AyurBhasmaNanoparticleCharacterizationChecker
Ayur Bhasma Nanoparticle Characterization
ℹ️ Utility performs physicochemical characterization of nanoscale metallic Ayurvedic preparations according to AYUSH standards and API Part-II:
• Mean particle size (SEM/TEM/XRD): adaptive limits by Bhasma type
• Polydispersity Index (PDI): ≤0.30 (monodispersity)
• Free (unoxidized) metal: ≤0.5–2.0% (key safety parameter)
• Zeta potential: |ZP| ≥25 mV (colloidal stability)
• Dilute HCl solubility: marker of Marana (calcination) completeness
• Loss on Ignition (LOI): ≤2–3% (residual organics from Shodhana)
⚠️ WHY THIS IS NOT COVERED BY PH.EUR./USP/BHP:
Western pharmacopoeias control HEAVY METALS as CONTAMINANTS (ppm limits).
In Bhasma, metals are the ACTIVE SUBSTANCE (% content).
Therapeutic effect and safety of Bhasma are determined NOT by total content,
but by PARTICLE SIZE, OXIDATION STATE and PHASE COMPOSITION.
Particles >100 nm do not penetrate cell membranes → no effect.
Free metal dissolves in stomach → acute toxicity.
Nanoscale metal oxide/sulfide → therapeutic activity + safety.
Usage:
AyurBhasmaNanoparticleCharacterizationChecker.exe → demo mode
AyurBhasmaNanoparticleCharacterizationChecker.exe input.csv output.json → evaluate data
Input format:
BatchNumber,BhasmaType,MeanSize_nm,PDI,FreeMetal%,ZetaPotential_mV,AcidSolubility%,LOI%
Example:
AYUR-001,Swarna_Bhasma,28.5,0.18,0.3,-32.0,1.2,0.5
Adaptive limits by Bhasma type:
• Swarna (gold): ≤50 nm, free metal ≤0.5%, acid solubility ≤2%
• Loha (iron): ≤100 nm, free metal ≤1.0%, acid solubility ≤5%
• Tamra (copper): ≤80 nm, free metal ≤0.5%, acid solubility ≤3%
• Abhraka (mica): ≤200 nm, free metal ≤2.0%, acid solubility ≤8%
• Rajata (silver), Yasada (zinc): similar to Tamra/Loha
— PARAMETERS AND THEIR SIGNIFICANCE:
• Mean Particle Size: Determines bioavailability and cellular penetration.
>100 nm = not a nanoparticle = no Bhasma therapeutic effect.
• PDI (Polydispersity Index): Measure of size uniformity.
>0.3 = heterogeneous mixture = unpredictable pharmacokinetics.
• Free Metal: MOST CRITICAL SAFETY PARAMETER.
Free metal dissolves in gastric juice → ionic form → toxicity.
Properly prepared Bhasma contains metal as insoluble oxides/sulfides.
• Zeta Potential: Indicator of colloidal stability in liquid media.
|ZP| < 25 mV = particle aggregation = loss of nanoscale properties.
• Acid Solubility: Marker of Marana (calcination) process completeness.
High solubility = under-calcined product = danger.
• LOI: Residual organics from Shodhana reagents (plant juices, acids).
High LOI = incomplete purification/calcination.
💡 Usage tips:
1. Determine particle size by at least two methods (SEM + XRD) for cross-verification
2. Determine free metal by selective dissolution in dilute HCl followed by AAS/ICP
3. Measure zeta potential in physiological buffer (pH 7.4), not in water
4. Establish baseline reference values for each new Bhasma type
5. Correlate particle size with number of Marana cycles (putas)
6. Track trends: increasing size/PDI between batches = calcination process drift
⚠️ Note: This utility closes the most critical gap in Ayurvedic preparation quality control. Without nanoparticle characterization, it is impossible to distinguish therapeutic Bhasma from toxic metal powder. No Western pharmacopoeia has methods for this test. The utility is based on AYUSH Ministry (India) standards, API Part-II, and modern scientific data on Bhasma nanotoxicology.
input.csv
BatchNumber,BhasmaType,MeanParticleSize_nm,PDI,FreeMetalPercent,ZetaPotential_mV,AcidSolubilityPercent,LossOnIgnition_Percent AYUR-SWARNA-BH-2026-001,Swarna_Bhasma,28.5,0.18,0.3,-32.0,1.2,0.5 AYUR-LOHA-BH-2026-002,Loha_Bhasma,75.0,0.22,0.8,-28.0,3.5,1.0 AYUR-TAMRA-FAIL-2026-003,Tamra_Bhasma,120.0,0.45,3.5,-15.0,8.0,4.5 AYUR-ABHRAKA-2026-004,Abhraka_Bhasma,150.0,0.25,1.5,-30.0,6.0,2.5
AyurBhasmaNanoparticleCharacterizationChecker — URS & FS
Ayur Bhasma Nanoparticle Characterization Checker
Ayur Bhasma Nanoparticle Characterization Checker
1. Назначение документа
Документ описывает пользовательские требования (URS) и функциональную спецификацию (FS) для утилиты AyurBhasmaNanoparticleCharacterizationChecker. Утилита предназначена для детерминированной проверки данных input.csv, формирования структурированного результата output.json и поддержки прослеживаемого QA/QC review.
