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).
pKa Value (Acid Constant)
The pKa value is the negative base-10 logarithm of the acid constant Ka and measures the strength of an acid: the smaller the pKa, the stronger the acid.
Free · no credit card · in your study plan in 2 minutes
Formula
pK_S = -\lg K_S = -\lg \frac{[\text{H}_3\text{O}^+] \cdot [\text{A}^-]}{[\text{HA}]}Variables & units – pKa Value (Acid Constant)
| Symbol | Meaning | Unit |
|---|---|---|
| pKs | Acid exponent (negative logarithm of Ka) | dimensionslos |
| Ks | Acid constant of the protolysis HA + H₂O ⇌ H₃O⁺ + A⁻ | mol/L |
| [H₃O⁺] | Hydronium concentration at equilibrium | mol/L |
| [A⁻] | Concentration of the conjugate base | mol/L |
| [HA] | Concentration of the undissociated acid | mol/L |
Derivation & background – pKa Value (Acid Constant)
The pKa follows from the law of mass action of the protolysis; the practically constant water concentration is absorbed into Ka. Orientation: very strong acids pKa < 0 (HCl ≈ −6), moderately strong 0 to 4, weak > 4 (acetic acid 4.75, ammonium 9.25). For weak acids the approximation pH = ½(pKa − log c₀) holds; for a conjugate pair pKa + pKb = 14 (25 °C).
Exam blueprint
Validity range
Applies to the protolysis of weak to moderately strong acids in dilute aqueous solution; for very strong acids protolysis is practically complete and the pKa barely measurable.
Derivation steps
The law of mass action of the protolysis is put on a logarithmic scale to obtain manageable numbers.
- 1HA + H₂O ⇌ H₃O⁺ + A⁻ gives Ka = [H₃O⁺][A⁻]/[HA]; the constant water concentration is absorbed into Ka.
- 2pKa = −log Ka compresses the many powers of ten onto a clear scale.
Rearrangements
Acid constant from pKa
One pKa unit corresponds to a factor of 10 in Ka.
pH of weak acids
Approximation for weak acids with a small degree of protolysis.
pKb of the conjugate base
Holds at 25 °C via the ion product of water.
Task variant
Ka of acetic acid is 1.78·10⁻⁵ mol/L. What is the pKa?
pKa = −log(1.78×10⁻⁵) = 4.75; a typical weak acid.
Calculate the pH of 0.10 mol/L acetic acid (pKa = 4.75).
pH = ½(pKa − log c₀) = ½(4.75 − log 0.1) = ½(4.75 + 1) = 2.88.
Common mistakes
Confusing a large pKa with a strong acid.
The smaller the pKa, the larger Ka and the stronger the acid.
Equating pKa with pH.
pKa is a substance constant; the pH additionally depends on concentration. Only at the half-equivalence point does pH = pKa hold.
Applying the approximation formula to strong acids.
Strong acids protolyze completely: pH = −log c₀.
Writing water into the Ka expression.
The practically constant water concentration is already absorbed into Ka.
Exam context
- Titration curves (half-equivalence point), buffer selection and acid-strength comparisons with pKa tables.
These mistakes cost points in real exams. The set drills them until they stick.
Formula cluster
Acid-base systems
pKa links the pH definition, buffer equation and ion product into one calculation toolkit.
Worked example
Acetic acid: Ka = 1.78×10⁻⁵ mol/L → pKa = −log(1.78×10⁻⁵) = 4.75. pH of 0.1 mol/L acetic acid: pH = ½·(4.75 − log 0.1) = ½·(4.75 + 1) = 2.88.
Applications
Comparing acid strengths, buffer selection (pKa near target pH), titration curves, pharmacology (membrane permeability of drugs), amino-acid chemistry
Quanta exam set
Curated exam set for "pKa Value (Acid Constant)":
Question (front)
Which formula describes pKa Value (Acid Constant)?
Answer in your set
Question (front)
How do you rearrange pKs = −lg(Ks) for Acid constant from pKa?
Answer in your set
Question (front)
Which common mistake happens with pKa Value (Acid Constant)?
