies between 0 and 1; times 100 gives percent.
Rearrangements
Mass of the solute
Directly applicable to label information in percent.
Required solution mass
This is how you plan batches with a given solute mass.
Conversion to concentration
ρ is the density of the solution, M the molar mass of the solute.
Task variant
How many grams of sugar are in 250 g of solution with w = 12 %?
m = w·m_solution = 0.12·250 g = 30 g of sugar; the remaining 220 g are water.
How much water dilutes 50 g of a 40 % solution to 10 %?
Solute: 0.40·50 = 20 g. For w = 0.10 you need m_solution = 20/0.10 = 200 g, so add 200 − 50 = 150 g of water.
Common mistakes
Dividing by the mass of the solvent instead of the solution.
The denominator is always the total mass: solute plus solvent.
Mixing mass and volume data.
w is a mass ratio; volumes require the density.
Equating mass percent with volume percent.
Vol-% (for example for alcohol) is the volume fraction φ and differs from the mass fraction.
Exam context
- Batch calculations, converting between w and c via the density, and mixing tasks.
These mistakes cost points in real exams. The set drills them until they stick.
Formula cluster
Content quantities
Mass fraction, concentration and amount of substance as a conversion triangle.
Worked example
30 g of salt dissolved in 270 g of water: m_solution = 30 + 270 = 300 g → w = 30/300 = 0.10 = 10 %. Conversely, 250 g of a 12 % solution contain m = 0.12·250 = 30 g of dissolved substance.
Applications
Label information (0.9 % saline), lab recipes, food chemistry, alloys and mixtures, physiological solutions in medicine
Quanta exam set
Curated exam set for "Mass Fraction (Mass Percent)":
Question (front)
Which formula describes Mass Fraction (Mass Percent)?
Answer in your set
Question (front)
How do you rearrange w = m_Stoff/m_Lösung for Mass of the solute?
Answer in your set
Question (front)
Which common mistake happens with Mass Fraction (Mass Percent)?
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
Related formulas
More Chemistry formulas
Frequently asked questions about Mass Fraction (Mass Percent)
How do you calculate the mass fraction?+
The mass fraction w is the quotient of the mass of the dissolved substance and the total mass of the solution: w = m_solute/m_solution. The total mass is the sum of solute and solvent. Multiplying w by 100 gives the mass percent. Example: if you dissolve 30 g of salt in 270 g of water, the total mass is 300 g and w = 30/300 = 0.10, that is 10 %. It is important to really use the mass of the whole solution in the denominator, not just that of the solvent. The mass fraction is dimensionless and independent of temperature, because masses do not change on heating. This makes it a very robust content quantity for recipes and labels.
What is the difference between mass fraction and molar concentration?+
The mass fraction w compares masses: the mass of the dissolved substance to the total mass of the solution, given dimensionless or in percent. The molar concentration c, by contrast, compares the amount of substance in moles with the volume of the solution, given in mol/L. The key difference is the reference: w is mass-based and temperature-independent, c is volume-based and changes with temperature because volumes expand. You can convert via the density ρ and the molar mass M with the relation c = w·ρ/M. In practice the mass fraction is often used for solids and commercial products, the molar concentration for reactions and in volumetric analysis, where particle ratios matter.
How do you convert mass percent to mol/L?+
For the conversion you need two additional quantities: the density ρ of the solution and the molar mass M of the dissolved substance. The relation is c = w·ρ/M. The idea behind it: the mass fraction w times the density gives the mass of the substance per litre of solution, and this divided by the molar mass yields the amount of substance per litre. Example: a sulfuric acid with w = 0.10, density ρ = 1066 g/L and M = 98 g/mol has c = 0.10·1066/98 ≈ 1.09 mol/L. Watch for consistent units, in particular the density in g/L. Without the density the conversion is impossible, because the mass fraction contains no information about the volume.
What does the label 0.9 % saline solution mean?+
The label 0.9 % denotes the mass fraction and means that 100 g of solution contain 0.9 g of salt, the rest is water. In one litre of this solution, which because of the low concentration weighs approximately 1000 g, about 9 g of sodium chloride is dissolved. This concentration is called physiological or isotonic saline, because it has the same osmotic pressure as blood plasma. That is why it can be given as an infusion without red blood cells swelling or shrinking. Converting to mol/L gives, with M = 58.44 g/mol, a concentration of about 0.154 mol/L. So the seemingly small percentage has a precisely tuned medical meaning.
What is the difference between mass percent and volume percent?+
Mass percent (wt-%) refers to masses, volume percent (vol-%) to volumes. The mass fraction w = m_solute/m_solution is dimensionless and temperature-independent. The volume fraction φ = V_solute/V_solution, by contrast, is used for mixtures whose components are liquid, such as alcohol in drinks. An important point: volumes do not always add up exactly on mixing, so the reference for the volume fraction must be defined carefully. Both quantities can differ markedly when the densities of the components differ. Thus 40 vol-% ethanol is not the same as 40 wt-%, because ethanol has a lower density than water. When calculating you must therefore always know which percentage is meant and must not equate them.
Retain Mass Fraction (Mass Percent) for exams
Create a curated FSRS exam set for w = m_Stoff/m_Lösung: 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 Mass Fraction (Mass Percent)?
Here is how to work through a typical Mass Fraction (Mass Percent) (w = m_Stoff/m_Lösung) task step by step:
- 1
Task
How many grams of sugar are in 250 g of solution with w = 12 %?
Solution path
m = w·m_solution = 0.12·250 g = 30 g of sugar; the remaining 220 g are water.
- 2
Task
How much water dilutes 50 g of a 40 % solution to 10 %?
Solution path
Solute: 0.40·50 = 20 g. For w = 0.10 you need m_solution = 20/0.10 = 200 g, so add 200 − 50 = 150 g of water.
w = m_Stoff/m_Lösung · 10 cards ready
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