Документ является проектной URS/FS-основой для CSV/CSA, IQ/OQ/PQ и дальнейшей валидации в контексте конкретной лабораторной процедуры.
2. Исходное описание утилиты
3. URS — пользовательские требования
3.1 Цель и область применения
Система должна принимать табличные результаты лабораторного контроля, выполнять проверку по заранее заданным критериям и возвращать понятный статус по каждой серии/записи: Pass, Review или Fail.
3.2 Нормативная / методическая база
В исходном описании и правилах утилиты используются следующие ориентиры: AYUSH, API Part-I, API Part-II, USP, EP, Ph.Eur, Ph.Eur., BHP. Финальные лимиты должны быть подтверждены утверждённой спецификацией, монографией, SOP или протоколом трансфера метода.
3.3 Ключевые QC-проверки
- Средний размер частиц (SEM/TEM/XRD): адаптивные лимиты по типу Bhasma
- Полидисперсность (PDI): ≤0.30 (монодисперсность)
- Свободный (неокисленный) металл: ≤0.5–2.0% (ключевой параметр безопасности)
- Дзета-потенциал: |ZP| ≥25 мВ (коллоидная стабильность)
- Растворимость в разбавленной HCl: маркер завершённости Marana (кальцинации)
- Потеря при прокаливании (LOI): ≤2–3% (остаточная органика от Shodhana)
- Swarna (золото): ≤50 нм, свободный металл ≤0.5%, кислотная растворимость ≤2%
- Loha (железо): ≤100 нм, свободный металл ≤1.0%, кислотная растворимость ≤5%
3.4 Пользователи
- QC analyst — подготовка и загрузка
input.csv. - QA/QC reviewer — проверка результата и отклонений.
- CSV/validation specialist — подтверждение пригодности утилиты.
- System owner — управление версией, доступом и изменениями.
3.5 Требования к данным и Data Integrity
- каждая строка CSV должна быть прослеживаемой к серии, образцу или измерению;
- исходные значения не должны изменяться утилитой;
- расчёты должны быть воспроизводимыми при повторном запуске;
- любое отклонение должно сохраняться как структурированное finding с указанием поля и правила;
- ручное изменение итогового статуса вне QA-процесса не допускается.
4. FS — функциональная спецификация
4.1 Поток обработки
- Проверить наличие и кодировку
input.csv. - Проверить заголовки, обязательные поля и типы данных.
- Нормализовать числовые и булевы значения без изменения исходного следа.
- Выбрать набор правил по категории продукта/типа, если он предусмотрен.
- Сравнить значения с лимитами и вычислить derived metrics.
- Сформировать запись результата по каждой строке.
- Сохранить
output.jsonс общей сводкой, findings и traceability.
4.2 CSV-схема
| № | Поле CSV | Тип | Обяз. | Назначение |
|---|---|---|---|---|
| 1 | BatchNumber | string | Да | Идентификатор серии / лота для прослеживаемости. |
| 2 | BhasmaType | string | Да | Классификация для выбора адаптивных лимитов или набора правил. |
| 3 | MeanParticleSize_nm | decimal | Да | Входной атрибут для детерминированной оценки правил и прослеживаемости результата. |
| 4 | PDI | decimal | Да | Входной атрибут для детерминированной оценки правил и прослеживаемости результата. |
| 5 | FreeMetalPercent | decimal | Да | Измеренный аналитический результат для сравнения с критерием приемлемости. |
| 6 | ZetaPotential_mV | decimal | Да | Входной атрибут для детерминированной оценки правил и прослеживаемости результата. |
| 7 | AcidSolubilityPercent | decimal | Да | Классификация для выбора адаптивных лимитов или набора правил. |
| 8 | LossOnIgnition_Percent | decimal | Да | Измеренный аналитический результат для сравнения с критерием приемлемости. |
4.3 Пример входных данных
| BatchNumber | BhasmaType | MeanParticleSize_nm | PDI | FreeMetalPercent | ZetaPotential_mV | AcidSolubilityPercent | LossOnIgnition_Percent |
|---|---|---|---|---|---|---|---|
| AYUR-SWARNA-BH-2026-001 | Swarna_Bhasma | 28.5 | 0.18 | 0.3 | -32.0 | 1.2 | 0.5 |
| AYUR-LOHA-BH-2026-002 | Loha_Bhasma | 75.0 | 0.22 | 0.8 | -28.0 | 3.5 | 1.0 |
| AYUR-TAMRA-FAIL-2026-003 | Tamra_Bhasma | 120.0 | 0.45 | 3.5 | -15.0 | 8.0 | 4.5 |
| AYUR-ABHRAKA-2026-004 | Abhraka_Bhasma | 150.0 | 0.25 | 1.5 | -30.0 | 6.0 | 2.5 |
4.4 Выходной JSON
{
"utility": "AyurBhasmaNanoparticleCharacterizationChecker",
