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).
Dilution Equation
The dilution equation uses the fact that on dilution the amount of dissolved substance stays the same: concentration times volume is equal before and after dilution.
Free · no credit card · in your study plan in 2 minutes
Formula
c_1 \cdot V_1 = c_2 \cdot V_2Variables & units – Dilution Equation
| Symbol | Meaning | Unit |
|---|---|---|
| c₁ | Concentration of the stock solution | mol/L |
| V₁ | Volume of stock solution taken | L oder mL |
| c₂ | Concentration of the diluted solution | mol/L |
| V₂ | Final volume of the diluted solution | L oder mL |
Derivation & background – Dilution Equation
When diluting, only solvent is added, not the solute: n = c·V stays constant, so c₁·V₁ = c₂·V₂. The quotient f = c₁/c₂ = V₂/V₁ is the dilution factor. In practice you pipette V₁ of the stock solution into a volumetric flask and fill up to the final volume V₂; therefore V₂ is the total volume of the finished solution, not the water added. Safety rule for concentrated acids: add acid to water, not the other way round.
Exam blueprint
Validity range
Applies to pure dilution or concentration as long as no reaction occurs and the solute stays dissolved; V₂ is the final volume of the finished solution.
Derivation steps
When diluting, only the volume changes; the amount of dissolved substance stays the same.
- 1Before dilution n = c₁·V₁, afterwards n = c₂·V₂.
- 2Equating the unchanged amount of substance gives c₁·V₁ = c₂·V₂.
Rearrangements
Required stock-solution volume
This is how you plan any dilution in a volumetric flask.
New concentration
V₂ is the total volume after filling up.
Dilution factor
A 1:10 dilution means f = 10.
Task variant
How much 2.0-molar stock solution do you need for 250 mL with c = 0.1 mol/L?
V₁ = c₂·V₂/c₁ = 0.1·250/2.0 = 12.5 mL. Put the 12.5 mL into the 250 mL volumetric flask and fill up to the mark with water.
50 mL of a 0.8-molar solution are filled up to 200 mL. What concentration results?
c₂ = c₁·V₁/V₂ = 0.8·50/200 = 0.2 mol/L. The dilution factor is f = 200/50 = 4, the concentration drops to a quarter.
Common mistakes
Interpreting V₂ as the volume of water added.
V₂ is the final volume of the finished solution; only V₂ − V₁ is added.
Mixing different volume units on the two sides.
mL or L are both fine, but use the same unit on both sides.
Applying the equation to reactions without stoichiometry.
c₁V₁ = c₂V₂ holds only without reaction; in titrations the stoichiometric factor comes in.
Exam context
- Dilution series, preparing standard solutions and combining with c = n/V in stoichiometry tasks.
These mistakes cost points in real exams. The set drills them until they stick.
Formula cluster
Solutions and content
Connects amount of substance, concentration and lab practice.
Worked example
To make 250 mL at c = 0.1 mol/L from a 2.0-molar stock solution: V₁ = c₂·V₂/c₁ = 0.1·250/2.0 = 12.5 mL of stock, then fill up to 250 mL in the volumetric flask.
Applications
Preparing solutions and buffers, dilution series in biology and medicine, titration preparation, dilution of infusions and medicines, calibration solutions for photometry
Quanta exam set
Curated exam set for "Dilution Equation":
Question (front)
Which formula describes Dilution Equation?
Answer in your set
Question (front)
How do you rearrange c₁·V₁ = c₂·V₂ for Required stock-solution volume?
Answer in your set
Question (front)
Which common mistake happens with Dilution Equation?
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 Dilution Equation
How do you calculate with c1V1 = c2V2?+
Three of the four quantities are given, and you solve for the fourth. To find how much stock solution you need, rearrange for V₁: V₁ = c₂·V₂/c₁. Example: for 250 mL of a 0.1-molar solution from a 2.0-molar stock, V₁ = 0.1·250/2.0 = 12.5 mL. You pipette these 12.5 mL into a 250 mL volumetric flask and fill up to the ring mark with water. Important: V₂ is always the final volume of the finished solution, not the amount of water added. The volume units may be mL or L as long as both sides use the same unit, because the conversion factor cancels.
Why does the dilution equation hold at all?+
Because when diluting, only solvent is added while the dissolved substance stays completely in the solution. Its amount n therefore does not change. Since molar concentration is defined as c = n/V, before dilution n = c₁·V₁ and afterwards n = c₂·V₂. Equating the two expressions for the same unchanged amount directly gives c₁·V₁ = c₂·V₂. This also makes intuitive sense: if you increase the volume tenfold, the concentration drops to one tenth. The equation breaks down as soon as a reaction occurs or substance precipitates or evaporates, because then the amount is no longer constant.
What is a dilution factor and how do you use it?+
The dilution factor f states by which factor the solution is diluted: f = V₂/V₁ = c₁/c₂. A 1:10 dilution means f = 10, one part stock solution in a total of ten parts final volume. Dilution series matter in practice: if you dilute 1:10 three times in a row, the factors multiply to f = 10³ = 1000 and the concentration drops to one thousandth. This is how calibration solutions for photometry or microbial dilutions in microbiology are made from one stock. Beware of the wording: in chemistry, "dilute 1:10" usually means 1 part plus 9 parts solvent, giving a final volume of 10 parts.
Why do you fill up in a volumetric flask instead of just adding water?+
Because V₂ in the equation is the exact final volume of the solution. If you simply added 250 mL of water to 12.5 mL of stock solution, the finished solution would have 262.5 mL and the concentration would be too low. Moreover, volumes are not always additive: when mixing ethanol and water, the total volume is slightly smaller than the sum of the individual volumes. The volumetric flask avoids both problems because it is calibrated to a single certified final volume: add the stock, add water to just below the mark, mix, then fill exactly to the ring mark. This way V₂ is correct regardless of mixing effects.
Does c1V1 = c2V2 also apply to titrations?+
Only with one important addition. In a titration two substances react, and at the equivalence point the amounts have reacted in their stoichiometric ratio. For a 1:1 reaction such as HCl with NaOH the equation therefore looks formally identical: c(acid)·V(acid) = c(base)·V(base). But as soon as the ratio is not 1:1, the stoichiometric factor enters: sulfuric acid delivers two protons, so 2·c(H₂SO₄)·V(H₂SO₄) = c(NaOH)·V(NaOH). The pure dilution equation, by contrast, only describes the case without reaction, where the same portion of substance is merely spread over more volume. Mixing up the two situations makes the result wrong by the stoichiometric factor.
Retain Dilution Equation for exams
Create a curated FSRS exam set for c₁·V₁ = c₂·V₂: 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 Dilution Equation?
Here is how to work through a typical Dilution Equation (c₁·V₁ = c₂·V₂) task step by step:
- 1
Task
How much 2.0-molar stock solution do you need for 250 mL with c = 0.1 mol/L?
Solution path
V₁ = c₂·V₂/c₁ = 0.1·250/2.0 = 12.5 mL. Put the 12.5 mL into the 250 mL volumetric flask and fill up to the mark with water.
- 2
Task
50 mL of a 0.8-molar solution are filled up to 200 mL. What concentration results?
Solution path
c₂ = c₁·V₁/V₂ = 0.8·50/200 = 0.2 mol/L. The dilution factor is f = 200/50 = 4, the concentration drops to a quarter.
c₁·V₁ = c₂·V₂ · 10 cards ready
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