Answer in your set
+ 8 more cards: units, variables, derivation, example, exam task
These 11 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 pKa Value (Acid Constant)
How do you calculate the pKa value from the acid constant?+
Take the negative base-10 logarithm of the acid constant: pKa = −log Ka. Example acetic acid: Ka = 1.78×10⁻⁵ mol/L gives pKa = −log(1.78×10⁻⁵) = 4.75. Conversely you recover the acid constant via Ka = 10^(−pKa). The acid constant itself comes from the law of mass action of the protolysis HA + H₂O ⇌ H₃O⁺ + A⁻: Ka = [H₃O⁺]·[A⁻]/[HA], where the practically constant water concentration is already absorbed into Ka. The logarithm makes the unwieldy powers of ten comparable: instead of values between 10⁶ and 10⁻¹⁴ you work with a scale from about −6 to +14. One pKa unit of difference means a factor of 10 in acid strength.
What does the pKa value say about the strength of an acid?+
The smaller the pKa, the stronger the acid, because the larger Ka is and the more completely the acid donates its proton to water. Rough orientation: very strong acids have negative pKa values (HCl ≈ −6, sulfuric acid first step ≈ −3), moderately strong ones lie between 0 and about 4 (phosphoric acid first step 2.1), weak ones above (acetic acid 4.75, carbonic acid 6.5, ammonium 9.25). Beware of the classic mix-up: a large pKa means a weak acid, not a strong one. For the conjugate base, pKb = 14 − pKa holds at 25 °C; a very weak acid therefore has a comparatively strong conjugate base.
How do you calculate the pH of a weak acid using the pKa?+
For weak acids the approximation pH = ½(pKa − log c₀) holds, where c₀ is the initial acid concentration. Example: 0.10 mol/L acetic acid with pKa = 4.75 yields pH = ½(4.75 − log 0.1) = ½(4.75 + 1) = 2.88. The approximation assumes that only a small fraction of the acid protolyzes and that the self-ionization of water is negligible; that fits here, since the degree of protolysis is only about 1.3 %. For strong acids such as HCl the formula is wrong; there, because of complete protolysis, simply pH = −log c₀ applies. Borderline case of moderately strong acids: they require the quadratic equation from the law of mass action.
Why does the pH equal the pKa at the half-equivalence point?+
At the half-equivalence point of a titration exactly half of the weak acid is neutralized, so acid HA and conjugate base A⁻ are present in equal concentration. In the Henderson-Hasselbalch equation pH = pKa + log([A⁻]/[HA]) the logarithm then becomes log(1) = 0, leaving pH = pKa. This is doubly useful: experimentally you read off the pKa of an unknown acid simply from the titration curve halfway to the equivalence point. And conceptually this point marks the maximum buffering effect, because there the system best absorbs additions of acid or base. Exam tasks like to combine both aspects.
What is the difference between pKa and pH?+
The pKa is a substance constant: it characterizes how readily a particular acid donates its proton and depends only on the acid and the temperature. The pH, by contrast, is a state variable of the solution: it describes the current hydronium concentration and changes with concentration, dilution or addition of other substances. The same acetic acid (pKa = 4.75) produces quite different pH values depending on concentration: 2.88 at 0.1 mol/L, 3.38 at 0.01 mol/L. The two quantities are linked via the law of mass action, most directly in the Henderson-Hasselbalch equation. Only in the special case of equal acid and base concentrations, for example at the half-equivalence point, do pH and pKa coincide.
Retain pKa Value (Acid Constant) for exams
Create a curated FSRS exam set for pKs = −lg(Ks): 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 pKa Value (Acid Constant)?
Here is how to work through a typical pKa Value (Acid Constant) (pKs = −lg(Ks)) task step by step:
- 1
Task
Ka of acetic acid is 1.78·10⁻⁵ mol/L. What is the pKa?
Solution path
pKa = −log(1.78×10⁻⁵) = 4.75; a typical weak acid.
- 2
Task
Calculate the pH of 0.10 mol/L acetic acid (pKa = 4.75).
Solution path
pH = ½(pKa − log c₀) = ½(4.75 − log 0.1) = ½(4.75 + 1) = 2.88.
pKs = −lg(Ks) · 11 cards ready
Study as an exam set