"runId": "urn:fuzkk:run:example",
"sourceFile": "input.csv",
"recordsProcessed": 4,
"overallStatus": "Pass / Review / Fail",
"records": [
{
"recordId": "AYUR-SWARNA-BH-2026-001",
"status": "Pass / Review / Fail",
"criticalFindings": [],
"warnings": [],
"evaluatedRules": [
"Configured acceptance criteria from the utility rule set"
],
"inputTrace": {
"BatchNumber": "AYUR-SWARNA-BH-2026-001",
"BhasmaType": "Swarna_Bhasma",
"MeanParticleSize_nm": "28.5",
"PDI": "0.18",
"FreeMetalPercent": "0.3",
"ZetaPotential_mV": "-32.0",
"AcidSolubilityPercent": "1.2",
"LossOnIgnition_Percent": "0.5"
}
}
],
"dataIntegrity": {
"deterministicEvaluation": true,
"sourceRowTraceability": true,
"manualOverrideAllowed": false
}
}
5. Трассировка URS → FS → тесты
| URS | FS-механизм | Проверка |
|---|---|---|
| Загрузка корректного input.csv | CSV parser + schema validator | OQ: валидный/невалидный CSV |
| Детерминированная оценка лимитов | Rule engine с фиксированной конфигурацией | OQ: граничные значения и known expected results |
| Статусы Pass/Review/Fail | Status aggregator по findings | OQ/PQ: образцы с проходными и провальными сериями |
| Прослеживаемость к исходной строке | inputTrace + recordId | PQ: сверка output.json с исходным CSV |
| Поддержка QA review | структурированные findings и warnings | PQ: review сценарии и deviation handling |
6. CSV/CSA и валидационный подход
IQ
- проверка версии утилиты;
- проверка расположения исполняемого файла;
- проверка шаблона CSV;
- контроль прав доступа.
OQ
- проверка обязательных полей;
- проверка типов данных;
- проверка граничных значений;
- проверка zero-tolerance правил.
PQ
- прогоны на реальных/репрезентативных данных;
- сверка с ручным расчётом;
- подтверждение QA review workflow.
Change control
- версионирование лимитов;
- impact assessment при изменении правил;
- регрессия после обновления.
1. Document purpose
This document defines user requirements (URS) and functional specification (FS) for AyurBhasmaNanoparticleCharacterizationChecker. The utility is intended to evaluate input.csv data deterministically, generate structured output.json output and support traceable QA/QC review.
This document is a project-level URS/FS baseline for CSV/CSA, IQ/OQ/PQ and further validation under an approved laboratory procedure.
2. Source utility description
3. URS — user requirements
3.1 Intended use and scope
The system shall accept tabular laboratory QC results, evaluate them against configured acceptance criteria and return a clear status for each batch or record: Pass, Review or Fail.
3.2 Regulatory / methodological basis
The source description and utility rules refer to the following framework: AYUSH, API Part-I, API Part-II, USP, EP, Ph.Eur, Ph.Eur., BHP. Final acceptance limits shall be confirmed by the approved specification, pharmacopoeial monograph, SOP or method-transfer protocol.
3.3 Key QC checks
- Mean particle size (SEM/TEM/XRD): adaptive limits by Bhasma type
- Polydispersity Index (PDI): ≤0.30 (monodispersity)
- Free (unoxidized) metal: ≤0.5–2.0% (key safety parameter)
- Zeta potential: |ZP| ≥25 mV (colloidal stability)
- Dilute HCl solubility: marker of Marana (calcination) completeness
- Loss on Ignition (LOI): ≤2–3% (residual organics from Shodhana)
- Swarna (gold): ≤50 nm, free metal ≤0.5%, acid solubility ≤2%
- Loha (iron): ≤100 nm, free metal ≤1.0%, acid solubility ≤5%
3.4 Users
- QC analyst — prepares and loads
input.csv. - QA/QC reviewer — reviews output, findings and deviations.
- CSV/validation specialist — confirms fitness for intended use.
- System owner — controls versioning, access and change management.
3.5 Data and data-integrity requirements
- each CSV row shall be traceable to a batch, sample or analytical measurement;
- source values shall not be modified by the utility;
- calculations shall be reproducible on repeated execution;
- each deviation shall be captured as a structured finding with field and rule references;
- manual override of the final status outside QA process is not allowed.
