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).

Physics · Electricity

Energy Stored in a Capacitor

The energy stored in the electric field of a capacitor grows quadratically with the voltage.

AdvancedExam-relevant

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

Formula

E = ½CU²
LaTeX: E = \frac{1}{2} C U^2
E in joules [J] · C in farads [F] · U in volts [V]

Variables & units – Energy Stored in a Capacitor

SymbolMeaningUnit
EStored electric energyJ
CCapacitanceF
UCharging voltageV

Derivation & background – Energy Stored in a Capacitor

During charging, each further portion of charge must be transported against the voltage already present. The charging work is the area under the Q-U line: W = ½·Q·U. With Q = C·U the three equivalent forms E = ½CU² = ½QU = Q²/(2C) follow. The factor ½ distinguishes the capacitor energy from the energy E = Q·U of a charge passing through a fixed voltage.

Exam blueprint

Validity range

Holds for ideal capacitors without leakage. When charging through a resistor, an equal amount of energy is dissipated as heat in the resistor, so the charging efficiency is at most 50%.

Derivation steps

The charging work is the area under the Q-U line, a triangle, hence the factor ½.

  1. 1Each charge portion dQ is moved against the instantaneous voltage u = q/C: dW = u·dq.
  2. 2Integrating from 0 to Q: W = Q²/(2C) = ½CU² = ½QU.

Rearrangements

Voltage from the energy

U = \sqrt{\frac{2E}{C}}

For double the energy you only need √2 times the voltage.

Form with charge

E = \frac{Q^2}{2C}

Practical when the charge is given instead of the voltage.

Capacitance from energy and voltage

C = \frac{2E}{U^2}

This is how buffer capacitors are sized for an energy demand.

Task variant

The charging voltage of a capacitor is doubled. What happens to the energy?

E ∝ U²: the stored energy quadruples.

A defibrillator capacitor (C = 150 µF) is charged to 2,000 V. Find E.

E = ½ × 1.5×10⁻⁴ × (2,000)² = ½ × 1.5×10⁻⁴ × 4×10⁶ = 300 J.

Common mistakes

Dropping the factor ½ and computing E = CU².

The voltage only builds up during charging; on average only U/2 acts.

Confusing E = ½CU² with E = QU.

E = QU holds for charge through a fixed voltage; on a capacitor U rises along.

Not squaring U.

The energy grows quadratically with voltage, which is why flash capacitors are charged to high voltages.

Exam context

  • Exam classics: flash unit and defibrillator, energy comparison before/after inserting a dielectric, redistributing charge between two capacitors.

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

Formula cluster

Field energy

The energy resides in the electric field between the plates.

Worked example

A flash capacitor with C = 1,000 µF is charged to U = 300 V: E = ½ × 10⁻³ × 300² = ½ × 10⁻³ × 9×10⁴ = 45 J.

Applications

Camera flash, defibrillator, buffer storage in electronics, supercapacitors (regenerative braking)

Quanta exam set

Curated exam set for "Energy Stored in a Capacitor":

Question (front)

Which formula describes Energy Stored in a Capacitor?

Answer in your set

Question (front)

How do you rearrange E = ½CU² for Voltage from the energy?

Answer in your set

Question (front)

Which common mistake happens with Energy Stored in a Capacitor?

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

E=1/2*C*U^2E=0.5CU²W = ½CU²Kondensator Energie FormelEnergie elektrisches Feld Kondensatorcapacitor energy formulaE=Q^2/2CLadearbeit Kondensator

Related formulas

More Physics formulas

Frequently asked questions about Energy Stored in a Capacitor

How do you calculate the energy stored in a capacitor?+

Insert capacitance and charging voltage into E = ½·C·U². Example: a flash capacitor with C = 1,000 µF = 10⁻³ F charged to U = 300 V stores E = ½ × 10⁻³ × 90,000 = 45 J, enough for a powerful flash of light. The voltage enters squared and is the most effective lever: double the voltage, four times the energy. If the charge is given instead of the voltage, use the equivalent forms E = ½·Q·U or E = Q²/(2C). Mind the unit prefixes: convert microfarads to farads first (µ = 10⁻⁶), otherwise the result is off by orders of magnitude.

Where does the factor ½ in E = ½CU² come from?+

From the charging process: the voltage on the capacitor is not fully there from the start but grows with the charge from 0 to U. The first portion of charge is moved almost without opposing voltage, the last against the full voltage. On average only U/2 acts, so the charging work is W = Q·(U/2) = ½QU = ½CU². Graphically this is the triangular area under the Q-U line. The contrast makes it clear: pushing the charge Q through a fixed voltage U (say from a battery) takes energy Q·U, without the factor ½. Leaving it out wrongly doubles the capacitor energy, the standard exam mistake.

Why are flash units and defibrillators charged to high voltages?+

Because the energy grows quadratically with the voltage: E = ½CU². To store a lot of energy in a compact component it pays more to raise the voltage than to enlarge the capacitance; ten times the voltage brings a hundred times the energy. A defibrillator typically charges C = 150 µF to about 2,000 V: E = ½ × 1.5×10⁻⁴ × 4×10⁶ = 300 J, delivered within a few milliseconds. This shows the capacitor second strength: it can release its energy extremely fast, briefly reaching enormous power (here ~100 kW), which no battery manages. That is why capacitors serve wherever short, strong bursts of energy are needed.

Where is the energy in a capacitor actually located?+

In the electric field between the plates, not "in the charges" themselves. The modern view assigns the field an energy density: w = ½·ε₀·E² per unit volume (E being the field strength here). Integrated over the field volume of a parallel-plate capacitor this gives exactly ½CU²; both descriptions are equivalent. This field picture is more than formalism: it explains why pulling the plates apart requires energy input (the field volume grows) and extends all the way to electromagnetic waves, which transport field energy through empty space. In final exams this appears as a concept question: the carrier of the energy is the field, the capacitor merely its container.

Why is half the energy lost when charging through a resistor?+

Charging a capacitor from a fixed voltage source U through a resistor, the source delivers in total W = Q·U = C·U². Yet only E = ½CU² arrives in the capacitor; the other half inevitably becomes heat in the resistor, no matter how large R is. The reason: at the start almost the entire source voltage sits across the resistor, only at the end across the capacitor; integrated over the whole process the two share the energy exactly half and half. A smaller resistance only shortens the charging time (time constant τ = R·C) but does not change the 50% balance. In practice the loss is avoided with switched charging circuits or inductors, a popular advanced question.

Retain Energy Stored in a Capacitor for exams

Create a curated FSRS exam set for E = ½CU²: formula recall, variables, derivation, rearrangement, worked example, common mistakes and exam context.

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How do you calculate with Energy Stored in a Capacitor?

Here is how to work through a typical Energy Stored in a Capacitor (E = ½CU²) task step by step:

  1. 1

    Task

    The charging voltage of a capacitor is doubled. What happens to the energy?

    Solution path

    E ∝ U²: the stored energy quadruples.

  2. 2

    Task

    A defibrillator capacitor (C = 150 µF) is charged to 2,000 V. Find E.

    Solution path

    E = ½ × 1.5×10⁻⁴ × (2,000)² = ½ × 1.5×10⁻⁴ × 4×10⁶ = 300 J.

E = ½CU² · 10 cards ready

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