4. FS — functional specification
4.1 Processing flow
- Verify presence and encoding of
input.csv. - Validate headers, mandatory fields and data types.
- Normalize numeric and boolean values while preserving the source trace.
- Select an adaptive rule set by product/category type, where applicable.
- Compare values with limits and compute derived metrics.
- Create a result record for each input row.
- Write
output.jsonwith summary, findings and traceability.
4.2 CSV schema
| # | CSV field | Type | Req. | Purpose |
|---|---|---|---|---|
| 1 | BatchNumber | string | Yes | Batch / lot identifier used for traceability. |
| 2 | BhasmaType | string | Yes | Classification used to select adaptive limits or rule set. |
| 3 | MeanParticleSize_nm | decimal | Yes | Input attribute required for deterministic rule evaluation and output traceability. |
| 4 | PDI | decimal | Yes | Input attribute required for deterministic rule evaluation and output traceability. |
| 5 | FreeMetalPercent | decimal | Yes | Measured analytical result compared with the configured acceptance criterion. |
| 6 | ZetaPotential_mV | decimal | Yes | Input attribute required for deterministic rule evaluation and output traceability. |
| 7 | AcidSolubilityPercent | decimal | Yes | Classification used to select adaptive limits or rule set. |
| 8 | LossOnIgnition_Percent | decimal | Yes | Measured analytical result compared with the configured acceptance criterion. |
4.3 Input data example
| BatchNumber | BhasmaType | MeanParticleSize_nm | PDI | FreeMetalPercent | ZetaPotential_mV | AcidSolubilityPercent | LossOnIgnition_Percent |
|---|---|---|---|---|---|---|---|
| AYUR-SWARNA-BH-2026-001 | Swarna_Bhasma | 28.5 | 0.18 | 0.3 | -32.0 | 1.2 | 0.5 |
| AYUR-LOHA-BH-2026-002 | Loha_Bhasma | 75.0 | 0.22 | 0.8 | -28.0 | 3.5 | 1.0 |
| AYUR-TAMRA-FAIL-2026-003 | Tamra_Bhasma | 120.0 | 0.45 | 3.5 | -15.0 | 8.0 | 4.5 |
| AYUR-ABHRAKA-2026-004 | Abhraka_Bhasma | 150.0 | 0.25 | 1.5 | -30.0 | 6.0 | 2.5 |
4.4 Output JSON
{
"utility": "AyurBhasmaNanoparticleCharacterizationChecker",
"runId": "urn:fuzkk:run:example",
"sourceFile": "input.csv",
"recordsProcessed": 4,
"overallStatus": "Pass / Review / Fail",
"records": [
{
"recordId": "AYUR-SWARNA-BH-2026-001",
"status": "Pass / Review / Fail",
"criticalFindings": [],
"warnings": [],
"evaluatedRules": [
"Configured acceptance criteria from the utility rule set"
],
"inputTrace": {
"BatchNumber": "AYUR-SWARNA-BH-2026-001",
"BhasmaType": "Swarna_Bhasma",
"MeanParticleSize_nm": "28.5",
"PDI": "0.18",
"FreeMetalPercent": "0.3",
"ZetaPotential_mV": "-32.0",
"AcidSolubilityPercent": "1.2",
"LossOnIgnition_Percent": "0.5"
}
}
],
"dataIntegrity": {
"deterministicEvaluation": true,
"sourceRowTraceability": true,
"manualOverrideAllowed": false
}
}
5. Traceability URS → FS → tests
| URS | FS mechanism | Test evidence |
|---|---|---|
| Load valid input.csv | CSV parser + schema validator | OQ: valid/invalid CSV cases |
| Deterministic limit evaluation | Rule engine with fixed configuration | OQ: boundary values and known expected results |
| Pass/Review/Fail statuses | Status aggregator based on findings | OQ/PQ: passing and failing representative batches |
| Traceability to source row | inputTrace + recordId | PQ: output.json reconciliation to source CSV |
| QA review support | structured findings and warnings | PQ: review and deviation-handling scenarios |
6. CSV/CSA and validation approach
IQ
- utility version check;
- executable location check;
- CSV template check;
- access-right verification.
OQ
- mandatory field checks;
- data type checks;
- boundary-value checks;
- zero-tolerance rule checks.
PQ
- runs on real or representative data;
- comparison with manual calculation;
- confirmation of QA review workflow.
Change control
- rule and limit versioning;
- impact assessment for rule changes;
- regression after updates.
Included in packages
Ayurveda QC Suite
QC utility package for Ayurvedic products, botanical raw materials, Bhasma/Rasa Shastra, fermented preparations, lipid matrices and finished products.
Open